People

Alex Bui, PhD

Alex Bui, PhD

Director Medical Informatics Home Area

Dr. Bui received his PhD in Computer Science in 2000, upon which he joined the UCLA faculty and MII. His research includes informatics and data science for biomedical research and healthcare in areas related to distributed information architectures and mHealth; data and probabilistic modeling methods, including machine learning and sequential decision making; and data visualization. His work bridges contemporary computational approaches with the opportunities arising from the breadth of biomedical observations and the electronic health record (EHR), tackling the associated translational challenges.

Dr. Bui has a long history of leading extramurally funded research, including from multiple different NIH institutes (NCI, NLM, NINDS, NIBIB). He was Co-Director for the NIH Big Data to Knowledge (BD2K) Centers Coordination Center; and Application Lead for the NSF-funded Expeditions in Computing Center for Domain-Specific Computing (CDSC), exploring cutting-edge hardware/software techniques for accelerating algorithms used in healthcare. He is currently the Director of the NIH-funded Los Angeles PRISMS Center, a U54 focused on mHealth informatics. He is also a Program Director of three separate NIH T32s at UCLA in the areas of informatics, biomedical big data, and data science; and is Co-Director of UCLA CTSI’s Informatics Program and the Center for SMART Health.

Denise Aberle, MD, PhD

Denise Aberle, MD, PhD

Professor, Department of Radiological Sciences and Bioengineering, Vice Chair for Research, Department of Radiological Sciences

Following completion of a doctorate in medicine in 1979, Dr. Aberle completed residency training in internal medicine and subsequently in diagnostic radiology, with fellowship training in thoracic imaging. Dr. Aberle is a well-established clinical researcher. She is a leader in cancer screening trials, having spearheaded the National Lung Screening Trial (NLST), a multi-center endeavor and the largest prospective randomized imaging trial on lung cancer screening in the world. Additionally, she is involved in multiple NIH research projects. She serves in leadership capacities for multiple organizations, including ECOG-ACRIN (Eastern Cooperative Oncology Group-American College of Radiology Imaging Network), where she is Co-Chair of the Early Detection, Diagnosis, and Surveillance Committee and a member of the Executive Committee through which all clinical trials and research opportunities are approved. She also serves on the IASLC (Intl Association for the Study of Lung Cancer) Screening Executive Committee and Co-Chairs the Radiology Working Group. She has been awarded for her teaching excellence at UCLA and received awards for outstanding scientific leadership from ACRIN, the Society of Thoracic Radiology, the IASLC, the Academy of Radiology Research, and the inaugural award for Outstanding Achievement in Clinical and Translational Research from the UCLA Clinical Translational Science Institute (CTSI).

Corey Arnold, PhD

Corey Arnold, PhD

Director, Computational Diagnostics (CDx) Associate Professor, Departments of Radiological Sciences, Pathology & Laboratory Medicine, Bioengineering & Bioinformatics

Dr. Corey Arnold is an Associate Professor with a joint appointment in the UCLA Departments of Radiological Sciences and Pathology & Laboratory Medicine. He leads the Computational Diagnostics program, a joint effort between the departments. His areas of research include medical image analysis, computational phenotyping, natural language processing, and multi-scale predictive disease modeling, with a preference for problems that have a clear pathway to clinical translation. Most projects share the goal of integrating radiology, pathology, and -omic features to further our understanding of disease through the discovery of predictive computational phenotypes that may be used for risk stratification, treatment selection, and response monitoring. His lab also serves as a resource for department physicians, fellows, and residents who wish to incorporate machine learning/data science techniques into their research.

Douglas Bell, MD, PhD

Douglas Bell, MD, PhD

Professor, General Internal Medicine and Health Services Research, Program Director, UCLA Clinical Informatics Fellowship, Biomedical Informatics Program Leader, UCLA CTSI

Dr. Bell is a practicing general internist and a researcher focused on transforming health care through data science and information technology. He is a Professor in the UCLA Department of Medicine, Division of General Internal Medicine, and he leads the Informatics Program of the UCLA Clinical and Translational Science Institute (CTSI), which provides research access to electronic health record data, in compliance with privacy and security regulations. He is also Program Director of UCLA’s fellowship program in the new medical subspecialty of Clinical Informatics. Dr. Bell has conducted pioneering research in electronic prescribing, clinical decision support, online physician education, online surveys, and the digital divide among health care providers. He developed novel web-based learning software for studies of physician learning and retention. Dr. Bell is also an Adjunct Research Scientist at the RAND Corporation, where he has led research programs on electronic prescribing policy and clinical decision support technologies. Dr. Bell completed an MD at Harvard Medical School, a medical informatics fellowship at Harvard and MIT, a residency in internal medicine at Stanford, and a PhD in Health Services at UCLA.

Thomas Belin, PhD

Thomas Belin, PhD

Professor and Vice Chair of Biostatistics

Thomas R. Belin, PhD, is a Professor in the UCLA Department of Biostatistics and has served as departmental Vice Chair since 2012. His methodological interests have focused on causal inference and handling incomplete data, and building on a joint appointment in the Department of Psychiatry and Biobehavioral Sciences, his collaborative work has included wide-ranging applications in mental-health, health-services, and quality-of-life research. His work as chair of the Design Committee for Community Partners In Care, a community-partnered study of alternative strategies for disseminating evidence-based care for depression, was recognized with multiple awards including the 2014 Team Science Award from the Association for Clinical and Translational Science, and he has also received awards for published articles in the Journal of Mental Health Policy and Economics, the Journal of Oral and Maxillofacial Surgery, and the Journal of the American Academy of Child and Adolescent Psychiatry. Within the UCLA Department of Biostatistics, he has supervised 16 doctoral dissertations to completion and has served on more than 60 other doctoral dissertation committees, receiving an award from the UCLA Public Health Student Association in 2015 for outstanding advising and mentoring of doctoral students. He was elected to be a Fellow of the American Statistical Association in 2004, he received the Washington (D.C.) Statistical Society Gertrude M. Cox Award honoring a statistician making “significant contributions to statistical practice” in 2005, and he was named the Lowell Reed Lecturer for the American Public Health Association in 2018. He has been a member of the Sample Design and Survey Methodology Technical Advisory Committee for the UCLA-based California Health Interview Survey since its inception, and his professional activity has also included being a member of the Census Advisory Committee (2001-2006) and the Committee on Professional Ethics (2014-2019) for the American Statistical Association.

Sally Blower, PhD

Sally Blower, PhD

Professor-in-Residence, Psychiatry and Biobehavioral Sciences

Sally Blower, PhD, is a Professor in the David Geffen School of Medicine at the University of California at Los Angeles. She is a biomathematician and evolutionary biologist whose research focuses on developing models of transmission dynamics. She uses these models as health policy tools: to design epidemic control strategies for a variety of infectious diseases, to understand and predict the emergence of antibiotic and antiviral drug resistance, and to develop vaccination strategies. The main focus of her research is to develop the study of infectious diseases into a predictive science. Recently her work has focused on HIV, Syphilis, Genital Herpes, Smallpox, MRSA, Tuberculosis, Leprosy, Trachoma, and Influenza. She has also pioneered the application of innovative uncertainty and sensitivity techniques (based upon Monte Carlo methods and Latin Hypercube Sampling) to the analysis of transmission models. These techniques enable transmission models to be used to predict the future with a degree of uncertainty and to identify which parameters are critical in determining which future outcome will actually occur.

