Predictive Analytics World for Healthcare 2022

Peter Bak is the CIO at Humber River Hospital. He is responsible for the digital vision, on-going operations of that vision, and the innovation agenda. With over 30 years of experience in healthcare informatics, IT operations, software development, and executive leadership, Peter has contributed to the Canadian healthcare system in many ways: driving 100% adoption of digital medical imaging in Canada, creating awareness of digital transformation and Command Centres around the world, and lecturing on Technology in Healthcare. Peter has a PhD in applied engineering from Imperial College, London. He has published various papers on health care-related topics and was recognized as the Canadian public sector CIO for 2016.

Anasse Bari is a professor of computer science and director of the Predictive Analytics and AI research lab at New York University. Prof. Bari teaches computer science and leads a multidisciplinary research team that designs specialized Artificial Intelligence to help solve problems in healthcare, business, finance, politics and social good.

Clinton Brownley, Ph.D., is a data scientist at WhatsApp, where he’s responsible for a variety of analytics projects designed to improve messaging and VoIP calling performance and reliability.  Before WhatsApp, Clinton was a data scientist at Facebook, working on large-scale infrastructure analytics projects to inform hardware acquisition, maintenance, and data center operations decisions.  As an avid student and teacher of modern analytics techniques, Clinton is the author of two books, “Foundations for Analytics with Python” and “Multi-objective Decision Analysis,” and also teaches Python programming and data science courses at Facebook and in the Bay Area. Clinton is a past-president of the San Francisco Bay Area Chapter of the American Statistical Association and is a council member for the Section on Practice of the Institute for Operations Research and the Management Sciences. Clinton received degrees from Carnegie Mellon University and American University.

Aaron is currently the Vice President of Data Science and Solutions at dotData. As a data science practitioner with 14 years of research and industrial experience, he has held various leadership positions in spearheading new product development in the fields of data science and business intelligence. At dotData, Aaron leads the data science team in working directly with clients and solving their most challenging problems.

Prior to joining dotData, he was a Data Science Principle Manager with Accenture Digital, responsible for architecting data science solutions and delivering business values for the tech industry on the West Coast. He was instrumental in the strategic expansion of Accenture Digital’s footprint in the data science market in North America.

Aaron received his Ph.D. degree in Applied Physics from Northwestern University.

Tom is the founding partner of At One Ventures, which backs early-stage (Seed, Series A) companies using disruptive deep tech to upend the unit economics of established industries while dramatically reducing their planetary footprint.

Previous to founding At One, Tom was a founding member of Google X where he led the teams that created self-driving cars, deep learning artificial intelligence, wearable augmented reality and internet connectivity expansion. He played a significant role in established projects with global reach including Microsoft (Outlook) and Yahoo (Search, Answers). 

He has also spent time in the developing world and via social entrepreneurship accelerators, mentoring 200+ entrepreneurs working on global development issues such as access to clean water, electricity, education, health care, and employment.

Tom has spoken at TEDx, Aspen Institute, YPO, SuperVenture, IDEO, Unreasonable and Summit at Sea. He  is also a lifelong inventor, with 75 patents across hardware, software, design, and mechanical systems.

Wilma Compagner is a clinical data scientist at Catharina Hospital in Eindhoven, the Netherlands. It is a tertiary teaching hospital specialized in cardiovascular disease, obesity and oncology. She is focusing on making healthcare more efficient by optimizing the integration of IT solutions in clinical processes.

It is not just about the perfect algorithms, but also on how to implement them in clinical practice in a way they really improve patient care. Wilma holds a Master’s degree in Biomedical Engineering and Clinical Informatics.

Kelley Counts is Director of Data Science at OneBlood. He leads teams that develop and deploy innovative machine learning applications to increase blood donations, anticipate hospital demand for blood products, and optimize the supply chain.  Kelley also has expertise in marketing analytics, data visualization, and the development of statistical business solutions. In addition to his work at OneBlood, Kelley supervises teams of students in Data Science graduate programs. He has also worked on committees to design Python-based Machine Learning graduate courses. Kelley is a frequent speaker on practical applications of machine learning and has published articles on analytics-driven organizational change and workforce adoption. He has served on international professional boards as an advisor on analytics, digital technology, and information systems. Kelley has a Bachelors in Biochemistry, and a MS and MBA in Business Analytics.

Ymke de Jong is working as a data science and system architecture professional. Her mission is to connect the academic cutting edge technologies to the practical challenges we are facing right now in healthcare thereby accelerating digital transformation by working together. Seeing data driven solutions actually have impact and meet and exceed expectations gives her energy. Ymke holds a degree in Biomedical Engineering focusing on computational biology and data science. Currently working for Royal Philips sharing the vision to improve the life of 3 billion people by 2030.

