Co-hosted by MIT CSAIL and STEMM Global


STEMM MIT CSAIL AI in Healthcare Summit

#AIHS2020 was a great success! Thanks to all the experts in attendance for your valuable contributions.

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Business and Academia for Innovations in Healthcare

Scientists, AI researchers, healthcare experts and business leaders will come together to discuss critical healthcare challenges, collaborate to minimize the damages, and find preventive measures. It is crucial now to drive the innovation and development of AI for good.

Covering the most relevant topics of AI in healthcare – including the ways in which AI is being used during the current pandemic – the STEMM MIT CSAIL AI in Healthcare Summit will be held online and is co-hosted by MIT’s Computer Science & Artificial Intelligence Laboratory and STEMM Global Scientific Community.

Meet World-Class
AI Experts

STEMM MIT CSAIL AI in Healthcare Summit unites researchers and business leaders, working together to address public health problems and improving healthcare outcomes with AI, to share their vision and experience for better global collaboration.

Director of MIT Computer Science & Artificial Intelligence Lab

Daniela Rus

Daniela Rus is the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science and Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT. Rus’s research interests are in robotics, mobile computing, and data science. Rus is a Class of 2002 MacArthur Fellow, a fellow of ACM, AAAI and IEEE, and a member of the National Academy of Engineering, and the American Academy for Arts and Science. She earned her PhD in Computer Science from Cornell University.
European Commission Directorate - General Communications Networks, Content and Technology

Saila Rinne

Head of Sector – EU policies
European Commission
Directorate-General Communications Networks, Content and Technology
Unit H3 “eHealth, Well-Being and Ageing”
Director of EPSRC CDT in Smart Medical Imaging, King's College London

Julia Schnabel

Julia Schnabel joined King's College London in July 2015 as Chair of Computational Imaging at the School of Biomedical Engineering and Imaging Sciences, where she is Director of the EPSRC Centre for Doctoral Training in Smart Medical Imaging, jointly run by King’s College London and Imperial College London.

She is School Head for Research & Impact, and Co-Director of the NIHR funded Medtech and In vitro diagnostic Co-operative (MIC) in Cardiovascular Diseases.

Her research interests are in machine/deep learning, nonlinear motion modelling, multi-modality imaging, dynamic imaging and quantitative imaging for applications in cancer, cardiovascular diseases, and fetal health. Her focus is on developing mathematically principled methods for correcting complex types of motion, such as sliding organs, fetal movements, as well as imaging artefacts. She also has an interest in early disease detection, characterisation and prediction of response to treatment, with the aim of rapid translation into clinical practice for patient stratification and improved treatment outcome.

Julia has over 25 years’ experience in medical imaging, has successfully supervised 20 PhD students to completion, and is leading a large research group at King’s, in close collaboration with Imperial.

Julia is elected member of the MICCAI Society Board (2017-21) and the IEEE EMBS Administrative Committee (2017-19, re-elected 2020-22). She is also a member of the Inria Science Board (2017-20) and the EPSRC Strategic Advisory Team (SAT) in Healthcare Technology (2018-21). In 2018 Julia was elected MICCAI Fellow "For contributions to multiple areas of medical image computing, and for distinguished service to the MICCAI conference and Society", and 2019 she was ellected Fellow of the European Laboratory for Learning and Intelligent Systems (ELLIS).

PhD in Computer Science, University College London, University of London, UK. January 1994 → February 1998.
MSc in Computer Science, Technische Universität Berlin, Germany. October 1989 → September 1993


Una-May O'Reilly

Una-May O'Reilly is the leader of ALFA Group at MIT-CSAIL. ALFA focuses on Machine learning technology, evolutionary algorithms, and data science for knowledge mining, prediction, analytics, and optimization. ALFA conducts research in cyber security, software analysis, MOOC technology, and medical technology. Una-May has expertise in agile data science systems with rapid intelligent data analytics capabilities. These systems span organization and visualization of raw data through to machine learning inference. She educates the forthcoming generation of data scientists, teaching them how develop state of art techniques that address the challenges spanning data integration to knowledge extraction.