Professor Blower is the Head of the Disease Modeling Group at the David Geffen School of Medicine at UCLA and a member of the Advisory Board for the Program in Infectious Disease & Social Change at Harvard Medical School.

She is currently serving on the editoral/advisory boards of The Lancet Infectious Disease, BMC Medicine, BMC Biology, BMC Infectious Diseases, Human Vaccines, Journal of Molecular Epidemiology & Evolutionary Genetics and has served as a consultant to the Kaiser Family Foundation, CDC, WHO, RAND, EPA, Burroughs Wellcome, Glaxo Smith Kline, Aventis Pasteur, the Frankel Group, the Global HIV Prevention Working Group, and the International Partnership for Microbicides.

Paul Boutros, PhD

Paul Boutros, PhD

Professor, Department of Urology, Department of Human Genetics Director of Cancer Data Science, UCLA, Associate Director of Cancer Informatics, UCLA Institute for Precision Health

Dr. Paul Boutros pursued his undergraduate education at the University of Waterloo in Chemistry. During the co-op portion of his degree he worked for a wide range of organizations, including the Federal Government, a water-purification company and Petro-Canada. But he found his true calling during a work-term spent at Michigan State University developing computer models of how cells respond to drugs and toxins. Dr. Boutros’ undergraduate thesis extended this work to focus on modeling DNA damage, and was awarded First Place in the National Undergraduate Chemistry Conference.In 2004, Paul started his PhD at the Ontario Cancer Institute,in Toronto. During his studies he received several awards, including the CIHR/Next Generation First Prize and the Invitrogen Canada Young Investigator Silver Award. After publishing 27 peer-reviewed papers over four years,Paul was awarded his PhD in 2008 for his development of novel biomarkers for predicting cancer severity.

In 2008,Paul started his independent research career at the Ontario Institute for Cancer Research, as Principal Investigator in Informatics & Biocomputing, and Assistant Professor in the Departments of Pharmacology & Toxicology and Medical Biophysics at the University of Toronto. He is a Prostate Cancer Canada Rising Star in Prostate Cancer Research, a Terry Fox New Investigator Award recipient, a University of Waterloo Young Alumni Award winner and recipient of the Early Career Graduate Student Teaching Award. In 2016 he received his MBA from the University of Toronto, and in 2018 Paul was awarded the Dorval Prize by the Canadian Cancer Society, recognizing the best early career investigator nationally.

In 2018, Paul relocated to join the University of California, Los Angeles, taking on leadership roles at the Jonsson Comprehensive Cancer Centre and the Institute for Precision Health. As a Professor in the Departments of Human Genetics and Urology, his research focuses on personalizing therapy for cancer by developing novel statistical methodologies. He leads the ICGC-TCGA DREAM Somatic Mutation Calling Challenge that is setting global standards for analyzing cancer genomic data, and drives programs in cancer genomics, data science and biomarker translation.

Kai-Wei Chang, PhD

Kai-Wei Chang, PhD

Assistant Professor, Computer Science

I am an assistant professor in the department of Computer Science at UCLA. My research goal is to build intelligence systems that solve real-world problems by automatically acquiring knowledge. This challenging goal involves two fundamental components: A machine learning component that can efficiently make coherent decisions for problems with complex structures, and a natural language understanding component that enables the system to extract knowledge from unstructured text. I have been published broadly in machine learning, natural language processing, artificial intelligence, and data mining.

David Elashoff, PhD

David Elashoff, PhD

Professor of Medicine, Biostatistics and Computational Medicine Director, Department of Medicine Statistics Core

Dr. David Elashoff is a Professor of Medicine and Biostatistics at UCLA and Director of the Department of Medicine Statistics Core. He serves as Leader for the Biostatistics, Study Design and Clinical Data Management Program (BSD-CDM) for the UCLA CTSI. His main areas of statistical research are in developing statistical methods for the analysis of high throughput genomic and proteomic data. He has extensive collaborative experience on a variety of basic science, clinical research and clinical trials projects, including those with members of the School of Dentistry, Department of Medicine, Jonsson Comprehensive Cancer Center (JCCC), School of Nursing, and investigators at their partner institutions. As an investigator on the BSD-CDM, he collaborates with program leaders to implement the CTSI-wide network of biostatistics consulting services and develop joint research in genomics, proteomics, bioinformatics and clinical correlates. His collaborations with the Boston University CTSA have led to new funding this year from the NCI Early Detection Research Network Biomarker Discovery Laboratory Grant, identifying and validating early detection lung cancer biomarkers. He will continue to collaborate with CTSI investigators in both general statistics and in microarray and other genomic analysis. His membership on the Cancer Biomarkers Study Section of the NCI will continue and provide valuable insight to biomarkers and clinical relationships.

Sam Emaminejad, PhD

Sam Emaminejad, PhD

Assistant Professor, Department Electrical and Computer Engineering

Sam Emaminejad, PhD, is an Assistant Professor in the Electrical and Computer Engineering department at UCLA and the founder and director of the Interconnected & Integrated Bioelectronics Lab.

His lab focuses on the development of an ecosystem of integrated wearable, mobile, and in-vivo physiological and environmental monitoring platforms to enable personalized and precision medicine. Dr. Emaminejad, who received a PhRMA Research Starter Grant in Translational Medicine and Therapeutics in 2018, has received numerous honors and awards, including a Distinguished Young Investigator Award for leading a multi-center program on remote patient monitoring with UCLA, Intermountain Healthcare and Stanford School of Medicine.

Jason Ernst, PhD

Jason Ernst, PhD

Associate Professor, Biological Chemistry Associate Professor, Computer Science

ason joined the faculty at UCLA in the Department of Biological Chemistry, the Computer Science Department, and the Bioinformatics Program in 2012. Prior to that, he was a postdoctoral fellow in Manolis Kellis’ Computational Biology Group in the Computer Science and Artificial Intelligence Laboratory at MIT and affiliated with the Broad Institute. In 2008, Jason completed a PhD advised by Ziv Bar-Joseph where he was part of the Systems Biology Group, Machine Learning Department, and School of Computer Science at Carnegie Mellon University. Jason also earned BS degrees in Computer Science and Mathematics from the University of Maryland College Park in 2002.

Jason’s research focuses on developing and applying computational methods to address problems in epigenomics and gene-regulation. Jason serves on the editorial board at Genome Research and has been a program co-chair for the Regulatory Genomics Special Interest Group meeting at ISMB. He is a recipient of a Sloan Fellowship, NSF CAREER Award, NSF Postdoctoral Fellowship, a Siebel Scholarship, and a Goldwater Scholarship.

Eleazar Eskin, PhD

Eleazar Eskin, PhD

Professor and Chair Department of Computational Medicine, Professor Computer Science Human Genetics

Eleazar Eskin is a computer scientist and geneticist, professor and Chair of the Department of Computational Medicine, and professor of computer science and human genetics at the University of California, Los Angeles. His research focuses on bioinformatics, genomics, and machine learning.

Nelson Freimer, MD

Nelson Freimer, MD

Director of the Center for Neurobehavioral Genetics, Professor of Psychiatry, Associate Director for Research Programs of the Semel Institute for Neuroscience and Human Behavior

Dr. Nelson Freimer is Director of the Center for Neurobehavioral Genetics and Professor of Psychiatry at UCLA and Associate Director for Research Programs of the Semel Institute for Neuroscience and Human Behavior. He also directs UCLA core facilities in genomics and neuroscience (The Informatics Center for Neurogenetics and Neurogenomics, The UCLA Neuroscience Genomics Core, and The Biological Samples Processing Core). He is Director of the NINDS-funded Postdoctoral Training Program in Neurobehavioral Genetics, and Co-Director of UCLA Neuroscience. Dr. Freimer received an M.D. degree from the Ohio State University, and completed residency training in psychiatry (at UC San Francisco) and a postdoctoral fellowship in human genetics (at Columbia University). He joined the UCLA faculty in 2000 after 10 years on the faculty at UC San Francisco.