Chris is the Chair of Predictive Analytics World Healthcare and the Vice President of Advanced Analytics for OSF Healthcare where he leads a team of data scientists and automation engineers who create and deploy industry leading advanced analytics solutions.  He has more than 16 years of experience working in healthcare and holds a MS in Predictive Analytics from Northwestern University, where he focused on advanced modeling techniques and predictive text mining.

Siddha Ganju, whom Forbes featured in their 30 under 30 list, leads AI innovation in LLM and Guardrails along with the deployment of Medical Instruments for Nvidia partners at Nvidia. Siddha previously worked in the self-driving teams for simulation, perception, scalable training, and inference along with global automotive partnerships and go-to-market strategies.

Robert Grossman is a partner at Analytic Strategy Partners and a professor at the University of Chicago.  From 2002 to 2016, he was the Founder and Managing Partner of Open Data Group, which provided data science consulting services to a wide variety of companies, including those in financial services, location services, computational advertising and cybersecurity. From 1996 to 2001, he was the Founder and CEO of Magnify, which developed predictive analytic software for the financial services and computational advertising industries.  Magnify was sold to ChoicePoint in 2003 and is now part of the RELX Group.  He is the Frederick H. Rawson Professor of Medicine and Computer Science and the Jim and Karen Frank Director of the Center for Translational Data Science at the University of Chicago, where he leads a data science research group that is developing systems and algorithms for managing, analyzing and sharing large biomedical and environmental datasets.

Rikkert Keldermann is a capacity manager at Catharina Hospital in Eindhoven, the Netherlands, with experience in healthcare business intelligence, clinical informatics, data analysis and  strategic planning. He has a Master’s in Biomedical Engineering from the Eindhoven University of Technology and a PhD degree in Bioinformatics from the University of Utrecht, the Netherlands

Dongsul Kim is a Data Scientist at OSF Healthcare, where he has been focusing on predictive model evaluation and implementation. Previously at the University of Kansas Health System, he worked on a wide range of analytical activities, including data collection, statistical analysis, data mining, ML model development & implementation, and BI solution. As a founding member of AI Center of Excellence at the health system, he also contributed to a ground work of team structure, process of ML model development & implementation, and ethical integrity. With his practical experiences in healthcare settings, his recent interest has been on delivering meaningful impact of ML models in healthcare. Dongsul holds MPH in Epidemiology from the University of Minnesota and MS in Environmental Health Science from the SUNY at Albany.

Dohyeong Kim, Ph.D. is currently a Professor of public policy, geospatial information sciences and social data analytics and research in the School of Economic, Political and Policy Sciences at the University of Texas at Dallas. He also serves as an Associate Dean of Graduate Education and works as the Director of the Geospatial Health Research Group. His multidisciplinary and multinational collaborative research projects have been funded by the U.S. National Institute of Health, World Health Organization, and the National Research Foundation of Korea. Most of his research fundings have been published in numerous leading refereed journals in public and environmental health fields, and presented in over 200 national and international meetings. His research interests include highly interdisciplinary, including global health and safety, environmental health informatics, and spatiotemporal big data analysis and machine learning. He was a recipient of the 2008 New Investigators in Global Health Award. He holds a Ph.D. in health planning from the University of North Carolina at Chapel Hill.

Danita Kiser is a Director of Applied Research and AI/ML in Optum Technology, part of UnitedHealth Group. She is an innovation leader with more than 20 years’ experience in companies such as AOL, Turner Broadcasting, Cox Communications, and numerous technology start-ups. For the past six years, Danita has held roles at Optum in applied research, data science, product management and led delivery of innovative products in big data, infectious disease forecasting and voice processing. She holds a Bachelor of Science degree from the University of Virginia and a PhD from Emory University.

Mariana Simons is a Senior Data Scientist at Philips Research. She holds a PhD in Numerical Methods and Algorithms from the University of Nijmegen in the Netherlands. She also completed “with distinction” the Data Science Specialization at the Department of Biostatistics at Johns Hopkins Bloomberg School of Public Health. Her passion about innovation in healthcare and data analytics resulted in more than 50 journal publications and patent applications.

Karl Rexer founded Rexer Analytics in 2002. He and his teams have built an outstanding reputation providing predictive modeling and analytic consulting to clients across many industries. Recent clients include OneBlood, PwC, Boston Scientific, Redbox, ADT Security, Interamericana University, MIT, Forward Financing, SharkNinja, and many smaller companies. In addition to leading client engagements and hands-on data work, Karl is a predictive analytics evangelist, frequently speaking at conferences, colleges, and other events. He also serves on Advisory Boards for the Business Analytics programs at both Babson College and Bentley University. Since 2007 Rexer Analytics has conducted surveys of analytic professionals, asking them about their algorithms, tools, behaviors and  views. Summary reports from these surveys are available as a free download from the Rexer Analytics website. Prior to founding Rexer Analytics, Karl held leadership positions at several consulting firms and two multi-national banks. Karl holds a PhD from the University of Connecticut.

