8:30 aM – 9:00 AM

Registration and continental breakfast

9:00 AM – 9:15 AM

Welcome & Opening Remarks

9:15 AM – 10:15 AM

Track I: AI in Medicine

Keynote – From Data to Diagnosis to Delivery: Artificial Intelligence in Precision Medicine

Atul Butte, MD, PhD
Director, Bakar Computational Health Sciences Institute, UCSF
Chief Data Scientist, University of California Health System

10:15 AM – 11:15 AM

Track I: AI in Medicine

Panel Discussion

TRACK LEAD

PANELISTS

Philip R.O. Payne, PhD
Director, Institute for Informatics, Data Science and Biostatistics (I2DB)
Janet and Bernard Becker Professor
Associate Dean for Health Information and Data Science, School of Medicine
Chief Data Scientist, School of Medicine
Digital Transformation Lead

Cristina Vazquez Guillamet, MD
Associate Professor of Medicine, Divisions of Infectious Diseases and Pulmonary and Critical Care Medicine 
Department of Internal Medicine, School of Medicine

Ning Zhang, PhD
Assistant Professor, Computer Security and Privacy Laboratory
Department of Computer Science and Engineering
McKelvey School of Engineering

Gregory J. Zipfel, MD
Chair, Department of Neurosurgery, School of Medicine
Ralph G. Dacey Distinguished Professor of Neurosurgery
Neurosurgeon-in-Chief, Barnes-Jewish Hospital

Michelle Oyen, PhD
Associate Professor, Biomedical Engineering
McKelvey School of Engineering

11:15 – 11:30 AM

Break

11:30 AM – 12:15 PM

Track II: AI & the Law

AI in Healthcare – from the Hype to the Reality

In this session, we will discuss the current state-of-the-art in applying AI and Machine Learning to health care challenges. AI has certainly been in the news with the advent of Large Language Models (LLMs) like ChatGPT, and the hype surrounding this poorly-understood technology has contributed to renewed interest in the potential applications and perils of artificial intelligence and machine learning. How can we reap the benefits of these technologies while ensuring ethical, fair application in an environment of emerging regulatory scrutiny?

Mark Pitts
RVP, Digital Solutions & Products
Centene Corporation

12:15 – 1 PM

Lunch

1 – 2 PM

Track II: AI & the Law

Panel Discussion

TRACK LEAD

Michal Grinstein-Weiss, PhD
Shanti K. Khinduka Distinguished Professor
Brown School

PANELISTS

Eunhye Ahn, PhD
Assistant Professor, Brown School

Patrick Fowler, PhD
Associate Professor, Brown School
Director, Doctoral Program in Public Health Sciences

Tyler Haupert, PhD
Assistant Professor of Urban Studies
NYU Shanghai

2 – 2:15 PM

Break

2:15 – 2:45 PM

Track III: Generative AI

Why Data Created by Generative AI May Solve Our Bias Woes… and Why It Might Not

Bradley Malin, PhD
Accenture Professor, Department of Biomedical Informatics
Vice Chair for Research Affairs, Department of Biomedical Informatics
Affiliated Faculty, Center for Biomedical Ethics & Society
Accenture Professor, Department of Biostatistics
Accenture Professor, Computer Science
Vanderbilt University

2:45 – 3:45 PM

Track III: Generative AI

Panel Discussion

TRACK LEAD

Jacob Montgomery, PhD
Professor of Political Science, College of Arts & Sciences
Chair of the Political Science Track for Division of Computational and Data Sciences
Director of TRIADS

PANELISTS

Christopher Lucas, PhD
Assistant Professor of Political Science, College of Arts & Sciences

Chenguang Wang, PhD
Assistant Professor, Computer Science & Engineering
McKelvey School of Engineering

Danielle Williams, PhD
Mellon Post-Doctoral Fellow in Modeling Interdisciplinary Inquiry
College of Arts & Sciences

3:45 – 4 PM

Closing remarks

Philip R.O. Payne, PhD
Director, Institute for Informatics, Data Science and Biostatistics (I2DB)
Janet and Bernard Becker Professor
Associate Dean for Health Information and Data Science, School of Medicine
Chief Data Scientist, School of Medicine
Digital Transformation Lead

4 – 5 PM

Reception

8:30 aM – 9:00 AM

Registration and continental breakfast

9:00 AM – 9:05 AM

Welcome

9:05 – 9:50 PM

Special Showcase

PANEL ORGANIZER

Thomas M. Maddox, MD, MSc
Vice President, Digital Products and Innovation, BJC HealthCare/Washington University School of Medicine
Professor of Medicine (Cardiology), Washington University School of Medicine
Trustee, American College of Cardiology

PANEL

Ali Kosydor
Director, Healthcare Innovation Lab

Sunny Lou, MD, PhD
Instructor in Anesthesiology Division of Cardiothoracic Anesthesiology
Division of Clinical and Translational Research
School of Medicine

Michele Thomas, MD, FAAFP
Physician, BJC Medical Group

9:50 – 10 am

Break

10 – 11 am

Distinguished Speaker: AI & Data Science in Medical Imaging of Cancer and COVID-19