The research in Dr. Freimer’s laboratory aims to use large scale genomics methods to identify the genetic basis of complex traits, particularly neurobehavioral disorders including bipolar disorder, schizophrenia, depression, and Tourette Syndrome. He has also conducted large-scale genomics studies of metabolic phenotypes and cardiovascular disorders. His research group has pioneered in whole genome sequencing studies of such disorders as well as the application of large-scale genomics to our understanding of non-human primates.

Daniel Geschwind, MD, PhD

Daniel Geschwind, MD, PhD

Gordon and Virginia MacDonald Distinguished Professor, Neurology Psychiatry and Human Genetics Senior Associate Dean and Associate Vice Chancellor, Precision Health Director, Institute of Precision Health

Dr. Geschwind is the Gordon and Virginia MacDonald Distinguished Professor of Human Genetics, Neurology and Psychiatry at UCLA. In his capacity as Senior Associate Dean and Associate Vice Chancellor of Precision Health, he leads the Institute for Precision Health (IPH) at UCLA, where he oversees campus precision health initiatives. In his laboratory, his group has pioneered the application of systems biology methods in neurologic and psychiatric disease, with a focus on autism spectrum disorders (ASD) and neurodegenerative conditions. His group defined the molecular pathology of autism using gene network analysis and has extended these integrative genomics methods so as to elucidate the mechanisms by which genetic risk for neuropsychiatric disease perturbs brain development and function. In addition to serving on several scientific advisory boards, including the Faculty of 1000 Medicine, the Scientific Advisory Board for the Allen Institute for Brain Science, the NIMH Advisory Council and the NIH Council of Councils, he currently serves on the editorial boards of Cell, Neuron and Science. He has has received several awards for his laboratory’s work is an elected Member of the American Association of Physicians and the National Academy of Medicine.

David Gjertson, PhD

David Gjertson, PhD

Professor, Pathology & Laboratory Medicine

Research Interest: Since joining the faculties of each of the Departments of Biostatistics and Surgery in 1990, my research has focused on statistical issues related to two main topics - organ transplantation and DNA identification. In the transplantation arena, I have assisted in the investigation of novel organ allocation schemes which promise equitable allocation of scarce compatible kidneys even for small pools and for minority patients. My research has also centered on elucidating (via standard and Bayesian methodologies) the factors most strongly influencing long-term graft survival and predicting chronic organ failure. With regard to DNA identification, I have been able to follow-up my thesis research (concerning proper statistical interpretation of evidence) through collaboration with Long Beach Genetics, Inc., a genetic testing laboratory. Generally, my work involves deriving likelihoods of pedigrees based on DNA profiles with special problematic circumstances like mutation, population substructure or relatives as possible suspects.

Eran Halperin, PhD

Eran Halperin, PhD

Professor in the departments of Computer Science, Computational Medicine, Anesthesiology, and Human Genetics.

Dr. Eran Halperin is a professor in the departments of Computer Science, Computational Medicine, Anesthesiology, and Human Genetics. He is also the associate director of informatics in the Institute of Precision Health at UCLA and the co-director of the Computation Genomics Summer Institute at UCLA. Dr. Halperin received his Ph.D. in computer science from Tel-Aviv University. Prior to his current position, he held research and postdoctoral positions at the University of California, Berkeley, the International Computer Science Institute in Berkeley, Princeton University, and Tel-Aviv University.

Dr. Halperin is a computational biologist who develops statistical and computational methods for the analysis of human genetic and epigenetic variation in the context of complex human diseases. His group has developed methods and software that have been used by hundreds of researchers worldwide to understand the genetic causes of diseases such as cardiovascular diseases, non-Hodgkin’s lymphoma, and breast cancer.

Dr. Halperin has published over 100 peer-reviewed articles across different disciplines such as human genetics, computational biology, and theoretical computer science. He received various honors for academic achievements, including the Rothschild Fellowship, the Technion-Juludan prize, and the Krill Prize.

Steve Horvath, PhD

Steve Horvath, PhD

Professor of Human Genetics & Biostatistics

Dr Horvath is an aging researcher and bioinformatician whose research lies at the intersection of epidemiology, chronic diseases, epigenetics, genetics, and systems biology. He developed systems biologic approaches such as weighted gene co-expression network analysis. He works on all aspects of biomarker development with a particular focus on genomic biomarkers of aging. He developed a highly accurate multi-tissue biomarker of aging known as the epigenetic clock. Salient features of the epigenetic clock include its high accuracy and its applicability to a broad spectrum of tissues and cell types. He develops and applies methods for analyzing and integrating gene expression-, DNA methylation-, microRNA, genetic marker-, and complex phenotype data. His lab members apply and develop data mining methods to study a broad spectrum of diseases, e.g. aging research, cancer, cardiovascular disease, HIV, Huntington’s disease, neurodegenerative diseases.

William Hsu, PhD

William Hsu, PhD

Associate Professor, Department of Radiological Sciences and Bioengineering

I am Associate Professor in Residence in the Department of Radiological Sciences, Bioinformatics, and Bioengineering and a member of the Medical & Imaging Informatics group. I am also affiliated with the Institute of Quantitative and Computational Biosciences (QCB), UCLA Medical Informatics Home Area, and Jonsson Comprehensive Cancer Center. I actively collaborate with faculty members in the Center for Domain-Specific Computing, Clinical & Translational Science Institute, and UCLA-PKU Joint Research Institute. I currently serve as Chair of the AMIA Biomedical Imaging Informatics Working Group, a section co-editor for the IMIA Yearbook of Medical Informatics and a deputy editor for Radiology: Artificial Intelligence.

In the current data-rich healthcare environment, our capacity to collect vast amounts of longitudinal observational data needs to be matched with a comparable ability to continuously learn from the data and enable individually tailored medicine. My research focuses on the systematic integration of information across different data sources to improve the performance and robustness of clinical prediction models. I direct the Integrated Diagnostics Shared Resource, which is an interdepartmental resource that prospectively collects clinical, imaging, and molecular data to improve the detection and characterization of early-stage cancer. I also lead a team of postdoctoral fellows and graduate students who are developing computational tools that harness clinical, imaging, and molecular data to aid physicians with formulating timely, accurate, and personalized management strategies for individual patients. We adapt and validate novel artificial intelligence/machine learning algorithms, translating them into applications that enable precision medicine. My team works on problems related to data wrangling, knowledge representation, machine learning, and interpretation. We utilize a wide spectrum of approaches from statistical approaches to machine and reinforcement learning, depending on the problem at hand. I work closely with a team of software developers and analysts who harden and translate research products into real-world applications that improve the practice of radiology.

