Datapalooza 2022 Speakers and Presenters
Rafael Alvarado
Associate Professor of Data Science, UVA
Rafael Alvarado is the Program Director of the M.S. in Data Science and an Associate Professor at the School of Data Science. His areas of research include digital humanities, text analytics, and the anthropology of information. A digital humanist, Alvarado has a background in anthropology. He became interested in data science when he realized he could combine his interests in human culture and quantitative methods. Prior to coming back to UVA, Alvarado worked at Princeton University as a Coordinator of Humanities and Social Sciences Computing. There, he worked on several projects, including the Charrette Project, which digitized an Old French manuscript of an Arthurian legend, Chrétien de Troyes’ Knight of the Cart, which tells the story of Lancelot. At the School of Data Science, Alvarado teaches courses on Exploratory Text Analytics and the Practice and Application of Data Science. He emphasizes the importance of ethics in data science to his students as they look to the future of data science.
Stephen Baek
Associate Professor of Data Science, UVA
Baek is an applied geometer, scientist, and entrepreneur. He studies the space of shapes using machine learning. Baek’s educational background is in mechanical and aerospace engineering. Prior to joining UVA in 2021, he was an Assistant Professor at the University of Iowa, where he taught courses on deep learning. There, he also founded and directed the Visual Intelligence Laboratory, which conducts fundamental research in computational geometry, vision, and machine learning. Baek’s research interests include geometric data analysis, geometric deep learning, scientific machine learning, and data-driven design. Baek’s published research is extensive, including “Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials” and “Deep segmentation networks predict survival of non-small cell lung cancer.” Stephen Baek is a data scientist who is interested in shapes. At the intersection of (computational) differential geometry and data science, Baek develops mathematical foundations and algorithms to quantify trends and patterns across geometric objects. His past and current research span a wide variety of interdisciplinary subjects, including applied mechanics and materials science, biological shape analysis, digital human modeling, etc. He has been leading more than $15M of research projects sponsored by NSF, NIH, NASA, Air Force, Army, DOT, Hyundai Motors, and others. Baek received his PhD in Mechanical and Aerospace Engineering from Seoul National University, Korea, for an award-winning study on the statistical modeling of human body shapes on Riemannian manifolds. He was a recipient of the National Science and Engineering Scholarship and was a Presidential Postdoc Fellow of the President of Korea. After spending 6 years as an Assistant Professor at the University of Iowa, he joined the University of Virginia in 2021, where he currently holds an appointment as an Associate Professor of Data Science (primary) and Mechanical and Aerospace Engineering (courtesy).
William Basener
Professor of Data Science, UVA
Bill Basener is a Professor at the School of Data Science with a joint appointment in the Department of Systems and Information Engineering. He has authored research publications in machine learning, signal processing, image processing, dynamical systems, game theory, ecological economics, evolutionary genetics, and other applied mathematical fields, as well as a textbook on applied topology and multiple patents. The methods and software he developed for processing images in hyperspectral imaging have become the gold-standard in the field, used for processing millions of images by dozens of organizations. The Basener-Ross model he developed for modeling ecological collapse has been used for studying ancient civilizations. His textbook, Topology and Its Applications, was one of the first textbooks in the field of applied topology, and covered diverse applications in cosmology, chaos theory, condensed matter physics, protein folding, computer graphics, and robot coordination. He invented the topological anomaly detection, gradient flow clustering, hierarchical material identification, and object-based identification algorithms in image processing. This technology has been used in disaster relief efforts across the world.
Phil Bourne
Dean, School of Data Science, UVA
Philip E. Bourne is the founding dean of the School of Data Science, the newest and 12th school to be formed in the University’s 200-year history. He is a world-renowned biomedical and data science researcher who has published over 350 papers and five books, launched four companies, received numerous awards, and been elected as a fellow to multiple scientific societies. He was the first associate vice chancellor for innovation and industrial alliances at the University of California San Diego and the first associate director for data science at the National Institutes of Health. As dean of the School of Data Science, Bourne is leading an effort to create a new kind of school — a school “without walls,” defined by interdisciplinary collaboration and open scholarship. The School is guided by common goals: to further discovery, share knowledge and make a positive impact on society through collaborative, open and responsible data science research and education. Founded in 2019 through a $120M gift, the largest in UVA history, the School is positioned to play an integral leadership role in the global digital future. The School joins other departments across UVA, the community, industry, government and non-profit organizations to use data science to advance cutting-edge research and support the common good.