Una-May is recognized by ACM SIG-EVO for her significant contributions having been elected a Fellow of ISGEC. She has served as Vice-Chair of ACM SIG-EVO, and has served as chair of the largest international Evolutionary Computation Conference, GECCO. She has served on the GECCO business committee, co-led the 2006 and 2009 Genetic Programming: Theory to Practice Workshops and co-chaired EuroGP, the largest conference devoted to Genetic Programming. In 2013, Una-May co-inaugurated the Women in Evolutionary Computation group at GECCO. She received the EvoStar Award for Outstanding Achievements in Evolutionary Computation in Europe in 2013. In 2018, Una-May was recognized by Nature Research journals for outstanding contributions in peer review. Recently, ACM SIG-EVO elected Una-May for Career Recognition for Scientific Merit.

Una-May is an area editor for Data Analytics and Knowledge Discovery for Genetic Programming and Evolvable Machines (Kluwer), and editor for Evolutionary Computation (MIT Press), and action editor for the Journal of Machine Learning Research. She serves in an advisory role on the Oakridge National Lab Directorate Advisory Committee. She serves as an Editorial Board Member of the new ACM Transactions on Evolutionary Learning and Optimization (ACM TELO). Start Up Advisory Positions: Aspiring Minds, Legit Patents, PatternEx, Cardinal Wind/Evervest acquired by Ultra Capital (to 2015). Research Sponsorships: MIT-IBM Watson AI Lab, Crowdstrike, Accenture, BBVA, Jaguar Land Rover, Philips Healthcare N.A., Arcelor Mittal, Givaudan, VMWare, National Science Foundation, DARPA, Dept. of Energy, Crossword Cybersecurity, HKUST-MIT Research Alliance Consortium, Cybersecurity @CSAIL, BigData @CSAIL, and SystemsThatLearn @CSAIL.

Number of graduate students: 17 (4 Ph.D., 13 Masters) Number of Postgraduate Scholars: 9

Una-May hails from Ottawa, Ontario Canada. She completed her undergraduate degree in Computer Science at the University of Calgary in 1985. After 3 years at Bell Northern Research, Una-May completed her MCS (’90) and Ph.D. (’95) in Computer Science at Carleton University. Her Ph.D. dissertation is one of the world’s first on the AI topic of Genetic Programming. She joined MIT as a member of the Artificial Intelligence Lab in 1998. She is the author of over 100 academic papers.

Director of the Language Intelligence and Information Retrieval Lab, KU Leuven

Marie-Francine Moens

Marie-Francine Moens is a full professor in the Department of Computer Science at KU Leuven. She leads a research team specialized in natural language processing and information retrieval, currently composed of 18 PhD students and 3 postdocs.

Her main direction of research is the development of novel methods for automated content recognition in text and multimedia using statistical and neural machine learning.

She is author or co-author of more than 350 peer-reviewed publications many of which published in major natural language processing, machine learning, artificial intelligence and information retrieval venues such as AAAI, ACL, EMNLP, ICML, JAIR, ML, SIGIR , TACL and WSDM. She is holder of the European Research Council (ERC) Advanced Grant CALCULUS (Commonsense and Anticipation enriched Learning of Continuous representations sUpporting Language UnderStanding, 2018 – 2023, Horizon 2020 - 788506).

She is currently associate editor of the journal IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). In 2011 and 2012 she was appointed as chair of the European Chapter of the Association for Computational Linguistics (EACL).

Director of Cambridge Centre for AI in Medicine, Cambridge University

Mihaela Van der Schaar

Professor van der Schaar is John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence and Medicine at the University of Cambridge and a Turing Fellow at The Alan Turing Institute in London, where she leads the effort on data science and machine learning for personalised medicine.

She is an IEEE Fellow (2009). She has received the Oon Prize on Preventative Medicine from the University of Cambridge (2018). She has also been the recipient of an NSF Career Award, 3 IBM Faculty Awards, the IBM Exploratory Stream Analytics Innovation Award, the Philips Make a Difference Award and several best paper awards, including the IEEE Darlington Award. She holds 35 granted USA patents.