Bahram Jalali, PhD

Bahram Jalali, PhD

Professor and Northrop Grumman Opto-Electronic Chair in Electrical Engineering

Bahram Jalali is a Professor of Electrical Engineering at UCLA. He is a Fellow if IEEE and the Optical Society of America, and the Chair of the Los Angeles Chapter of the IEEE Lasers and Electro Optics Society (LEOS). His research interests include silicon photonics and techniques for ultra fast data generation and capture. He has published over 200 scientific papers and holds 6 US patents. He is the recipient of the 2007 R.W. Wood Prize from the Optical Society of America. In 2005, he was chosen by the Scientific American Magazine as the 50 Leaders Shaping the Future of Technology. His work in demonstration of the first silicon laser was cited by the MIT Technology Review magazine as the top 10 technology trends in 2005. While on leave from UCLA from 1999-2001, Dr. Jalali founded Cognet Microsystems, a Los Angeles based fiber optic component company. He served as the company’s CEO, President and Chairman, from its inception through acquisition by Intel Corporation in 2001. From 2001-2004, he was a consultant for Intel Corporation. Dr. Jalali serves on the Board of Trustees of the California Science Center. He has received the BridgGate 20 Award for his contributions to the southern California economy.

Robert Jenders

Robert Jenders

Professor, Department of Medicine

Robert A. Jenders, MD, MS, FACP, FACMI is professor in the Department of Medicine at the University of California, Los Angeles (UCLA). His work focuses on clinical decision support systems, electronic health records and vocabularies. A general internist and fellow of the American College of Physicians and the American College of Medical Informatics, he provides clinical care and teaches in the graduate medical education programs of the Department of Medicine.

William Kaiser, PhD

William Kaiser, PhD

Professor, Department of Electrical Engineering

William Joseph Kaiser is a professor and former department chair of Electrical Engineering at the University of California, Los Angeles (UCLA). He is a winner of 2007 Gold Shield Prize and has been a Fellow of American Vacuum Society since 1994. He is the director of Actuated Sensing & Coordinated Embedded Networked Technologies research group at UCLA and co-director of UCLA Wireless Health Institute.

Jennifer Labus, PhD

Jennifer Labus, PhD

Director, Neuroimaging and Biostatistics Core, Oppenheimer Center for Neurobiology of Stress; Associate Professor, Division of Digestive Diseases

Dr. Labus applies an approach based on system biology using bioinformatics, network analyses, supervised and unsupervised machine learning tools to integrate multimodal brain imaging data with other large scale biological data sets including genetics and metabolomics. This research provides the means to integrate and decipher large amounts of multivariate neuroimaging data to subgroup patients based on objective biological markers, and characterize central nervous system alterations for further pathophysiological investigations targeting treatment of chronic pain and obesity.

Ning Li, PhD

Ning Li, PhD

Associate Professor, Division of General Internal Medicine and Health Services Research

Dr. Li recieved her Ph.D in 2005. Her research interests are in the areas of longitudinal analysis, missing data in longitudinal studies, joint modeling of longitudinal and time-to-event data. She has extensive statistical consulting and collaborative experience with investigators in many areas of biomedical research.

Li-Jung Liang, PhD

Li-Jung Liang, PhD

Professor, Division of General Internal Medicine and Health Services Research

Dr. Liang received her Ph.D. in Biostatistics from UCLA in 2005. Prior to her doctoral studies, she worked in the pharmaceutical and biotechnology industries for over 10 years. Her statistical research interests are hierarchical (multi-level) modeling, longitudinal data analysis, Bayesian methods, Markov model, and Markov chain Monte Carlo computation. She works with collaborators in several application areas, HIV/AIDS, bioinformatics, clinical trials, behavioral and social sciences, and nutrition.

Ali Mosleh, PhD

Ali Mosleh, PhD

Distinguished Professor, Evelyn Knight Chair in Engineering, and Director of the B. John Garrick Institute for the Risk Sciences

Ali Mosleh is a Distinguished University Professor, holder of the Evelyn Knight Endowed Chair in Engineering, and Director of UCLA’s B. John Garrick Institute for the Risk Sciences. He also holds honorary appointments at six other universities internationally. He was elected to the National Academy of Engineering in 2010 and is a Fellow of the Society for Risk Analysis, and the American Nuclear Society, recipient of several scientific achievement awards, including the American Nuclear Society Tommy Thompson Award. He has been technical advisor to numerous national and international organizations. He conducts research on methods for probabilistic risk analysis and reliability of complex systems, holds several patents, and has authored or co-authored over 650 publications.

Arash Naeim, MD, PhD

Arash Naeim, MD, PhD

Chief Medical Officer for Clinical Research

Arash Naeim, M.D., Ph.D., is a health professional whose career has spanned a combination of health services, informatics, health policy and quality of care issues. He earned his B.S. in Biochemistry and M.D. in Medicine at the University of California, and received a Ph.D. in Public Policy from the RAND Corporation. He currently serves as Professor of Medicine in the divisions of Hematology-Oncology and Geriatric Medicine at the David Geffen UCLA School of Medicine and Professor of Bioengineering in the Henry Samueli School for Engineering and Applied Sciences .

He also holds key organizational roles at UCLA. Dr. Naeim is Chief Medical Officer for Clinical Research for UCLA Health. He is a Associate Director for the Clinical & Translational Science Institute, Institute for Precision Health, and Garrick Institute for Risk Science, as well as a Senior Leader and Director of Informatics for the Jonsson Comprehensive Cancer Center,. Dr. Naeim is also very involved in information technology implementation and research. He is a board certified Clinical Informatics and is a Physician Informaticist for UCLA Health. He provide oversight and support to the Clinical Research Information Systems and the Care Connect Research Team. He is a Founder and Co-Director for the Center for SMART Health.

His primary research focus is on breast cancer, and other research interests include outcomes research, cost-effectiveness analysis, modeling of health and frailty, and clinical trial design. In 2009, Naeim was selected as the principal investigator for the Athena Breast Health Network, and is the site PI for a large pragmatic trial, the WISDOM Study funded by PCORI, providing risk-based breast cancer screening recommendations to patients. He has had R01 funding looking at the use of wearable technology in at-risk frail elderly populations, and his sensing platform has a provisional patent filed.

Stan Nelson, MD

Stan Nelson, MD

is Professor and Vice Chair of Human Genetics and Professor of Psychiatry

Stanley F. Nelson, MD is Professor and Vice Chair of Human Genetics and Professor of Psychiatry within the David Geffen School of Medicine at UCLA where he has been on faculty since 1993. Prof. Nelson attended the University of Michigan and obtained a BS degree in Physics in 1982. He graduated from Duke University School of Medicine in 1987 and completed an ITT International Fellowship to Sweden in the Laboratory of George Klein. He was trained in Pediatrics and Pediatric Hematology-Oncology at UCSF School of Medicine, and subsequently trained as a postdoctoral fellow with Patrick Brown from 1990-1993 where he developed genomic mismatch scanning and initiated the lab development of DNA microarrays for genomic applications. At UCLA, Prof. Nelson has continued to be interested in technology development and application of genomics to cancer biology and common human diseases with active research areas in Autism, ADHD, vertigo and brain cancers. He developed and led the first genomics core on UCLA campus ( UCLA DNA Microarray Facility). He led the whole genome expression array analysis for the NIH Neuroscience Blueprint. With a team in Pathology and Pediatrics, he implemented whole exome sequencing for clinical purposes in 2011. He formed the Center for Duchenne Muscular Dystrophy in 2007 with Drs. Miceli and Spencer that has grown into a unique center that provides coordinated patient care, access to clinical trials, translational and basic research, and educational opportunities on campus. In 2014, he initiated with others, the Undiagnosed Diseases Network UCLA Clinical Site to improve diagnosis of individuals with difficult to diagnose genetic disorders. His laboratory continues to develop and use genomic techology to pursue biological insights that lead to new therapeutic interventions in humans.