Artificial Intelligence in medical imaging involves research in task-based discovery, predictive modeling, and robust clinical translation.  Quantitative radiomic analyses, an extension of computer-aided detection (CADe) and computer-aided diagnosis (CADx) methods, are yielding novel image-based tumor characteristics, i.e., signatures that may ultimately contribute to the design of patient-specific cancer diagnostics and treatments. Beyond human-engineered features, deep networks are being investigated in the diagnosis of disease on radiography, ultrasound, and MRI.  The method of extracting characteristic radiomic features of a region can be referred to as “virtual biopsies”.  Various AI methods are evolving as aids to radiologists as a second reader or a concurrent reader, or as a primary autonomous reader.  This presentation will discuss the development, validation, database needs, and ultimate future implementation of AI in the clinical radiology workflow including examples from cancer and COVID-19, including the creation and benefits of MIDRC (midrc.org).

Maryellen Giger, PhD
A.N. Pritzker Distinguished Service Professor of Radiology, Committee on Medical Physics, & the College
The University of Chicago

Sponsored by the Department of Biomedical Engineering, McKelvey School of Engineering

11 am – 12 pm

Showcase: Digital Solutions Studio

MODERATOR

Mary McKay, PhD, MSW
Vice Provost of Interdisciplinary Initiatives

PANEL ORGANIZER

Betsy Sinclair, PhD
Chair of Political Science
Professor of Political Science
College of Arts & Sciences

PANEL

Natee Viravan, MD

Albert M. Lai, PhD
Deputy Director, Institute for Informatics, Data Science and Biostatistics (I2DB)
Chief Research Information Officer, School of Medicine
Professor of Medicine, Division of General Medical Sciences
Professor of Computer Science and Engineering, School of Engineering and Applied Science
Deputy Faculty Lead, Digital Transformation

Andrew Reeves, PhD
Professor of Political Science
College of Arts & Sciences
Director of the Weidenbaum Center on the Economy, Government, and Public Policy

12 – 12:45 pm

Lunch

12:45 – 2:45 pm

Track IV: Intersection of AI & Human/Computer Interaction

Lightning Talks and Panel Discussion

TRACK LEAD

Ruopeng An, PhD
Associate Professor, Brown School

PANEL

Eunhye Ahn, PhD
Assistant Professor, Brown School

Chien-Ju Ho, PhD
Assistant Professor, McKelvey School of Engineering

Caitlin Kelleher, PhD
Associate Professor, Department of Computer Science and Engineering
McKelvey School of Engineering

Wouter Kool, PhD
Assistant Professor of Psychological & Brain Sciences, School of Medicine

2:45 – 3 pm

Break

3 – 4 pm

Ryan Durrie, JD
Associate Director for Policy
The Cordell Institute for Policy in Medicine & Law
Washington University in St. Louis

4 – 4:15 pm

Closing remarks

Gregory S. Hart, PhD
Chief Technology Officer
Washington University in St. Louis

Atul Butte, MD, PhD
Director, Bakar Computational Health Sciences Institute, UCSF
Chief Data Scientist, University of California Health System

Atul Butte, MD, PhD is the Priscilla Chan and Mark Zuckerberg Distinguished Professor and inaugural Director of the Bakar Computational Health Sciences Institute (bchsi.ucsf.edu) at the University of California, San Francisco (UCSF). Dr. Butte is also the Chief Data Scientist for the entire University of California Health System (health.universityofcalifornia.edu), the eighth largest by revenue in the United States, with 20 health professional schools, 6 medical schools, 6 academic health centers, 10 hospitals, and over 1000 care delivery sites.

Dr. Butte has been continually funded by NIH for 25 years, is an inventor on 24 patents, and has authored over 300 publications, with research repeatedly featured in the New York Times and Wall Street Journal. Dr. Butte has been elected into the American Association for the Advancement of Science (AAAS), American Institute for Medical and Biological Engineering (AIMBE), American College of Medical Informatics (ACMI), and National Academy of Medicine, and in 2013, he was recognized by the Obama Administration as a White House Champion of Change in Open Science for promoting science through publicly available data.

Dr. Butte is also a co-founder of three investor-backed data-driven companies: Personalis (IPO, 2019), providing medical genome sequencing services, Carmenta (acquired by Progenity, 2015), discovering diagnostics for pregnancy complications, and NuMedii, finding new uses for drugs through open molecular data. Dr. Butte trained in Computer Science at Brown University, worked as a software engineer at Apple and Microsoft, received his MD at Brown University, trained in Pediatrics and Pediatric Endocrinology at Children’s Hospital Boston, then received his PhD from Harvard Medical School and MIT.

Maryellen Giger, PhD
A.N. Pritzker Distinguished Service Professor of Radiology, Committee on Medical Physics, & the College
The University of Chicago

Sponsored by the Department of Biomedical Engineering, McKelvey School of Engineering

Maryellen L. Giger, PhD is the A.N. Pritzker Distinguished Service Professor of Radiology, Committee on Medical Physics, and the College at the University of Chicago. She is also the Vice-Chair of Radiology (Basic Science Research) and the immediate past Director of the CAMPEP-accredited Graduate Programs in Medical Physics/ Chair of the Committee on Medical Physics at the University.