Renée Cummings
Assistant Professor of Data Science, UVA
Renée Cummings joined the School of Data Science in 2020 as the School’s first Data Activist in Residence and become an Assistant Professor of Data Science in 2022. She is a criminologist, criminal psychologist, artificial intelligence ethicist, therapeutic jurisprudence specialist, and urban technologist. Her areas of research interests include artificial intelligence, political science, and criminology. She studies the impact of artificial intelligence on criminal justice, specifically in communities of color and incarcerated populations. In her work as a Criminologist, Cummings founded Criminal Justice Intelligence Inc., which works with governments in the Caribbean to strengthen crime prevention, incorporate new technologies in existing crime prevention strategies, and develop behavior and hardware strategies that interlink to reduce vulnerabilities and tailor more proactive approaches to crime control and crime reduction. Cummings also founded Urban AI and is an East Coast Regional Leader for Women in AI Ethics. In her time in New York City, Cummings brought her expertise to train police officers and law enforcement agents to decrease homicides and gun and gang violence.
MC Forelle
Assistant Professor in Engineering & Society, UVA
MC Forelle is an assistant professor in Engineering & Society at the School of Engineering and Applied Science at the University of Virginia. Their work broadly examines the intersection of law, technology, and culture, with particular interests in materiality, sustainability, and practices of resistance and change. They received their PhD in Communication from the University of Southern California’s Annenberg School for Communication and Journalism, where their dissertation examined how copyright presents a legal challenge to car owners and mechanics attempting to do their own repairs, and how those communities have responded to that challenge. After graduating, they accepted a Cornell Presidential Postdoctoral Research Fellowship, and was the first fellow to be based at Cornell Tech in New York City. There, they expanded on their dissertation to study the technological challenges faced by users, tinkerers, and repair communities working to repair, maintain, and modify software-enabled automotive technologies, and the various legal avenues they are pursuing to resist corporate control over their devices.
Miriam Friedel
Senior Director, Machine Learning Engineering, Capital One
Miriam Friedel is a Senior Director of ML Engineering at the Capital One Center for Machine Learning, where she leads a team of engineers and data scientists building tools and solutions to solve ML problems across the enterprise. Prior to Capital One, she was Head of Data Science at Skafos, an eCommerce start-up based in Charlottesville, VA. She has spent over fifteen years in scientific and technical fields spanning theoretical physics, software engineering, transportation, neuroscience, management consulting, and machine learning. Miriam received her ScB in Physics from Brown University and her PhD in Physics from the University of California, Santa Barbara and is a co-author on more than fifteen peer-reviewed articles.
Alexander J. Gates
Assistant Professor of Data Science, UVA
lex Gates is a computational social scientist with an avid curiosity for understanding how connectivity shapes human behavior. Prior to joining the University of Virginia School of Data Science as an Assistant Professor in 2022, he was an Associate Research Scientist in Northeastern University’s Network Science Institute and the Department of Sociology. His work has been featured in top journals, including Nature, The Proceedings of the National Academy of Sciences, and The Journal of Machine Learning. Gates also embraces multi-modal communication channels, including award-winning data visualizations, journal covers, interactive web-based models, and videos. Examples of his work include exploring the interdisciplinary structure of a major scientific journal and a video on the collaboration network emerging from one of the NSF's largest gender equity efforts.
Douglas C. Hague
Executive Director, School of Data Science, UNC-Charlotte
Dr. Douglas Hague is the founding Executive Director of the School of Data Science at UNC Charlotte. He comes with deep industry experience in financial services, telecommunications, and aerospace and is currently a member of the State of North Carolina’s Innovation Council, a regulatory sandbox. Dr. Hague’s research interests are split between sports analytics and methods for managing the bias and fairness of data science models. Prior to joining the university, Dr. Hague was Chief Analytics Officer for Bank of America's Merchant Services. He also chaired for UNC Charlotte's industry advisory board for the Data Science Initiative. Dr. Hague earned a bachelor’s degree in Engineering Physics from the University of Tulsa, a master’s degree in System Design and Management from MIT, and a master’s degree and Ph.D. in Materials Science and Engineering from Penn State University.