Lola Ogunyemi, PhD

Lola Ogunyemi, PhD

Assistant Professor, Department of Radiological Sciences

Dr. Ogunyemi‘s research interests include computerized medical decision support, reasoning under uncertainty, 3D graphics and visualization, and machine learning. Her research focuses on developing and evaluating novel computerized decision support systems for different biomedical domains with an emphasis on assisting clinicians in medically underserved settings. She has been principal investigator on a National Library of Medicine-funded study of computerized decision support for penetrating trauma, and on a National Cancer Institute-funded study of individualized breast cancer risk prediction using Bayesian networks. She is currently co-director of the biomedical informatics function for CDU’s Accelerating eXcellence In translational Science(AXIS, http://axis.cdrewu.edu/) grant and a co-chair of the UCLA CTSI’s biomedical informatics program, representing CDU.

Dr. Ogunyemi holds an undergraduate degree in Computer Science from Barnard College, Columbia University and an M.S.E, and Ph.D. in Computer and Information Science from the University of Pennsylvania. Before moving to Charles Drew University in 2007 to become the Director of the Center for Biomedical Informatics, Dr. Ogunyemi was biomedical informatics faculty in the Department of Radiology at Brigham and Women‘s Hospital and Harvard Medical School from 1999 until 2007. She was also a member of the affiliated faculty in the Harvard-MIT Division of Health Sciences and Technology from 2003 until 2007. She has taught graduate level biomedical informatics courses in the Harvard-MIT Division of Health Sciences and Technology, at UCLA, and short courses on informatics at the University of Natal, Durban, South Africa. She served on the National Library of Medicine’s Biomedical Library and Informatics Review Committee study section from 2003-2007, on the National Library of Medicine’s Literature Selection and Technical Review Committee as a member (2010-2014), and as chair (2013-2014), and is an editorial board member of the Journal of Biomedical Informatics (2015 - 2018).

Michael Ong, MD, PhD

Michael Ong, MD, PhD

Professor in Residence of Medicine & Health Policy and Management

Michael Ong, MD PhD, is a Professor in Residence of Medicine & Health Policy and Management at UCLA. He is Chief of the Hospitalist Division at the VA Greater Los Angeles Healthcare System. Dr. Ong is a practicing general internist. His research interests focus on improving the delivery of appropriate and efficient health care by general internal medicine physicians. His research has applied this focus in several areas of general medicine, including hospital-based care, mental health, and tobacco control. Dr. Ong co-directs the new Stakeholder-Partnered Implementation Research and Innovation Translation (SPIRIT) Learning Health System (LHS) Center of Excellence in LHS Researcher Training funded by the Agency for Healthcare Research and Quality and the Patient Centered Outcomes Research Institute. He co-leads the BreatheWell and ResearchWell Pods for the Semel Healthy Campus Initiative Center at UCLA. Dr. Ong is currently Chair of the State of California Tobacco Education and Research Oversight Committee.

Aydogan Ozcan, PhD

Aydogan Ozcan, PhD

Chancellor’s Professor and HHMI Professor

Dr. Aydogan Ozcan received his Ph.D. degree at Stanford University Electrical Engineering Department. After a short post-doctoral fellowship at Stanford University, he was appointed as a research faculty at Harvard Medical School, Wellman Center for Photomedicine in 2006. Dr. Ozcan joined UCLA in 2007 and he is currently the Chancellor’s Professor at UCLA and an HHMI Professor with the Howard Hughes Medical Institute, leading the Bio- and Nano-Photonics Laboratory at UCLA Electrical Engineering and Bioengineering Departments, and is also the Associate Director of the California NanoSystems Institute (CNSI) at UCLA. Full bio link: https://innovate.ee.ucla.edu/prof-ozcan-brief-biosketch.html

Matteo Pellegrini, PhD

Matteo Pellegrini, PhD

Professor, Molecular, Cell, and Developmental Biology

Matteo Pellegrini is a biophysicist who has served on the UCLA Life Sciences Division faculty since he joined the Department of Molecular, Cell and Developmental Biology in 2005. Dr. Pellegrini earned his B.A. in Physics at Columbia University and his Ph.D. in Physics at Stanford. He was a postdoctoral fellow at UCLA, where he worked on computational biology. Following his postdoctoral studies Dr. Pellegrini co-founded a start-up company and later worked for the pharmaceutical company Merck before returning to UCLA. His laboratory research centers on the development of novel computational approaches to reverse engineer biomolecular networks. Professor Pellegrini is also a member of the California NanoSystems Institute (CNSI).

Peipei Ping, PhD

Peipei Ping, PhD

Professor, Department of Physiology, Medicine in Cardiology, Medical Informatics, and Bioinformatics

Dr. Ping received her B.S. degree in Biomedical Engineering with a minor in Mathematics from Zhejiang University in China. Subsequently, she completed her graduate training in the United States with a Ph.D. in Cardiovascular Physiology and a postdoctoral training in Molecular Cardiology. Currently she is a Professor of Physiology, Medicine/cardiology, Medical Informatics, and Bioinformatics at UCLA DG School of Medicine. Over the past 25 years, her research program has focused on cardiac physiology, functional proteomics, mitochondrial biology, and data science. From 2014-2019, Dr. Ping has served as the Directors of NIH BD2K Center of Excellence in Biomedical Computing (HeartBD2K Center) and the BD2K Centers Coordination Center (BD2KCCC) at UCLA. Currently she is the Director of NHLBI Integrated Data Science Training Program in Cardiovascular Medicine (IDISCOVER) at UCLA School of Medicine and the associate Director of Scalable Analytics Institute (ScAi) at UCLA School of Engineering.

Throughout her entire career, Dr. Ping has been passionate about education. She has mentored 90+ trainees; all of them are making important contributions to our society. Among them, 17 individuals hold positions in academic institutions globally; including UCLA, UC Davis, University of Colorado, University of Heidelberg, and Fudan University. In parallel, 45 students underwent data science training in her program and continued their careers in technology industry. They hold engineer or equivalent positions in 27 companies across the world; many are Fortune 500 leaders, including Apple, Google, Microsoft, Amazon, and Ericsson.

Dr. Ping has authored over 211 peer-reviewed publications, with a Google Scholar H index of 85 and over 28,800 citations. She has dedicated her services to many professional organizations. She was a Founding Council Member of Human Proteome Organization (HUPO) and served as Secretary General for both USHUPO and International HUPO. She received multiple honorable awards, including the Thomas W Smith Lectureship from the American Heart Association (AHA, 2012), the Distinguished Service Award from the Human Proteome Organization (HUPO, 2013), the Robert M Berne Distinguished Lectureship in Cardiovascular Medicine from the American Physiological Society (APS, 2015), the Outstanding Investigator Award (OIA:R35) from NHLBI/NIH (2017), the Clinical Translational Award on Proteomic Sciences from International HUPO (2018), and the A. Ross McIntyre Endowed Lectureship from University Nebraska Medical Center (2019). Please see details of Dr. Ping’s research focus at the homepage of her lab (https://cvdatascience.dgsom.ucla.edu/).

Mindy Ross, MD

Mindy Ross, MD

Pediatric Pulmonology Specialist

Dr. Ross attended undergraduate school at UC Los Angeles (UCLA) and received her medical degree from UC San Diego (UCSD). She completed her pediatric residency and pulmonary fellowship at Rady Children’s Hospital in San Diego through UCSD. She joined the UCLA Pediatric Pulmonology group in 2015. During her pulmonary fellowship she was trained in clinical informatics, which is the use of information technology to deliver healthcare. Her research is to create a more personalized asthma care using the electronic health record. She is board certified in pediatrics, pediatric pulmonology, and clinical informatics.