For over 30 years, she has conducted research on computer-aided diagnosis, including computer vision, machine learning, and deep learning, in the areas of breast cancer, lung cancer, prostate cancer, lupus, and bone diseases, and now COVID-19. Over her career, she has served on various NIH, DOD, and other funding agencies’ study sections, and is now a member of the NIBIB Advisory Council of NIH.

She is a former president of the American Association of Physicists in Medicine and a former president of the SPIE (the International Society of Optics and Photonics) and is the inaugural Editor-in-Chief of the SPIE Journal of Medical Imaging. She is a member of the National Academy of Engineering (NAE) and was awarded the William D. Coolidge Gold Medal from the American Association of Physicists in Medicine, the highest award given by the AAPM. She is a Fellow of AAPM, AIMBE, SPIE, SBMR, IEEE, COS, and IAMBE, a recipient of the EMBS Academic Career Achievement Award, the SPIE Director’s Award, the SPIE Harrison H. Barrett Award in Medical Imaging, the RSNA Honored Educator Award, and the RSNA Outstanding Researcher Award, and was a Hagler Institute Fellow at Texas A&M University.

In 2013, Giger was named by the International Congress on Medical Physics (ICMP) as one of the 50 medical physicists with the most impact on the field in the last 50 years. In 2018, she received the iBIO iCON Innovator award. She has more than 260 peer-reviewed publications (over 450 publications), has more than 30 patents and has mentored over 100 graduate students, residents, medical students, and undergraduate students.

Her research in computational image-based analyses of breast cancer for risk assessment, diagnosis, prognosis, and response to therapy has yielded various translated components, and she is now using these image-based phenotypes, i.e., these “virtual biopsies” in imaging genomics association studies for discovery.She has now extended her AI in medical imaging research to include the analysis of COVID-19 on CT and chest radiographs, and is contact PI on the NIH NIBIB-funded Medical Imaging and Data Resource Center (MIDRC; midrc.org). She was a cofounder of Quantitative Insights, Inc., which started through the 2009-2010 New Venture Challenge at the University of Chicago. QI produced QuantX, which in 2017, became the first FDA-cleared, machine-learning-driven system to aid in cancer diagnosis (CADx). In 2019, QuantX was named one of TIME magazine’s inventions of the year, and was bought by Qlarity Imaging.

Chenyang Lu, PhD
Chenyang Lu is the Fullgraf Professor in the Department of Computer Science & Engineering at Washington University in St. Louis. His research interests include artificial intelligence (AI) for medicine, embedded and real-time systems, cyber-physical systems, and Internet of Things (IoT). The author and co-author of over 200 research papers with over 25,000 citations and an h-index over 70, Professor Lu is Editor-in-Chief of ACM Transactions on Cyber-Physical Systems. He also served as Editor-in-Chief of ACM Transactions on Sensor Networks, Chair of the IEEE Technical Community on Real-Time Systems (TCRTS), and Program/General Chair of leading conferences on Internet of Things (SenSys), real-time systems (RTSS/RTAS), and cyberphysical systems (ICCPS). He received the Outstanding Technical Achievement Award and Leadership Award from the IEEE Technical Community on Real-Time Systems in 2022. He has also been recognized by a Test of Time Award from ACM Conference on Embedded Networked Sensor Systems (SenSys), an Influential Paper Award from IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), and eight Best or Outstanding Paper Awards. He received a PhD from University of Virginia in 2001. He is a Fellow of ACM and IEEE.

Philip R.O. Payne, PhD
Dr. Payne is the founding Director of the Institute for Informatics, Data Science and Biostatistics (I2DB) at Washington University in St. Louis, where he also serves as a Professor in the Division of General Medical Sciences. Previously, Dr. Payne was Professor and Chair of the Department of Biomedical Informatics at The Ohio State University. Dr. Payne is an internationally recognized leader in the field of clinical research informatics (CRI) and translational bioinformatics (TBI). His research portfolio is actively supported by a combination of NCATS, NLM, and NCI grants and contracts, as well a variety of awards from both non-profit and philanthropic organizations. Dr. Payne received his Ph.D. with distinction in Biomedical Informatics from Columbia University, where his research focused on the use of knowledge engineering and human-computer interaction design principles in order to improve the efficiency of multi-site clinical and translational research programs. Prior to pursuing his graduate training, Dr. Payne served in a number of technical and leadership roles at both the UCSD Shiley Eye Center and UCSD Moores Cancer Center. Dr. Payne’s leadership in clinical research informatics community has been recognized through his appointment to numerous national steering, scientific, editorial, and advisory committees, including efforts associated with the American Medical Informatics Association (AMIA), AcademyHealth, the Association for Computing Machinery (ACM), the National Cancer Institute (NCI), the National Library of Medicine (NLM), and the CTSA consortium, as well as his engagement as a consultant to academic health centers throughout the United States and the Institute of Medicine. Dr. Payne is the author of over 190 publications focusing on the intersection of biomedical informatics and the clinical and translational science domains, including several seminal reports that have served to define a new sub-domain of biomedical informatics theory and practice specifically focusing upon clinical research applications.