Teague Henry
Assistant Professor of Psychology and Data Science, UVA
Teague Henry holds a dual appointment in the School of Data Science and in the Department of Psychology. His research focuses on developing new statistical techniques for modeling network and dynamical systems data, with applications to personalized medicine, neuroimaging and predictive modeling. Prior to his work in higher education, Teague worked as a Statistician for the 3-C Institute for Social Development, where he analyzed data and consulted for the company. After earning his PH.D. in Psychometrics and Quantitative Psychology, Henry worked as a Postdoctoral Researcher at the University of North Carolina, Chapel Hill, followed by a position as a Postdoctoral Scholar at the University of Pittsburgh. In addition to his main focus on statistical methods for network data, he is also interested in better understanding the neural correlates of neurodevelopmental disorders and how to design personalized interventions for psychological disorders.
Brant Horio
Fellow, Applied Research & Partnerships, LMI
Brant M. Horio is a Fellow with LMI, leading their Applied Research & Partnerships practice. Supporting basic research and partnerships with academia and industry, his practice is focused on helping advance innovation at LMI. Prior to this role, he served as Director of Data Science at LMI. He holds a Master’s degree in Operations Research from George Mason University and a Bachelor of Science degree in Industrial and Systems Engineering from Virginia Tech. His experience is focused in the application of data science, modeling and simulation, operations research, and complexity science. He has applied these methods over a wide range of projects across federal government and the commercial sector, including defense and national security, aviation, healthcare system dynamics and policy, and transportation networks.
H.V. "Jag" Jagadish
Director, Michigan Institute for Data Science, University of Michigan
H. V. Jagadish is Edgar F Codd Distinguished University Professor and Bernard A Galler Collegiate Professor of Electrical Engineering and Computer Science at the University of Michigan in Ann Arbor, and Director of the Michigan Institute for Data Science. Prior to 1999, he was Head of the Database Research Department at AT&T Labs, Florham Park, NJ. Professor Jagadish is well known for his broad-ranging research on information management, and has approximately 200 major papers and 37 patents, with an H-index of 94. He is a fellow of the ACM, "The First Society in Computing," (since 2003) and of AAAS (since 2018). He currently chairs the board of the Academic Data Science Alliance and previously served on the board of the Computing Research Association (2009-2018). He has been an Associate Editor for the ACM Transactions on Database Systems (1992-1995), Program Chair of the ACM SIGMOD annual conference (1996), Program Chair of the ISMB conference (2005), a trustee of the VLDB (Very Large DataBase) foundation (2004-2009), Founding Editor-in-Chief of the Proceedings of the VLDB Endowment (2008-2014), and Program Chair of the VLDB Conference (2014). Since 2016, he is Editor of the Morgan & Claypool “Synthesis” Lecture Series on Data Management. Among his many awards, he won the David E Liddle Research Excellence Award (at the University of Michigan) in 2008, the ACM SIGMOD Contributions Award in 2013, and the Distinguished Faculty Achievement Award (at the University of Michigan) in 2019. His popular MOOC on Data Science Ethics is available on EdX, Coursera, and Futurelearn.
Natalie Kupperman
Assistant Professor of Data Science, UVA
Kupperman is an applied sports science researcher and certified athletic trainer. She studies the use of biometrics, wearables, and other athlete monitoring methods to reduce injury risk and optimize athletic performance. Prior to joining the School of Data Science faculty in 2022, Kupperman was a Ph.D. student in the Department of Kinesiology at the University of Virginia where she did research in the Exercise and Sport Injury Lab and athletics with the men’s basketball team and women’s volleyball team. Before her doctoral studies, she spent seven years at Northwestern University working clinically as an athletic trainer in Athletics and the University Health Service. In combination with teaching, Kupperman’s research interests include data infrastructure and pipelines for collaboration in athlete monitoring, dynamic models of injury risk and athlete readiness, and creating seamless monitoring environments for sports teams. A few of her research papers include, “Global positioning system–derived workload metrics and injury risk in team-based field sports: A systematic review” and “Quantification of workload and wellness measures in a women’s collegiate volleyball season.”
Reggie Leonard
Associate Director for Career Connections and Community Engagement, School of Data Science, UVA
Reggie Leonard is in career development at the UVA School of Data Science, where he advises MSDS students, and builds relationships with people and organizations who can support their career development. Reggie has been with the school since it was an institute, in 2015, and has been in career development for 12+ years. Outside of work, Reggie enjoys hosting dinner parties, immersing himself in the business-side of tech, and studying wine.