The current emphasis of her research is on machine learning with applications to medicine, finance and education. She has also worked on data science, network science, game theory, signal processing, communications, and multimedia. Prior to her academic career, she was a Senior Researcher at Philips Research in the Netherlands and USA.

Head of the Pattern Recognition Lab, FAU

Andreas Maier

Prof. Dr. Andreas Maier was born on 26th of November 1980 in Erlangen. He studied Computer Science, graduated in 2005, and received his PhD in 2009. From 2005 to 2009 he was working at the Pattern Recognition Lab at the Computer Science Department of the University of Erlangen-Nuremberg. His major research subject was medical signal processing in speech data. In this period, he developed the first online speech intelligibility assessment tool – PEAKS – that has been used to analyze over 4.000 patient and control subjects so far.

From 2009 to 2010, he started working on flat-panel C-arm CT as post-doctoral fellow at the Radiological Sciences Laboratory in the Department of Radiology at the Stanford University.

From 2011 to 2012 he joined Siemens Healthcare as innovation project manager and was responsible for reconstruction topics in the Angiography and X-ray business unit.

In 2012, he returned the University of Erlangen-Nuremberg as head of the Medical Reconstruction Group at the Pattern Recognition lab. In 2015 he became professor and head of the Pattern Recognition Lab.

Since 2016, he is member of the steering committee of the European Time Machine Consortium. In 2018, he was awarded an ERC Synergy Grant “4D nanoscope”.

Current research interests focuses on medical imaging, image and audio processing, digital humanities, and interpretable machine learning and the use of known operators.

MIT Sloan

Kathleen Kennedy

Kathleen is a strategic leader with a unique skill set for transforming organizations as well as building new ones.

Director, Special Projects, at MIT; Executive Director, Center for Collective Intelligence at the MIT Sloan School.

Lead organizer of The Engine, 2016-17 (, a venture fund and accelerator program for tough tech startups.

Former President, Chief Strategy Officer, MIT Technology Review, MIT’s global media company President of the MIT Enterprise Forum, a global network of chapters organized around entrepreneurship.

Co-founder, HUBweek (, a first-of-its-kind civic collaboration and weeklong festival that brings together the most
creative and inventive minds making an impact in art, science and technology.

Kathleen is a frequent speaker at global conferences. She is very active in the community, serving as a judge for many competitions including the MacArthur Foundation. In 2017, she was named by the Women of the Harvard Club as one of Boston’s Most Influential Women.

Co-founder, Co-Chief Executive Officer, and President of Evidation Health

Christine Lemke

Christine is the Co-founder, Co-Chief Executive Officer, and President of Evidation Health. Previously, Christine was the Co-founder and Chief Operating Officer of Sense Networks, developers of the first machine learning platform for mobile phone activity data (exited to She has also held roles at 3iGroup (Paris), Microsoft XBOX and co-founded Chicago-based Channel IQ, a product analytics platform. Christine has a BA from the University of Washington and an MBA from HEC Paris.
Director of the UCL Center for Artificial Intelligence

David Barber

David Barber received a BA in Mathematics from Cambridge University and subsequently a PhD in Theoretical Physics (Statistical Mechanics) from Edinburgh University. He is Director of the UCL Centre for Artificial Intelligence, which aims to develop next generation AI techniques. He has broad research interests related to the application of probabilistic modelling and reasoning. David is also a Fellow of the Alan Turing Institute and the CSO of re:infer, an AI spin-out from UCL.
CEO and Co-Founder, Composable Analytics, Inc.