Cristina Vazquez Guillamet, MD
Dr. Guillamet’s focus has been bringing new mathematical and statistical methods to the study of infections in critically ill patients. She has been interested in infections caused by multidrug resistant microbes, their epidemiology, treatment and impact. Her research aims at how to better predict and understand who’s at risk for developing an infection caused by multidrug resistant microbes. her current subjective approach has lead to both underrecognizing sepsis and also overtreating for MDR pathogens. More so, current prediction models have failed the external validation. Dr. Guillment strives to correct that and develop tools that classify patients at risk and that are easy to understand, apply and extrapolate.

Ning Zhang, PhD
Professor Zhang joined the Department of Computer Science & Engineering at Washington University in Fall 2018. Prior to that, he was a principal cyber engineer/researcher and technical lead at Cyber Security Innovations of Raytheon. Throughout his eleven-year career at Raytheon, he has worked to protect various critical networked and cyberphysical infrastructures. Professor Zhang’s research focus is system security, which lies at the intersection of security, computer architecture and programming language. He is particularly interested in secure software/hardware systems, side-channel analysis, malware and digital forensics. He is also interested in developing new methods to automatically discover and mitigate system vulnerabilities.

Gregory J. Zipfel, MD
Dr. Zipfel was recruited to Washington University in St. Louis in 2004. He was promoted to Associate Professor in 2011, Professor in 2015, and Chairman of the Department in 2019. In addition, he serves as Co-Director of the Stroke and Cerebrovascular Center at Barnes-Jewish Hospital / Washington University in St. Louis and is Director of the Neurological Surgery Residency Program. He is board certified in Neurological Surgery. Dr. Zipfel focuses his clinical practice on the surgical management of cerebrovascular disease and skull base tumors. He also directs the Cerebrovascular Research Program in the Department of Neurosurgery at Washington University. This program has three primary areas of interest: 1) Examining the impact of cerebral amyloid angiopathy and vascular oxidative stress on Alzheimer’s disease and other forms of dementia; 2) Exploring the molecular basis and developing novel therapeutics for subarachnoid hemorrhage-induced brain injury; and 3) Determining and classifying the pathophysiology, natural history, and treatment of dural arteriovenous fistulae. This research program has been continuously funded by the NIH since 2005 and has been supported by numerous other foundations including the American Heart Association, American Health Assistance Foundation, Brain Aneurysm Foundation, Neurosurgery Research & Education Foundation, Hope Center For Neurological Disorders, and McDonnell Center for Systems Neuroscience. His CV lists over 200 peer-reviewed publications – primarily in the areas of cerebrovascular neurosurgery, subarachnoid hemorrhage, and cerebral amyloid angiopathy.

Michelle Oyen, PhD
Prior to joining the faculty of Washington University in St. Louis in January, 2022, she was a member of the faculty at the Cambridge University Engineering Department in Cambridge, UK (2006-2018) and at East Carolina University (2018-2021). Michelle Oyen has a background in materials and biomechanics and has worked on many problems within tissue mechanics and biomimetic materials. For over twenty years, she has had an increasing interest in pregnancy and women’s health research, particularly in engineering approaches for prevention of and intervention into preterm birth.

Michal Grinstein-Weiss, PhD
Michal Grinstein-Weiss conducts research on improving health and socio-economic mobility for low-income households by creating scalable, evidence-based interventions to inform and shape policy, domestically and internationally. Grinstein-Weiss serves as director of the university-wide Social Policy Institute. As an influential voice in the design of innovative savings and asset-building policies, Grinstein-Weiss is pioneering the field of tax-time savings and spearheading Israel’s creation of a national child savings account program. Her work also merges behavioral science and managed healthcare toward the goal of creating evidence-based solutions for effective healthcare.  She has led successful research collaborations for top industry, government, and philanthropic partners, including Fortune 500 companies, major foundations, and government agencies. Her work has been featured in popular media such as National Public Radio and The Wall Street Journal and published in top-tier academic journals, including American Economic Journal, Social Service, Review, and Social Work Research.  She serves as a Nonresident Senior Fellow in Global Economy and Development at the Brookings Institution, has held leadership roles with the Clinton Global Initiative, and was recently identified as one of the highest-impact social work scholars by Research on Social Work Practice.

Eunhye Ahn, PhD
Eunhye Ahn’s research focuses on leveraging data to improve the outcomes of children and families and advance broader social goals of equity and justice. She is particularly interested in informing child welfare policy and practice by utilizing data science and promoting equitable child welfare outcomes through rigorous examination of racial and socioeconomic disparities. She integrates policy knowledge in child welfare with data science approaches with an emphasis on ethics and justice. To expand our understanding of applying data science to government, policy, and protection systems in the child welfare arena, she closely collaborates with practitioners and community partners. Her research seeks to lay the foundation for future research on aligning data science initiatives with child welfare practice and policy priorities. Some of her current projects explore the ethical use of data in child welfare to support human decision-making processes. This study also examines the biases and fairness of machine learning applied to child welfare.