Her clinical interests include caring for patients with asthma, chronic lung disease, chronic cough, and quality improvement. She attends on the inpatient pediatric wards as a consultant at UCLA Mattel Children‘s Hospital and UCLA Medical Center Santa Monica. She provides outpatient clinical care at the Children’s Health Center (200 Medical Plaza, Westwood).

Majid Sarrafzadeh, PhD

Majid Sarrafzadeh, PhD

Professor of Computer Science & Electrical Engineering

Majid Sarrafzadeh received his Ph.D. in 1987 from the University of Illinois at Urbana-Champaign in Electrical and Computer Engineering. He joined Northwestern University as an Assistant Professor in 1987. In 2000, he joined the Computer Science Department at University of California at Los Angeles (UCLA) where he is current a distinguished professor of Computer Science and Electrical Engineering. He is a co-founder and co-director of the Center for SMART Health. His recent research interests lie in the area of Embedded Computing and Data Anlytics with emphasis on healthcare. Dr. Sarrafzadeh is a Fellow of IEEE. Professor Sarrafzadeh has published more than 550 papers, co-authored 5 books, and is a named inventor on many US patents.

Dr. Sarrafzadeh has collaborated with many industries in the past 30 years. He co-founded two companies around 2000 – they were both acquired around 2004. He has recently co-founded three companies in the area of Technology in Healthcare.

Alcino Silva, PhD

Alcino Silva, PhD

Director, Behavioral Testing Core Distinguished Professor, Psychology Behavioral Neuroscience Director, ICLM Distinguished Professor, Tennenbaum Center for the Biology of Creativity Neurobiology

Alcino Silva got his Bachelor of Science from Rutgers University in 1979. There, he worked with William Sofer on Drosophila tRNA non-sense suppressors and minored on philosophy (epistemology). In 1983 he joined the graduate program of human genetics at the University of Utah, where he worked with Ray White, a pioneer in Human Genetics, on the inheritance of epigenetic information (Silva et al, 1988; Cell PMID: 2898978). During his post-doctoral work at the Massachusetts Institute of Technology with Nobel Laureate Dr. Susumu Tonegawa (1988-92), Dr. Alcino J. Silva introduced transgenic mice to neuroscience studies of learning and memory and pioneered the field of Molecular and Cellular Cognition (Silva et al, Science 1992, PMIDs 1321493 &1378648). His first independent position (1992) was with the Cold Spring Harbor Laboratory, NY, where his research group had a key role in the development of Molecular and Cellular Cognition into a mainstream neuroscience field. In 2002 Dr. Silva founded and became the first President of the Molecular and Cellular Cognition Society, an international organization with more than 7000 members and with branches in North America, Asia and Europe. Besides work on molecular, cellular and circuit approaches to cognition, his laboratory also develops bioinformatics strategies to address the growing complexity of the literature, including the development of a set of algorithms and a free web app (researchmaps.org) to track causal information in biology. In 2006/2007 Dr. Silva served as Scientific Director of the Intramural Program of the National Institute of Mental Health. He is currently a Distinguished Professor in the Departments of Neurobiology, Psychiatry & Biobehavioral Sciences, and Psychology, and directs the Integrative Center for Learning and Memory. He has been awarded a number of prizes and distinctions, including most recently the Order of Prince Henry (2008), the Senior Roche Award For Translational Neuroscience (2009), and in 2012 he was elected a Fellow of the American Association for the Advancement Science.

Myung-Shin Sim

Myung-Shin Sim

Associate Professor, Division of General Internal Medicine and Health Services Research
William Speier, PhD

William Speier, PhD

Assistant Professor, Department of Radiological Sciences

Robotics, natural language processing, and machine learning have made amazing advances over the past few decades, with significant time and funding dedicated to development of countless applications of these fields. Nevertheless, no machine-based system can match the versatility or robustness of the human brain; human-created language and image processing systems are vastly inferior to their biological counterparts; and human decisions and mechanical actions remain the gold standard in the medical field. The goal of my research is to bridge the gap between the brain and machine applications through:

- Learning the underlying processes in the function of the human brain
- Creating interfacing software to facilitate brain-machine interaction
- Developing closed-loop systems to modulate patient treatment based on their physiological state

Yizhou Sun, PhD

Yizhou Sun, PhD

Associate Professor, Department of Computer Science

I am currently an associate professor at Computer Science, UCLA. Prior to that, I joined Northeastern University as an assistant professor in 2013. I received my Ph.D. degree from Computer Science Department, University of Illinois at Urbana Champaign (UIUC) in December 2012. I got my master degree and bachelor degrees in Computer Science and Statistics from Peking University, China.

Peter Szilagyi, MD

Peter Szilagyi, MD

Professor and Vice-Chair for Clinical Research in the Department of Pediatrics
Ricky Taira, PhD

Ricky Taira, PhD

Professor, Department of Radiological Sciences

Dr. Ricky Taira obtained his Bachelor’s degree in electrical engineering in 1982, and went on to receive a PhD in biomedical physics in 1988 from UCLA. He is now a Professor in the Department of Radiological Sciences at UCLA’s David Geffen School of Medicine. His past research interests have included picture archive and communication systems (PACS), medical knowledge bases (the KMeD project) for intelligent patient case retrieval, and structuring clinical observations for disease modeling. Currently, his main research focus is on developing a cognitively inspired natural language processing system (NLP) for clinical reports. He is the co-PI and investigator of several NIH-funded grants. Dr. Taira is the UCLA site PI for a telemedicine screening grant for diabetic retinopathy in collaboration with Charles Drew University and the Los Angeles County of Health Services. Dr. Taira teaches courses in medical knowledge representation and medical imaging informatics that are part of the UCLA Medical and Imaging Informatics interdisciplinary training program.

Chi-hong Tseng, PhD

Chi-hong Tseng, PhD

Professor, Division of General Internal Medicine and Health Services Research

Dr. Tseng received his Ph.D in Biostatistics from UCLA in 2004. His research interest includes design of clinical trials, survival analysis, multiple comparisons problem, and statistical genetics. He has extensive collaborative experience in cardiology, infectious disease, pulmonary, nephrology, cancer, and health services studies.

Mihaela van der Schaar, PhD

Mihaela van der Schaar, PhD

Chancellor’s Professor

Mihaela Van der Schaar’s current research interest is on machine learning, AI and data science for medicine. She has helped to pioneer new machine learning and data science theory and methods for clinical risk prediction (including competing risks), predictions of disease trajectories based on repeated measures, causal inference and individualized treatment effects, data imputation methods (including for longitudinal data and data that is informatively missing), operation research methods for developing personalized screening policies, and new methods for making machine learning predictions interpretable. These methods have been successfully applied for risk prediction and management of many diseases (including cardiovascular diseases, heart transplantation, cancer, cystic fibrosis, asthma). She is also developing machine learning and data science methods to enable personalized education of students and professionals.

Besides machine learning and data science, van der Schaar‘s research expertise spans signal processing, multimedia, communication networks, network science, game theory and distributed systems. Her research work has been widely cited and several of her papers received best paper awards, including the prestigious IEEE Circuits & Systems Society Darlington Award. In addition, van der Schaar’s work has also led to 33 US patents (many widely cited and adopted in standards) and 45+ contributions to international standards. Her work has received many recognitions and awards, including the NSF CAREER award, the Okawa Foundation Award, 3 IBM Faculty Research Awards, Philips Make a Difference Award, 3 International ISO (International Organization for Standardization) Awards, the Oon International Prize and Lecture in Preventive Medicine for 2018 etc.