Andy Vidan

Dr. Andy Vidan has a passion for developing and scaling disruptive technology platforms, drawing from his diverse and extensive experience spanning data science, information technology and applied physics. Andy is CEO and Co-Founder of Composable Analytics, Inc., a data analytics and machine learning software company headquartered in Cambridge, MA. Composable’s Intelligent DataOps platform is based on technology invented and prototyped at MIT, and enables enterprises to rapidly adopt a modern data operations strategy to robustly manage unlimited amounts of data. Composable’s recent joint venture Scrypt.AI with CheckAlt delivers intelligent document processing solutions for a variety of industry sectors, including healthcare.
Andy began his career at MIT Lincoln Laboratory, and was a key technical contributor on a broad range of homeland security and defense research programs. He developed a scalable, distributed web application system, now operational and used by entities such as DHS and NATO, for which he received the IEEE Technical Field Award. Andy has a PhD from Harvard University and a BS from Cornell University.

Matthew Versaggi


MS, computer science (artificial intelligence), DePaul University
MBA, international business and economics, DePaul University
BA, computer science, Alfred University
BS, finance and management information systems, Alfred University
Five professional certificates including two in security (server/network), one in data science and machine learning, one in artificial intelligence, one in quantum computing
Career bio

I hold a senior leadership role in the artificial intelligence and cognitive technologies space for the Advanced Technology Collaborative (ATC) at Optum Technology. This combination role comprises the responsibilities of thought leader, evangelist, education subject-matter expert (SME), strategist, and advanced technology delivery of projects and technical capabilities in the AI/CT spaces.

My previous role in Optum was leading a global AI/machine learning delivery team (Dublin, Boston, Minnesota and South Carolina). Other responsibilities I hold are education and SME in AI/ML for the College of Artificial Intelligence in Optum Tech University, and SME in the UHG Patent Review Board reviewing AI/ML technologies.

Prior to Optum, my roles were: AI engineer for a military contractor, CEO of my own company, CIO of a dental insurance company, adjunct professor at a university, business startup partner, and an AI developer.

Technology areas I work on

Graph technologies
Deep learning
Natural language processing
Image processing/computer vision
Machine learning
Quantum computing
Intelligent agents
Awards and recognitions

DePaul University teaching award: The Daniel Siden Outstanding Adjunct Faculty of the College of Commerce, 2001.

Co-founder at Synodis

Yann de Cambourg

Co-founder at Synodis, an IT company specialized in Healthcare.
Yann has a wide knowledge of interoperability in healthcare systems.
Yann has deployed several healthcare data components ; he is an expert on FHIR, data management and data sharing.

Synodis is an healthcare integrator at the crossing between IT and Business.
EMR implementation, Interoperability and Digital Services Integration are our core competencies : FHIR Servers, Interoperability and MDM platforms, NLP, Semantic analysis, Machine Learning, Data Labs

Scientific Director of the Italian Institute of Technology

Giorgio Metta

Giorgio Metta is the Scientific Director of the Istituto Italiano di Tecnologia (IIT). He holds a MSc cum laude (1994) and PhD (2000) in electronic engineering both from the University of Genoa. From 2001 to 2002, Giorgio was postdoctoral associate at the MIT AI-Lab. He was previously with the University of Genoa and from 2012 to 2019 Professor of Cognitive Robotics at the University of Plymouth (UK).

He was member of the board of directors of euRobotics aisbl, the European reference organization for robotics research. Giorgio Metta served as Vice Scientific Director of IIT from 2016 to 2019. He coordinated IIT's participation into two of the Ministry of Economic Development Competence Centers for Industry 4.0 (ARTES4.0, START4.0).

He was one of the three Italian representatives at the 2018 G7 forum on Artificial Intelligence and, more recently, one of the authors of the Italian Strategic Agenda on AI.

Giorgio coordinated the development of the iCub robot for more than a decade making it de facto the reference platform for research in embodied AI. Currently, there are more than 40 robots reaching laboratories as far as Japan, China, Singapore, Germany, Spain, UK and the United States. Giorgio Metta research activities are in the fields of biologically motivated and humanoid robotics and, in particular, in developing humanoid robots that can adapt and learn from experience.

Giorgio Metta is author of more than 300 scientific publications. He has been working as principal investigator and research scientist in about a dozen international research as well as industrial projects.