Patrick Fowler, PhD
Patrick J. Fowler’s research aims to prevent homelessness and its deleterious effects on child, family, and community well-being. Trained in child clinical-community psychology, Fowler uses innovative methods that rigorously investigate policies and programs intended to promote housing and family stability. Recent research focuses on cross system collaborations to prevent child maltreatment associated with family homelessness, as well as youth homelessness in the transition from foster care to adulthood. Fowler also designs and tests big data applications that improve fair and efficient delivery of homeless services; the approaches leverage linked administrative data to target prevention for households most likely to benefit.  His work applies a complex systems perspective to inform developmentally and culturally tailored responses to homelessness. He collaborates with experts in the areas of prevention science, artificial intelligence, social system dynamics, as well as network and systems science. Fowler’s federally funded research has been supported by the National Institute of Child Health and Human Development, the U.S. Administration for Children and Families, and the U.. Department of Housing and Urban Development.  Fowler teaches courses in public health and social work focused on prevention science, program and systems evaluation, and developmental psychopathology.

Tyler Haupert, PhD
Tyler Haupert is an Assistant Professor of Urban Studies at NYU Shanghai. He also serves as a Faculty Affiliate at the NYU Furman Center, the Social Policy Institute at Washington University in St. Louis, and the Center for Applied Social and Economic Research (CASER) at NYU Shanghai. His research focuses on the technological, economic, and regulatory mechanisms contributing to racial disparities, segregation, and exclusion in urban areas. He has particular interests in mortgage lending, fintech, housing affordability, homelessness, and neighborhood change. He strives to design studies that inform policy and produce actionable results for legislators, regulators, planners, and advocacy organizations. Professor Haupert’s work has appeared in scholarly journals including Housing Policy Debate, Housing Studies, the Journal of Urban Affairs, Race and Social Problems, and Urban Studies. His work has been cited by or appeared in a number of media outlets including the New York Times, Slate, Governing, Next City, Planetizen, and Shelterforce. He has professional experience in the public education, affordable housing development, and research sectors.

Bradley Malin, PhD
Bradley Malin, Ph.D. is the Accenture Professor of Biomedical Informatics, Biostatistics, and Computer Science, as well as Vice Chair for Research Affairs in the Department of Biomedical Informatics. His research is funded through grants from the National Science Foundation (NSF), National Institutes of Health (NIH), and Patient Centered Outcomes Research Institute (PCORI). His research is on the development of technologies to enable artificial intelligence and machine learning (AI/ML) in the context of organizational, political, and health information architectures. He has made specific contributions in a number of areas, including distributed data processing methods for medical record linkage and predictive modeling, intelligent auditing technologies to protect electronic medical records from misuse in the context of primary care, and algorithms to formally anonymize patient information disseminated for secondary research purposes. His investigations on the empirical risks to health information re-identification have been cited by the Federal Trade Commission in the Federal Register and certain privacy enhancing technologies he developed have been featured in popular media outlets and blogs, including Nature News, Scientific American, and Wired magazine. He co-directs the Health Data Science (HEADS) Center, the Center for Genetic Privacy and Identity in Community Settings (GetPreCiSe) – an NIH Center of Excellence on Ethical, Legal, and Social Implications Research (CEER), the Ethics Core of the NIH Bridge2AI program, and the Infrastructure Core of the NIH Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD). In addition, he serves as the co-chair of the Committee on Access, Privacy, and Security (CAPS) of the All of Us Research Program of the U.S. Precision Medicine Initiative, an appointed member of the Technical Anonymisation Group of the European Medicines Agency, and an appointed member of the Board of Scientific Counselors of the National Center for Health Statistics of the Centers for Disease Control and Prevention (CDC). He is an elected fellow of the National Academy of Medicine (NAM), the American College of Medical Informatics (ACMI), the International Academy of Health Sciences Informatics (IAHSI), and the American Institute for Medical and Biological Engineering (AIMBE). In addition, he was honored as a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE) from the White House. Dr. Malin completed his education at Carnegie Mellon University, where he received a bachelor’s in biological sciences, a master’s in machine learning, a master’s in public policy and management, and a doctorate in computer science (with a focus on databases and software systems).

Jacob Montgomery, PhD
Professor Montgomery’s research focuses on how to use advanced computational methods for core social science tasks including measurement, theory testing, survey research, and causal inference. Substantively, his research focus is on American politics and social media. I am the Founding Director of the Transdisciplinary Research Institute in Applied Data Science (TRIADS) and Professor and Director of Data Science Training in the Department of Political Science at Washington University in St. Louis. I am also the chair of the political science track for the Division of Computational and Data Sciences. My research is in the areas of political methodology and American politics, with a special interest in measurement, Bayesian statistics/machine learning, and computational methods. My work has been published in many of the field’s leading journals—including the American Political Science Review, the American Journal of Political Science, Proceedings of the National Academy of Sciences, the Journal of Politics, and Political Analysis—and my work has received support from the National Science Foundation. In 2020, I was given the Emerging Scholar Award from The Society for Political Methodology, which honors a young researcher, within ten years of their degree, who is making notable contributions to the field.