Wei Wang, PhD

Wei Wang, PhD

Leonard Kleinrock Professor in Computer Science, Director, Scalable Analytics Institute (ScAi)

Wei Wang is the Leonard Kleinrock Chair Professor in Computer Science and Computational Medicine at University of California, Los Angeles and the director of the Scalable Analytics Institute (ScAi). She is also a member of the UCLA Jonsson Comprehensive Cancer Center, Institute for Quantitative and Computational Biology, and Bioinformatics Interdepartmental Graduate Program. She received her PhD degree in Computer Science from the University of California, Los Angeles in 1999. She was a professor in Computer Science and a member of the Carolina Center for Genomic Sciences and Lineberger Comprehensive Cancer Center at the University of North Carolina at Chapel Hill from 2002 to 2012, and was a research staff member at the IBM T. J. Watson Research Center between 1999 and 2002. Dr. Wang’s research interests include big data analytics, data mining, database systems, natural language processing, bioinformatics and computational biology, and computational medicine. She has filed seven patents, and has published one monograph and more than two hundred research papers in international journals and major peer-reviewed conference proceedings.
Dr. Wang received the IBM Invention Achievement Awards in 2000 and 2001. She was the recipient of a UNC Junior Faculty Development Award in 2003 and an NSF Faculty Early Career Development (CAREER) Award in 2005. She was named a Microsoft Research New Faculty Fellow in 2005. She was honored with the 2007 Phillip and Ruth Hettleman Prize for Artistic and Scholarly Achievement at UNC. She was recognized with an IEEE ICDM Outstanding Service Award in 2012, an Okawa Foundation Research Award in 2013, and an ACM SIGKDD Service Award in 2016. Dr. Wang has been an associate editor of the IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Big Data, ACM Transactions on Knowledge Discovery in Data, Journal of Knowledge and Information Systems, Data Mining and Knowledge Discovery, Journal of Computational Biology, IEEE/ACM Transactions on Computational Biology and Bioinformatics, International Journal of Knowledge Discovery in Bioinformatics, and an editorial board member of the International Journal of Data Mining and Bioinformatics and the Open Artificial Intelligence Journal. She serves on the organization and program committees of international conferences including ACM SIGMOD, ACM SIGKDD, ACM BCB, VLDB, ICDE, EDBT, ACM CIKM, IEEE ICDM, SIAM DM, SSDBM, ISMB, RECOMB, BIBM. She was elected to the Board of Directors of the ACM Special Interest Group on Bioinformatics, Computational Biology, and Biomedical Informatics (SIGBio) in 2015.

Xiaoyan Wang, PhD

Xiaoyan Wang, PhD

Associate Professor, Division of General Internal Medicine and Health Services Research

Dr. Wang is an Associate Professor in the Department of Medicine Statistics Core (DOMStat). She has a strong interest in statistical methodological development and collaborative research. Her main research areas include biomarker discovery and validation, general area of survival analysis, high-throughput genomic data analysis. She is also heavily involved in numerous pre-clinical and early phase oncology clinical trials and has expertise in study design and clinical trial protocol development.

Karol Watson, MD, PhD

Karol Watson, MD, PhD

Professor, Department of Medicine in Cardiology

Dr. Karol Watson is an attending cardiologist and a Professor of Medicine/Cardiology at the David Geffen School of Medicine at UCLA. She is Director of the UCLA Women’s Cardiovascular Health Center, the UCLA-Barbra Streisand Women’s Heart Health Program, Co-Director of the UCLA Program in Preventive Cardiology, and Director of the UCLA Fellowship Program in Cardiovascular Diseases. Dr. Watson is a principal investigator for several large National Institutes of Health research studies including the Diabetes Prevention Program Outcomes Study and the Multi-ethnic Study of Atherosclerosis. She is a Fellow of the American College of Cardiology and a member of the American Heart Association. She is also a Board member of the American Heart Association, Western States Affiliate, and Chairperson of the Scientific Advisory Board for Womenheart, the largest national organization for women survivors of heart disease.

Jasmine Zhou, PhD

Jasmine Zhou, PhD

Professor, Pathology and Laboratory Medicine

Jasmine Zhou, PhD is a Professor of Pathology and Lab Medicine at UCLA. Her team
developed innovative methods for disease diagnostics, network biology, as well as novel
approaches to analyze multi-dimensional genomics data. For five years, her lab has been
focusing on early cancer detection using liquid biopsy. She served as the contact PI for the NIH
Knowledge Base and Coordination Center of the Mechanism-based Disease Connections, and
she is currently the contact PI of the NIH-funded UCLA Center for the Early Detection of Liver
Cancer. She has previously served as the Head of the Computational Biology and
Bioinformatics Program at University of Southern California. She was an associate editor of the
journal PLOS Computational Biology and BMC Genomics. She served the program committees
and organizing committees of many international conferences. She was a recipient of several
awards including an Alfred Sloan fellowship and a NSF Career award.

Samir Akre

Samir Akre

PhD Student

Samir is a first-year Ph.D. student in the medical informatics program at UCLA interested in translational medicine and entrepreneurship. He received a bachelor’s degree in biomedical engineering from UC Davis in 2018.

Ammy L. Cummings, MD

Ammy L. Cummings, MD

PhD Candidate

Amy L. Cummings is a PhD candidate in the UCLA Bioengineering Medical & Imaging Informatics Program and recently joined UCLA Hematology/Oncology faculty. Her research interests include artificial intelligence clinical decision support, translational oncology, and biomarker development in lung cancer. She received her bachelor of arts from UCLA and medical degree from the Keck School of Medicine at the University of Southern California where she graduated with honors and was elected to the Alpha Omega Alpha Honor Society. She completed both her internal medicine residency and hematology and oncology fellowship at UCLA and served as Chief Fellow for UCLA Hematology/Oncology as well as the David Geffen School of Medicine Specialty Training and Advanced Research (STAR) Program.

Joe Friedman

Joe Friedman

PhD Student

Joe Friedman is a PhD (Medical Informatics) and MD (Geffen School of Medicine) student. His past work has spanned the gamut from machine learning to ethnography, focusing on social determinants of health, reproductive justice, the North American opioid epidemic, and HIV. Prior to starting at UCLA, he completed a combined M.P.H and research fellowship program at the Institute for Health Metrics and Evaluation at the University of Washington, and his undergraduate training (B.A.) in Anthropology at the University of Vermont.

Joy (Mingzhou) Fu

Joy (Mingzhou) Fu

PhD Student

Joy (Mingzhou) Fu is a first-year medical informatics Ph.D. student. Her research interest lies in precision health, specifically integrating bioscience and clinical data to drive improvement of healthcare quality and equity. She received her MBBS degree in clinical medicine from Shanghai Jiao Tong University. Before starting at UCLA, she completed a combined MPH and MHI program at the University of Michigan.

David Gordon

David Gordon

PhD Student

David is a PhD student in the Medical Imaging & Informatics group. His current research involves probabilistic graphical models using electronic health record (EHR) and observational databases to support sequential decision making. He completed his MS in Department of Biomathematics at UCLA with research focus in statistical machine learning using medical imaging and EHR data. Prior, he completed a Fellowship in Clinical and Translational Science at UCLA School of Medicine with research focus in predictive modeling using clinical data.