Sheng Li
Assistant Professor of Data Science, UVA
Sheng Li is an Assistant Professor of Data Science at the University of Virginia (UVA). Prior to joining UVA, he was an Assistant Professor of Computer Science at the University of Georgia from 2018 to 2022, and a Data Scientist at Adobe Research from 2017 to 2018. He received his PhD degree in Computer Engineering from Northeastern University in 2017. His recent research interests include trustworthy representation learning, graph neural networks, visual intelligence, and causal inference. He has published over 120 papers, and has received over 10 research awards, such as the INNS Aharon Katzir Young Investigator Award, Fred C. Davidson Early Career Scholar Award, Adobe Data Science Research Award, Cisco Faculty Research Award, and SDM Best Paper Award. He has served as Associate Editor for seven international journals such as IEEE Trans. Neural Networks and Learning Systems and IEEE Trans. Circuits and Systems for Video Technology, and has served as an Area Chair for NeurIPS and ICLR.
Kelsey McDonald
Director, Ticket Analytics, Brooklyn Nets, BSE Global
Kelsey McDonald is currently the Director of Ticket Analytics for the Brooklyn Nets at BSE Global, where she also supports other Barclays Center events like New York Liberty games. Kelsey’s team is primarily responsible for making dynamic pricing decisions, forecasting demand, building retention models, and creating Tableau reports as a source of truth for all ticketing data in the organization. Prior to this, Kelsey worked at the NBA corporate office on the Stats team where she was a Project Manager focused on finding ways to share their advanced player stats with fans across the world. Kelsey got her start in sports analytics up in Boston working as a Data Scientist with the Kraft Analytics Group (KAGR) after receiving an MS in Business Analytics from Duke. For undergrad, Kelsey studied Finance and Economics at Longwood University where she also played soccer against UVA most seasons!
Cathy O'Neil
Data skeptic and New York Times bestselling author Cathy O’Neil is a thought leader exploring the realities and dangers of social networking, the consequences of algorithm design, and defending human dignity in the context of predatory capitalism. A prolific voice in academia and the private sector, O’Neil is the New York Times bestselling author of Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, which was a semifinalist for the National Book Award. She is also a columnist for Bloomberg Opinion, a renowned blogger, and her expertise was featured in the critically acclaimed documentary The Social Dilemma. O’Neill is the Founder of ORCAA, a consultancy providing algorithmic auditing services focused on safety, fairness, and principled use of data, and launched the Lede Program in Data Journalism at Columbia University. Her latest book, The Shame Machine: Who Profits in the New Age of Humiliation, investigates how shame functions as a tool across sectors including government, the healthcare system, and the wellness industry. With a mathematics Ph.D. and background in finance and AdTech startups, O’Neil offers unparalleled insight and analysis about the challenges that lie ahead for individuals and businesses in our increasingly algorithmic world.
Alvitta Ottley
Assistant Professor of Computer Science and Engineering, Washington University in St. Louis
Alvitta Ottley is an Assistant Professor in the Department of Computer Science & Engineering at Washington University in St. Louis. Ottley's current research interests include information visualization, human-computer interaction and visual analytics. Previously funded by NSF and U.S. Army, her research pursues areas such as learning and modeling user behavior, individual differences, and personalized health risk communication. Her work has been published in leading conferences and journals such as CHI, InfoVis, VAST and TVCG.
Micaela Parker
Executive Director, Academic Data Science Alliance
Micaela Parker is the Founder and Executive Director of the Academic Data Science Alliance (ADSA). ADSA is a community network for academic data science leaders, practitioners, and educators. We support new forms of community-driven resource building and sharing of approaches for the thoughtful integration of data science best practices in higher education. Before launching ADSA, Micaela worked for the Moore-Sloan Data Science Environments and was an Executive Director for the University of Washington’s eScience Institute. At eScience, she developed research and training programs, and participated in strategic planning and fiscal oversight. Based on her years of experience, Micaela now offers consulting for emerging data science initiatives in academia. Prior to her entry into data science, Micaela was a research scientist for 10 years in the University of Washington's School of Oceanography, where she also earned her PhD. She managed the Center for Human Health and Ocean Studies and was involved in many large, interdisciplinary projects bridging oceanography and genomics. She holds the title of eScience Data Science Fellow and she is a Research Scholar with the Ronin Institute for Independent Scholarship.