Christopher Lucas, PhD
I am an Assistant Professor in the Department of Political Science and a faculty affiliate with the Division of Computational & Data Sciences at Washington University in St. Louis. I study methodology, political communication, and the media. My research is published or forthcoming in the American Political Science Review, the American Journal of Political Science, and the Journal of Politics, among other venues, and has received the Gosnell Prize for Excellence in Political Methodology twice. Ongoing work is supported by multiple grants from the National Science Foundation.

Chenguang Wang, PhD
Chenguang Wang joined Washington University in St. Louis in 2022. Before that, he was a postdoc in Computer Science at UC Berkeley. He was previously a research scientist at Amazon AI and a research staff member at IBM Research-Almaden. He was nominated for the 2016 ACM China Doctoral Dissertation Award and received honorable mention (one of the two national finalists). Chenguang Wang has broad interests in natural language processing and machine learning. His work focuses on fundamental NLP research including deep learning models, language models, structure prediction, knowledge graphs, language representation and generation, language and vision, responsible models (security, robustness, interpretability, fairness), neural symbolic models, code understanding and generation, as well as applications of NLP for science, biomedicine, math, economics, and blockchain. He has created several open-source deep learning systems, including AutoGluon and GluonNLP.

Danielle Williams, PhD
My name is Danielle, and I recently earned my Ph.D. in the department of philosophy at UC Davis in California. My research is primarily focused on the philosophy of science. Specifically cognitive science, neuroscience, and computation. I am currently a Mellon Postdoctoral Fellow in Modeling Interdisciplinary Inquiry at Washington University in St. Louis (WashU). I am a first-generation university student and the first to earn a BA and pursue a post-graduate degree. My educational journey has taken me through every stage of the California college system. I earned an AA and AS at Sacramento City College, a BA at California State University, Sacramento, and then a Ph.D. at the University of California, Davis.

Thomas M. Maddox, MD, MSc
Dr. Thomas Maddox is the inaugural Executive Director of the Healthcare Innovation Lab at BJC HealthCare and Washington University School of Medicine in St. Louis. He is also a practicing cardiologist, a professor of medicine (cardiology) at Washington University School of Medicine, and a health services researcher. The Innovation Lab catalyzes research and development in care delivery innovation to improve the health of patients and their communities. To date, the Lab has developed innovations in predictive analytics in inpatient care, critical care, and palliative care; remote patient monitoring in heart failure, post-operative, and post-partum patients; patient transportation for ambulatory and cancer patients; voice assistants in inpatient supply chain and pre-operative patients, and patient billing. Prior to his arrival at Washington University in 2017, Dr. Maddox served as the National Director for the Veterans Affairs (VA) Clinical Assessment, Reporting, and Tracking (CART) cardiac quality program, which oversaw care in all 78 VA cardiac catheterization laboratories. He was also a staff cardiologist at the Denver VA Medical Center, and an associate professor of medicine at the University of Colorado School of Medicine. Dr. Maddox earned his bachelor of arts in economics and history, cum laude, from Rice University; his medical degree from Emory University; and a master of science in epidemiology from the Harvard University School of Public Health. He trained in internal medicine at the University of Texas Southwestern Medical Center, and in cardiovascular medicine at the Mount Sinai Medical Center. He was also a fellow at the Kaiser Family Foundation and the National Academy of Medicine. Dr. Maddox’s research interests have focused on health care delivery innovation, learning health care systems, prevention in coronary artery disease, optimal care for cardiac patients undergoing non-cardiac surgery, and quality of care for cardiac patients. He has authored over 200 peer-reviewed publications, received multiple grants exploring optimal cardiac care and outcomes, and holds national leadership positions in the American College of Cardiology and the American Heart Association.

Ali Kosydor
Ali Kosydor, MHA, is the Director of the Healthcare Innovation Lab at BJC HealthCare & Washington University School of Medicine. In this role, Ali manages an innovation portfolio that supports the health system advance their strategic portfolio, research in emerging innovation trends in healthcare, and build a culture of innovation. Ali is an experienced healthcare leader with ability to navigate complex transformative initiatives in large, integrated delivery networks, taking novel concepts through discovery, design, and delivery of value outcomes. She is a pragmatic thinker who balances strategic decisions and financial discipline with a passion for driving innovative solutions and process in digital health, AI/ML, and personalized medicine to redesign clinical care models and improve the way care is delivered. Prior to joining the Innovation Lab, Ali spent over ten years in consulting and in clinical operations focusing on advancing clinical care models through performance improvement best practices. Ali earned her MHA from Webster University, graduating with honors. She earned her BS in health sciences from University of Missouri with a focus in healthcare administration and a minor in business.

Sunny Lou, MD, PhD
I’m an Instructor in the Divisions of Cardiothoracic Anesthesiology, Clinical and Translational Research (DoCTR), and Institute for Informatics (I2) at the Washington University School of Medicine in St Louis. My research is focused on the use of clinical informatics and data science to improve clinician workflow, efficiency, and the quality of clinical care.