Sung-Chul Seo received a PhD in environmental health and occupational hygiene with strong background in aerosol science, extensive experiences in project management and laboratory works, and exposure assessment for radon and air pollutants, as well as chemical/biological agents. Since 2018, he has been the President of Korea Association of Radon. He is currently a Professor with Seokyeong University, Seoul, South Korea. He has served on the executive boards of Korean Society of Indoor Environment, and for over 20 years he is dedicated to the improvement of indoor air related to environmental health, including radon, particulate matters, and bioaerosols. Recently, he is focusing on establishment of prevention platform using deep learning technology based on big data attributed to real-time the IoT devices. He has many funding as well as academic articles. His research interest includes development of monitoring system for the level of environmental risk factors (i.e., particulate matters) to prevent diseases exacerbations.

Tom (PhD, Physics) has spent most of his career building computational tools and applying them to complex problems. As a Lead Scientist at Elder Research, Tom contributes to a diverse collection of projects and clients across the company. Highlights include Bayesian multifactor modeling with Stan, object detection with PyTorch, and network science and graphs research. He most enjoys the opportunity to work with many other Elder Research scientists to learn, experiment, and solve interesting problems.

Tom joined Elder Research after completing a PhD in Physics at the University of North Carolina, where he applied high performance computing systems to the study of nuclear radioactive decays. This radioactivity occurs in massive quantities during supernovae and neutron star mergers like those events observed by gravitational wave detectors in recent years.

Eric Siegel, Ph.D., is a leading consultant and former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series and its new sister, Generative AI Applications Summit, the instructor of the acclaimed online course “Machine Learning Leadership and Practice – End-to-End Mastery,” executive editor of The Machine Learning Times, and a frequent keynote speaker. He wrote the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, which has been used in courses at hundreds of universities, as well as The AI Playbook: Mastering the Rare Art of Machine Learning Deployment. Eric’s interdisciplinary work bridges the stubborn technology/business gap. At Columbia, he won the Distinguished Faculty award when teaching the graduate computer science courses in ML and AI. Later, he served as a business school professor at UVA Darden. Eric also publishes op-eds on analytics and social justice.

Eric has appeared on Bloomberg TV and Radio, BNN (Canada), Israel National Radio, National Geographic Breakthrough, NPR Marketplace, Radio National (Australia), and TheStreet. Eric and his books have been featured in Big Think, Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, Fast Company, The Financial Times, Forbes, Fortune, GQ, Harvard Business Review, The Huffington Post, The Los Angeles Times, Luckbox Magazine, MIT Sloan Management Review, The New York Review of Books, The New York Times, Newsweek, Quartz, Salon, The San Francisco Chronicle, Scientific American, The Seattle Post-Intelligencer, Trailblazers with Walter Isaacson, The Wall Street Journal, The Washington Post, and WSJ MarketWatch.

Owen is the Director of Machine Learning for Revenue and Access at Epic systems, where he has work for over seven years, working on predictive analytics for population health, acute care, and operations. He has helped healthcare organizations across the world gain value from implementing predictive analytics within workflows. He has also served on the advisory board for multiple colleges, including UW-Platteville and Dickinson College, to help them develop Data Science major programs. Owen holds a Ph.D. in Mathematics from UCLA and before working at Epic he held a faculty position at UW-Madison and visiting scholar positions at the University of Tokyo and the Sorbonne.

David Talby is the Chief Technology Officer at John Snow Labs, helping companies apply artificial intelligence to solve real-world problems in healthcare and life science. David is the creator of Spark NLP the world's most widely used natural language processing library in the enterprise. He has extensive experience building and running web-scale software platforms and teams – in startups, for Microsoft's Bing in the US and Europe, and to scale Amazon's financial systems in Seattle and the UK. David holds a Ph.D. in Computer Science and Masters degrees in both Computer Science and Business Administration. He was named USA CTO of the Year by the Global 100 Awards and GameChangers Awards in 2022.

Co-founder of MIM Solutions. A graduate from the University of Warsaw with a Ph.D. in Informatics and double master's degree in Informatics and Mathematics. Assistant professor at the University of Warsaw. Experienced both in the theoretical and commercial aspects of machine learning. His principal focus is on delivering deep learning solutions in socially important areas, predominantly medicine.