Simon X. Han

Simon X. Han

PhD Student

Simon has worked on numerous projects in MII, such as observational databases for various cancer patients, system for assessing the concordance between radiology findings and pathology findings, and lung cancer disease modeling. Currently, Simon is investigating sequential decision making in a breast cancer screening context.

Jiayun Li

Jiayun Li

PhD Candidate

Jiayun’s research focuses on developing weakly- or semi-supervised models to learn deep representations from large-scale whole slide image datasets, and combine histopathological features, imaging representation and clinical variable for disease progression prediction. Jiayun has also worked as a data scientist intern at Ancestry for image caption generation during summer 2018, and a software engineering intern in machine learning at Google for hotel photo analysis during summer 2019.

Previously, Jiayun received a B.S. in Electrical Engineering at Fudan University in 2015. During that time, she worked as an undergraduate researcher on graphical models and their applications in Traditional Chinese Medicine at Adaptive Network and Control Lab

Yannan Lin

Yannan Lin

PhD Student

Yannan has clinical and public health background. Before starting her PhD program, she has worked as a student research assistant for several lung cancer projects in the Medical Imaging Inoformatics (MII) group.

Jennifer Polson

Jennifer Polson

PhD Student

Jennifer is a Ph.D. student in the Medical Imaging & Informatics Group under the mentorship of Dr. Corey Arnold. Her research focuses on applying deep learning techniques to medical images and using interpretability methods to gain insight into model behavior. Previously at UCLA, Jennifer received her BS in Biochemistry and an MS in Physiology, with her thesis focusing on statistical analysis of protein turnover in mouse models under cardiovascular stress.

Al Rahrooh

Al Rahrooh

PhD Student

Al Rahrooh is a Ph.D. student in the Medical Informatics Program at UCLA interested in the novel applications of artificial intelligence and computational modeling to create clinically useful diagnostic tools that personalize therapy. Prior to joining UCLA, Al graduated summa cum laude from the University of Central Florida with a B.S in Biomedicine and minor in Political Science. During his undergraduate education Al conducted research on the reduction and extraction of information from EEG motion artifact data through machine learning algorithms and statistical classification to predict walking speed. Al currently works as the Director of Innovation for LeNgineer, an engineering services and R&D company contracted by NASA, to develop and automate the next generation of human space flight systems along with the exploration of biotechnology ventures.

Karthik V. Sarma

Karthik V. Sarma

MD-PhD Student

Karthik is an MD-PhD student at the UCLA-Caltech Medical Scientist Training Program, currently pursuing his PhD in the UCLA Medical Imaging Informatics group.

Karthik‘s research focuses on the development of novel artificial intelligence techniques for medical applications. His thesis work seeks to assist radiologists and pathologists focusing on diagnosis, staging and treatment of prostate cancer by adapting modern computer vision approaches to the development of computerized clinical decision support systems (CDS). He is the recipient of an F30 fellowship from the National Institutes of Health and several other awards and grants. In addition to his work in prostate CDS, Karthik’s work also includes the evaluation of social media as a predictive tool for health status, the use of artificial intelligence for stroke prognosis estimation, and the development of patient portals for effectively sharing understandable medical information.

Karthik also serves as a member of the Board of Trustees of the American Medical Association, having been elected in 2016 and re-elected in 2017. Prior to joining the AMA-BOT, he was a member of the AMA House of Delegates for four years as part of the California delegation and served on the AMA Council on Medical Service. He also led the effort to create the AMA Medical Student Section Committee on Health Information Technology and served as its first chair. Currently he is the vice chair of the California Medical Association (CMA) Subcommittee on Health Information Technology, having previously served on the CMA Board of Trustees in 2014.

A native of Chicago, Karthik is an alumnus of the California Institute of Technology, where he received the degree of Bachelor of Science with honors in computer science.

Dylan Steinecke

Dylan Steinecke

PhD Student

Dylan Steinecke graduated cum laude from California State University San Marcos with a B.S. in Biological Sciences concentrated in Cellular & Molecular Biology with minors in Mathematics, Computer Science, and Economics. As an undergraduate, he worked tutoring math and science. He also gained research experience in the field of conservation genetics and molecular ecology at CSUSM and in a data science drug repurposing project at The Scripps Research Institute. Dylan is interested in precision and translational medical research in order to help those suffering from disease and hopes to do so during his time at UCLA and beyond.

Zichen Wang

Zichen Wang

PhD Student

BIOGRAPHY
Zichen is a PhD student in the Medical Image Informatics (MII) group.He is advised by Prof. Corey Arnold.
He is interested in machine learning analysis on biomedical images and deep learning with applications to healthcare. His current research topic focuses on semi-supervised learning approach for digital pathology.

Leihao Wei

Leihao Wei

PhD Student

Leihao Wei is a Ph.D. student working towards his Ph.D. degree in Electrical and Computer Engineering Department. He is interested in applying machine learning techniques to medical imaging methods for delivering insights to complex healthcare problems and improving patient care. Before joining MII, he was with Terahertz Electronics Laboratory at UCLA, where he worked on smart terahertz antennas for wireless communication systems.

Anil Yadav

Anil Yadav

PhD Student

Anil is a first-year Ph.D. student in the Medical Informatics group at UCLA. He did his undergraduate in Computer Science from Coppin State University (Baltimore, MD) and is interested in the CS applications (Big data, Deep learning) in the Medical Imaging domain. He is currently working under Dr. Hsu in the MII lab in various research projects relating to Lung cancer (processing, segmentation, detection, etc.)

Yu Yan

Yu Yan

PhD Student

Yu Yan received his B.S degree in biological science from Wuhan University. His research interest lies in designing and implementing quantitative and computational methods that solve problems in biology and medicine.

Davina Zamanzadeh

Davina Zamanzadeh

PhD Student

Davina Zamanzadeh is a PhD student in Computer Science whose focus is on machine learning with clinical applications.

Haoyue (Harry) Zhang

Haoyue (Harry) Zhang

PhD Student

I am PhD student in Medical & Imaging Informatics. I work on the applications of computer vision in medical imaging, advised by Dr Corey Arnold. Currently I focus on brain MRI imaging analysis using deep learning methods.

Tianran Zhang

Tianran Zhang

PhD Student

Tianran received her B.E. degree in optical information from Beijing Institute of Technology in 2015 and joined MII group as a doctorate student in bioengineering. She is interested in creating new methods for statistical disease modeling to combine clinical factors with imaging features and provide better clinical decision support.

David Zheng

David Zheng

PhD Student

David Zheng is a first-year medical informatics Ph.D. student who is interested in the applications of software and data science to medicine, particularly in the field of cancer research. He graduated with a degree in computer science from UCLA in 2020.

Henry Zheng

Henry Zheng

PhD Student

Henry Zheng is a first year PhD student in the medical informatics program at UCLA. He received a BS in biochemistry from Yale University in 2013 and studied at the University of Wisconsin School of Medicine and Public Health before coming to UCLA.

Isabel Rippy

Isabel Rippy

Senior Administrative Analyst

Isabel is the research and graduate program administrator for the Medical & Imaging Informatics group. She has a bachelor’s degree from UCLA and joined the UCLA Radiology department in 1994, and in 1998 transferred to the MII group. She assists in preparing annual budgets and oversees operations of all contracts, grants and other sources of intra/extramural funding for the group (annual budgets of $4M+). She completes IRB and data request/release forms. Maintains and submits annual corresponding progress reports for extramural funding to NIH and continued IRB approvals. She also acts as student affairs officer for Medical Informatics Home Area Graduate Program.