Michele Thomas, MD, FAAFP
Michelle M. Miller-Thomas, MD, is vice chair for faculty development and a professor for Mallinckrodt Institute of Radiology (MIR) at Washington University School of Medicine in St. Louis. Miller-Thomas, who completed her fellowship in neuroradiology at MIR, oversees functional MRI, tractography, vessel wall imaging, PET/MRI and volumetric imaging for dementia. Her research interests include applying fMRI and tractrography to presurgical planning for brain tumors and epilepsy, and imaging the brain after brain tumor therapy. Miller-Thomas is the university’s director of medical student education in radiology and, in 2020, received the Loeb Teaching Fellowship from the School of Medicine. She is an active member of several organizations, including the Radiological Society of North America, the American Society of Neuroradiology, and the American Board of Radiology, where she serves as questions writing committee chair for the neuroradiology certifying and subspecialty exam. Miller-Thomas completed a residency in diagnostic radiology at the University of Texas Health Science Center, and she earned her medical degree from St. Louis University and her bachelor’s degree from California Institute of Technology in Pasadena.

Mary McKay, PhD
Mary M. McKay joined the Brown School at Washington University in St. Louis as dean in 2016, continuing the School’s legacy of creating vital knowledge, initiating social change, and preparing leaders to address social and health challenges both locally and globally. Dean McKay’s academic experience connects deeply to both social work and public health. She has received substantial federal funding for research focused on meeting the mental health and health prevention needs of youth and families impacted by poverty. She also has significant expertise in child mental health services and implementation research methods, as well as over 20 years of experience conducting HIV prevention and care-oriented studies, supported by the National Institutes of Health. She has authored more than 150 publications on mental and behavioral health, HIV/AIDS prevention and urban poverty, and more. Prior to joining the Brown School, Dean McKay was the McSilver Professor of Social Work and the inaugural director of the McSilver Institute for Poverty Policy and Research at New York University’s Silver School of Social Work. She previously served as the head of the Division of Mental Health Services Research at Mount Sinai School of Medicine. Her prior academic appointments include Columbia University and University of Illinois at Chicago.

Betsy Sinclair, PhD
I am a Professor of Political Science at Washington University in St Louis. My research interests are located in American politics and political methodology with an emphasis on individual political behavior. I focus on the social foundations of participatory democracy — the ways in which social networks influence voting, donating, choosing a candidate or identifying with a particular party. My other interests are broadly defined as those involving voting and elections and range from evaluating the consequences of different voting technologies to developing techniques to draw causal inferences from social network data.

Todd Braver, PhD
Professor Braver’s laboratory studies how humans exert control over their thoughts and behavior, and how this control can break down. His work focuses on the cognitive and neural mechanisms underlying memory, attention, and controlled processing. Professor Braver studies the cognitive and neural mechanisms underlying memory, attention, and controlled processing. His research approach combines computational modeling (using connectionist framework), functional neuroimaging (using fMRI and PET methods), and behavioral studies (in normal and clinical populations, and under pharmacological challenge). Ongoing projects include testing model predictions regarding (1) how the prefrontal cortex represents and maintains information in working memory; and (2) how the dopamine neurotransmitter system regulates control over these processes.

Albert M. Lai, PhD
Albert M. Lai, PhD, is the Chief Research Information Officer (CRIO) for the Washington University School of Medicine and is a Professor of Medicine in the Division of General Medical Sciences. In his role as CRIO, he oversees the Informatics Core Services group, which serves as the informatics services arm for the Institute for Informatics. Dr. Lai specializes in the development of research informatics infrastructure and is well recognized in the fields of clinical research informatics and consumer health informatics. His recent research has focused on the application of natural language processing, temporal reasoning and information fusion to generate a longitudinal computable phenotype to support clinical trial prescreening. He has additional research interests in telemedicine, mobile health, data sharing networks, and usability of provider and patient-facing systems.

Andrew Reeves, PhD
Andrew Reeves is the director of the Weidenbaum Center on the Economy, Government, and Public Policy and professor of political science at Washington University in St. Louis. He is also an affiliated faculty member in the Division of Computational and Data Sciences and the Center for the Study of Race, Ethnicity & Equity and an associate of the Taylor Geospatial Institute. He has held research fellowships at the Hoover Institution at Stanford University and at the Center for the Study of American Politics within the Institution for Social and Policy Studies at Yale University. He studies elections, public opinion, and executive politics. His research examines the interchange between institutions and behavior with a focus on political accountability and public policy in the United States. His work has appeared in the American Political Science Review, the American Journal of Political Science, and the Journal of Politics, among other outlets. His most recent book, No Blank Check: The Origins and Consequences of Public Antipathy towards Presidential Power with Jon C. Rogowski was published in 2022 with Cambridge University Press ( Amazon | CUP). His first book, The Particularistic President: Executive Branch Politics and Political Inequality with Douglas Kriner is the winner of the 2016 Richard E. Neustadt Award ( Amazon | CUP).