Amar Gupta

Amar Gupta (born 1953) is a computer scientist, originally from Gujarat, India and now based in the United States. Gupta has worked in academics, private companies, and international organizations in positions that involved analysis and leveraging of opportunities at the intersection of technology and business, as well as the design, development, and implementation of prototype systems that led to widespread adoption of new techniques and technologies. He has surmounted several strategic, business, technical, economic, legal, and public policy barriers related to several innovative products and services.

Gupta has spent the bulk of his career at MIT. In 2015, he rejoined MIT to work at the Institute for Medical Engineering and Sciences (IMES), Department of Electrical Engineering & Computer Science, and the Computer Science & Artificial Intelligence Lab (CSAIL) on innovation and entrepreneurship related to Digital Health and Globally Distributed Teams. He serves as Principal/Co-Principal Investigator and Coordinator for “Telemedicine” and “Enhancing Productivity of Geographically Distributed Teams” areas.

Gupta currently teaches a MIT School of Engineering course -- Telehealth and Telemedicine for Enhancing Global Healthcare: Opportunities and Challenges. The course received very high grades in student evaluation of course contents and instructor for all 3 consecutive years. MIT uses a scale of 1-7 for such grades with 1 being very poor and 7 being excellent, and the course received Median Grade of 7 overall in all years. Over these past years, he has assisted multiple startups established by students of this course and supervise research of dozens of students. During 2018, he delivered the keynote addresses at events in DC for senior officials of federal government officials and for federation of state medical boards. His subsequent address streamlined to a global audience is available online.

During the interim period that he was away from MIT, Gupta served as Phyllis and Ivan Seidenberg Endowed Professor and Dean of the Seidenberg School of Computer Science and Information Systems at Pace University, USA and as the Thomas R. Brown Professor of Management and Technology at the University of Arizona, USA. At the latter university, he was also Professor of Entrepreneuship and Professor of MIS at Eller College of Management, Profess.

PathAI, Co-Founder & CTO

Aditya Khosla

Co-Founder & CTO

Aditya recently completed his PhD in machine learning and computer vision at MIT. He completed his MS at Stanford in 2011 and BS at Caltech in 2009. In his research he developed new methods for an array of applications in computer vision, including eye-tracking, prediction of image memorability, and visualization of deep networks. He is the recipient of a Facebook Fellowship and his work has been widely covered by various media outlets including BBC, The New York Times and The Washington Post. He has published over 30 papers in the fields of deep learning, computer vision and neuroscience.


Ramesh Raskar

Raskar joined MIT Media Lab in 2008. Raskar, together with others developed a computational display technology that allows observers with refractive errors, cataracts and some other eye disorders to perceive a focused image on a screen without wearing refraction-corrective spectacles. The technology uses a light field display in combination with customized filtering algorithms that pre-distort the presented content for the observer.

His lab produced a number of extreme highspeed pictures using a femto-camera that took images at around one-trillion frames per second. They have also developed a camera to see around corners using bursts of laser light.

Juliett Fiss has covered his role as the catalyst behind the Siggraph NEXT program at Siggraph 2015 in Los Angeles.

Raskar was awarded the "2017 CG Achievement Award" by ACM SIGGRAPH for his potential contribution in computational photography and light transport and their applications for social impact.

He has been influential in deploying research ideas in the real world. Startups created by members of his CameraCulture research group include (ophthalmic tests), Photoneo (high speed 3D sensing), Labby (AI for food testing), Lumii (novel printing for 3D imagery), LensBricks (computer vision with computational imaging), Tesseract (personalized display) and more. Non-profits emerging from his efforts include (AI for Social Impact), MIT Emerging Worlds, LVP-MITra, REDX-WeSchool, DigitalImpactSquare and more.
He serves on the Expert Commission of $3.5 Billion Botnar Fondation as AI and Health expert.

Founder, ExactCure

Frédéric Dayan

Frédéric Dayan, 40 years old, is the founder of ExactCure, a company that aims at simulating your personalized response to drugs thanks to digital models. His dream is to build your perfect virtual avatar in a mobile application. Imagine how this virtual copy of yourself could help you optimize your health!