Paul B. Perrin
Professor of Data Science and Psychology, UVA
Paul Perrin is a Professor of Data Science and Psychology at UVA. He believes that disparities in the context of disability and health are one of the most shocking and inhumane forms of oppression and that the academic and medical communities have a central role to play in their alleviation. A combination of data science, modern analytic techniques, and community-based participatory research approaches are key tools for identifying the sources of—and potential solutions to—these disparities. With this aim, his research area of “social justice in disability and health” encompasses three facets: (a) cultural, familial, and international approaches to disability rehabilitation and adjustment, particularly in medically underserved and minority populations with neurological conditions; (b) social determinants of health (e.g., stigma, access to integrated care and telehealth, personal and collective strengths); and (c) social justice approaches to understand and dismantle oppression. Perrin is a psychologist by training and holds a joint appointment with the University of Virginia's Department of Psychology. He also serves as Co-Director of the Polytrauma Rehabilitation Center Traumatic Brain Injury Model Systems Program at the Central Virginia Veterans Affairs Health Care System and is an incoming editor of Rehabilitation Psychology. He is passionate about mentoring students in data science, psychology, and allied fields to become agents of social change in their personal and professional lives with an emphasis on disability and health. He teaches courses in multivariate statistics, research methodology, health disparities, health psychology, multicultural psychology, and community intervention.
Sally Pusede
Assistant Professor of Environmental Sciences, UVA
Sally Pusede is an Assistant Professor of Environmental Sciences at UVA. She is the recipient of the prestigious 2021 NSF CAREER Award. The award supports Pusede who will conduct field work in Dakar, Senegal, which will lead to the training of U.S. and Senegalese students in an international collaboration of physical and social scientists that will involve collecting and integrating scientific data and demographic information from a wide range of sources to shed light on inequalities in pollutant exposure and their consequences. Pusede is an atmospheric chemist with broad interests in air quality, climate, and atmosphere-biosphere interactions. Her research group makes measurements at the Earth’s surface and from onboard aircraft in diverse locations, including polluted cities, agricultural areas, and within forest canopies. Their focus is on the role of reactive nitrogen in chemical oxidation mechanisms and emissions of the greenhouse gas nitrous oxide. They utilize spatial and temporal variability in our datasets to derive mechanistic insight into processes taking place in urban and human-influenced environments. The group works to find solutions to atmospheric problems that adversely affect human health and ecosystems.
Sara Riggs
Associate Professor of Systems Engineering, UVA
Sara Riggs is an Associate Professor of Systems Engineering at UVA. Her research focuses on task sharing, attention management, and interruption management in complex environments that have included aviation, healthcare, military operations, and manufacturing. These work environments impose considerable and continually increasing attentional demands on operators by requiring them to work symbiotically with automation and technology. As such, they are required to divide their mental resources effectively amongst numerous tasks and sources of information. It is critical to consider cognitive ergonomics and systems engineering to support the design of interfaces that can present the right information at the right time. Current research includes: multimodal displays, adaptive displays and cognitive limitations. Her research been funded by the National Science Foundation, Agency for Healthcare Research and Quality, Air Force Office and Scientific Research, and National Institutes of Health with research expenditures totaling over $6 million. She is also the recipient of the NSF CAREER Award and the 2016 APA Briggs Dissertation Award.
William T. Scherer
Professor and Associate Chair of Engineering Systems and Environment, UVA
William T. Scherer is an expert in systems engineering, stochastic control, and systems analytics. Professor Scherer has served on the University of Virginia School of Engineering and Applied Science Engineering faculty since 1986. He also consults on the topics of systems thinking and business analytics with disparate organizations. He has authored and co-authored numerous publications (journal and conference papers, business cases, and book chapters) on intelligent decision support systems, financial engineering, transportation systems, stochastic control, and systems thinking. His current research focuses on systems engineering methodology, sports analytics, financial engineering and systems analytics. His co-authored book, How To Do Systems Analysis, was published by Wiley in 2007, and a follow-on book, How to Do Systems Analysis: Primer and Casebook, was also published by Wiley in 2016. He has strong interests in engineering education and has published papers on curriculum and pedagogy and was awarded an Outstanding University of Virginia Faculty Award in 2007 and the UVa Jefferson Scholars Hartfield-Jefferson Teaching Award 2013. He was also a Visiting Professor at the Darden Graduate School of Business in 2001-2002 and President (and Co-Founder) of the IEEE Intelligent Transportation Systems (ITS) Society 2007-2008.