Ruopeng An, PhD
Ruopeng An conducts research to assess population-level policies, local food and built environment, and socioeconomic determinants that affect individuals’ dietary behavior, physical activity, sedentary lifestyle, and adiposity in children, adults of all ages, and people with disabilities. His research aims to develop a well-rounded knowledge base and policy recommendations that can inform decision-making and the allocation of resources to combat obesity. An’s research has been funded by federal agencies and public/private organizations (e.g., OpenAI, Abbott, Amgen). He has wide teaching and methodological expertise, including applied artificial intelligence (machine and deep learning), quantitative policy analysis (causal inference, cost-benefit and cost-effectiveness analysis, and microsimulation), applied econometrics and regression analysis, and systematic review and meta-analysis. He founded and chairs the Artificial Intelligence and Big Data Analytics for Public Health (AIBDA) Certificate program and hosts the “Artificial Intelligence in the Social Sciences” Open Classroom series. He has repeatedly been recognized for teaching excellence, receiving student evaluations in the top 10% of University faculty. With over 200 peer-reviewed journal publications, Dr. An is recognized as one of Elsevier’s top 2% most cited scientists. His work has been highlighted by media outlets such as TIME, New York Times, Los Angeles Times, Washington Post, Reuters, USA Today, Bloomberg, Forbes, Atlantic, Guardian, FOX, NPR, and CNN. He serves on research grants and expert panels for NIH, CDC, NSF, HHS, USDA, and the French National Research Agency. He is a Fellow of the American College of Epidemiology.

Eunhye Ahn, PhD|
Dr. Eunhye Ahn is an Assistant Professor at the Brown School whose research aims to harness data science to benefit vulnerable children and families. Her work informs child welfare policy and practice by developing data-driven methods to enhance human decision-making. She is particularly interested in leveraging predictive analytics and AI to provide insights that improve outcomes for children involved in child protective services.

Chien-Ju Ho, PhD
Chien-Ju is an assistant professor in Computer Science & Engineering at Washington University in St. Louis, holding a Ph.D. in Computer Science from UCLA. He previously worked as a postdoctoral associate at Cornell and spent three years of his PhD at Harvard’s EconCS group. He received the Google Outstanding Graduate Research Award in 2015 and had work nominated for Best Paper Awards in 2015 and 2021. His research focuses on the interactions between humans and AI, including designing AI that learns from humans and assists human decision-making, drawing techniques from machine learning, optimization, behavioral sciences, and algorithmic economics.

Caitlin Kelleher, PhD
Professor Kelleher joined the faculty at Washington University in St. Louis in 2007. She is the recipient of an NSF Career award and was named a 2013 Sloan Foundation Fellow. Her work has won several best paper awards at top conferences. Caitlin Kelleher is a researcher in Human-Computer Interaction and focuses on designing new kinds of programming environments and languages that democratize programming. Recently, her research group has focused on supporting children learning to program independently. This research has resulted in new kinds of support for tutorials, code execution history exploration tools, and robust support for reusing code from unfamiliar programs. Additionally, her group has explored how to support learning from code puzzles and the kinds of learning decisions young novices make in open ended contexts.

Caitlin Kelleher, PhD
Professor Kelleher joined the faculty at Washington University in St. Louis in 2007. She is the recipient of an NSF Career award and was named a 2013 Sloan Foundation Fellow. Her work has won several best paper awards at top conferences. Caitlin Kelleher is a researcher in Human-Computer Interaction and focuses on designing new kinds of programming environments and languages that democratize programming. Recently, her research group has focused on supporting children learning to program independently. This research has resulted in new kinds of support for tutorials, code execution history exploration tools, and robust support for reusing code from unfamiliar programs. Additionally, her group has explored how to support learning from code puzzles and the kinds of learning decisions young novices make in open ended contexts.

Wouter Kool, PhD
Wouter Kool is an assistant professor in the Department of Psychological & Brain Sciences here at WashU. He obtained his Ph.D. from Princeton University, and did his postdoctoral research at Harvard University before coming to St. Louis. The research in his lab aims to understand how people make decisions, how they control information processing, and how they make decisions about how to control information processing. Recently, he has become interested in understanding how human behavior changes when people interact with AI algorithms. 

• Philip R.O. Payne – Digital Transformation Implementation Chair
• Ruopeng An, Brown School at Washington University – Track Lead for Intersection of AI and Human-Computer Interaction
• Michal Grinstein Weiss, Brown School at Washington University – Track Lead for AI and the Law
• Chenyang Lu, McKelvey School of Engineering – Track Lead for AI in Medicine
• Jacob Montgomery, College of Arts and Sciences – Track Lead for Generative AI
• Chandler Ahrens, Sam Fox School of Design & Visual Arts
• Matthew Allen, Sam Fox School of Design & Visual Arts
• Patrick Fowler, Brown School at Washington University
• Jonathan Hanahan, Sam Fox School of Design & Visual Arts
• Pauline Kim, Washington University School of Law
• Sharvari Mhatre, Sam Fox School of Design & Visual Arts
• Keith Schnakenberg, College of Arts and Sciences
• Constance Vale, Sam Fox School of Design & Visual Arts
• Yevgeniy Vorobeychik (Eugene), McKelvey School of Engineering
• Dennis Zhang, Olin Business School

Learn more about Digital Transformation at WashU.