Suchetha Sharma
Data Scientist, School of Data Science, UVA
Suchetha Sharma is a Data Scientist in the School of Data Science, University of Virginia. She obtained her Master of Science degree in Data Science from the University of Virginia in 2020. Her research interests are in Data Analysis and Machine Learning, with a particular focus on clinical and socioeconomic data. She has been working on several recent projects in the area including ML-assisted diagnosis of cardiopulmonary health conditions and assessment of healthcare disparity among COVID-19 patients.
Rupa Valdez
Associate Professor of Public Health Sciences and Engineering Systems and Environment, UVA
Rupa Valdez is an Associate Professor of Public Health Sciences and Engineering Systems and Environment at UVA. Her research focuses on understanding and designing solutions to support the ways in which people manage health at home and in the community. She draws on methods from multiple disciplines including human factors engineering, cultural anthropology, and health informatics, among others. This work encompasses participatory and co-design approaches and attends to the ways in which social networks, physical environment, community resources, and information technology shape patient experiences. Valdez is particularly interested in how health is managed among marginalized populations, including racial/ethnic minorities, people with disabilities, and people living in under-resourced settings. A complementary research interest is in methodological development for research and teaching in this space. She serves as an Associate Editor for Ergonomics, the Journal of American Medical Informatics Association Open, and Human Factors in Healthcare. Among other appointments, Valdez serves on the Board of Directors for the American Association of People with Disabilities and on PCORI's Patient Engagement Advisory Panel. She is also the Founder and President of the Blue Trunk Foundation.
John Darrell Van Horn
Professor of Psychology and Data Science, UVA
John Darrell Van Horn holds dual appointments as Professor with the School of Data Science and Department of Psychology. His extensive research interests include human neuroimaging, patterns, and biomarkers in brain health and disease; the brain as a data science; high-performance computation; multivariate statistical modeling; time series and spectral analysis; network and graph theory; image processing; programming in C, Matlab, Bash/csh; and methods of FAIR data sharing and open science. His research has appeared in such publications as Science, Nature, Nature Neuroscience, the American Journal of Psychiatry, Biological Psychiatry, British Journal of Psychiatry, Frontiers In Neuroinformatics, Journal of the American Medical Informatics Association, Journal of Cognitive Neuroscience, Journal on Nuclear Medicine, Journal of Psychopharmacology, Magnetic Resonance in Medicine, and Neuroimage, among others. His work has been featured prominently in the media and popular press. Prior to joining UVA in 2019, Van Horn served as associate professor of clinical neurology at the University of Southern California and associate professor at the University of California, Los Angeles. Additional appointments include associate professor at Dartmouth College and staff and doctoral fellowships at the National Institutes of Health. He currently teaches brain mapping with MRI and has served as a capstone research project mentor in the M.S. in Data Science program.
Ifrah Zawar
Assistant Professor of Neurology, UVA
Ifrah Zawar, MD, is a neurologist who specializes in epilepsy and seizure disorders. She has expertise in neurophysiology, adult ketogenic diet, autoimmune epilepsy and surgical epilepsy. Dr. Zawar earned her medical degree from Aga Khan Medical College and University in Pakistan. She completed neurology residency and epilepsy fellowship training at Cleveland Clinic, where she also held an Epilepsy Clinical Scholar position. Before joining UVA Health in 2021, she worked as a clinical instructor at Cleveland Clinic Lerner College of Medicine. “I believe that every patient deserves world-class care and my patients are my priority,” Dr. Zawar shares. She adds: “Growing up, I saw a dear relative struggle with memory loss. Helpless and puzzled, I saw a man suffer who had always been very dear to me. Eventually he succumbed to his illness, and passed away after years of struggling with Alzheimer’s disease. “As I saw him suffer, I realized what I had to do. I had to contribute to people’s lives to minimize their suffering. My interest in public health led me to volunteer at local hospitals since an early age and serve at free clinics ... Gradually through these experiences, I grew interested in medicine. Having grown up in a rural area in Pakistan with little opportunity to excel, I faced many challenges.” With consistent family support and hard work, she was able to get her medical degree from one of the best medical schools in Pakistan and train at one of the best hospitals in United States. In her free time, Dr. Zawar loves to paint and travel.