Frédéric is a former Research & Development (R&D) team leader from the Dassault Systèmes software editor. He is expert in modeling for Life Sciences. He received two Doctorates (Pharmaceutical Science + Cancer Research), and a Physics Engineering diploma from the “Ecole de Physique et de Chimie de Paris”.

After an academic career in bio-modeling as a researcher and teacher at the University of Nice Sophia Antipolis, he decided to manage teams in private R&D, both for small and big industries. Now he is creating his own company in order to bring his vision to life: a world where patients and health professionals would benefit from cutting-edge technologies in modeling and simulation.

CEO and Founder, BioMind

Raymond Moh

Raymond is the founder and CEO of BioMind®, an artificial intelligence company specialising in healthcare and has a strong team of over 100 in-house deep learning scientists, medical experts, and research advisors from prestigious hospitals and universities. He is also the co-founder of CHAIN, the world’s largest AI research center developing AI applications from diagnosis to treatment for neurological disorders.
Raymond graduated from the prestigious National University of Singapore’s Engineering Double Degree Program and has served as a scholar and technology advisor in big data engineering since 2008. From FinTech to HealthTech, he has advised over 50 organisations to achieve high growth rate and productivity driven by technology adoptions.

David Sontag

Led by David Sontag, the Clinical Machine Learning Group is interested in advancing machine learning and artificial intelligence, and using these techniques to advance health care.

Broadly, we have two goals:

Clinical: To truly make a difference in health care, we need to create algorithms that are useful for solving real clinical problems.

Machine learning: We need rigorous solutions, which can pave the way for safe deployment of machine learning in high-stakes settings like healthcare.

Our lab is broadly interested in advancing machine learning and artificial intelligence, and using these to transform health care. Here we explain our three broad focus areas as well as representative papers. For more papers, see our publications section.

Clinical Prediction
These are exciting times for the practice of medicine. The rapid adoption of electronic health records has created a wealth of new data about patients, which is a goldmine for improving our understanding of human health. Our lab develops algorithms that use this data to make better clinical predictions in areas like antibiotic resistance, multiple myeloma, Parkinson’s disease, and other chronic illnesses. In addition, we are concerned with efforts around fairness and interpretability to ensure accurate, useful, and equitable clinical predictions.

Probabilistic and Causal Inference
Probabilistic inference is one of the cornerstones of machine learning. Whether for parameter inference at training time or answering queries at test time, we build new inference algorithms for inference in undirected and directed graphical models along with tools to analyze their efficacy. We work on probabilistic inference in deep generative models by developing new inference networks that learn to amortize approximate variational inference. In many instances, the quantity of interest within a Bayesian network is of a causal nature. To that end, our lab develops novel methods for answering causal queries that work effectively with high-dimensional data.

Medical Knowledge and Extraction
Today’s electronic health records are predominately a place for recording a patient’s health data. We aim to develop the foundation for the next-generation of intelligent electronic health records, where machine learning and artificial intelligence is built-in to help with medical diagnosis, automatically trigger clinical decision support, personalize treatment suggestions, autonomously retrieve relevant past medical history, make documentation faster and higher quality, and predict adverse events before they happen. A major challenge is the need for robust machine learning algorithms that are safe, interpretable, can learn from little labeled training data, understand natural language, and generalize well across medical settings and institutions.

CEO and Founder of Ad Astra Media LLC , 2020 Eisenhower Fellow

Jose Morey

CEO and Founder of Ad Astra Media LLC and an Eisenhower Fellow with the 2020 ZHI-XING Fellows Program. He is a health and technology keynote speaker, author and a consultant for NASA, Forbes, MIT and the White House Office of Science and Technology. He is considered a leader in exponential technology innovation and excels at leading multidisciplinary teams that sit at the epicenter of biotechnology, AI and aerospace.

He is considered the first Intergalactic Doctor and is often featured on Forbes, Univision, CNBC and NASA360. His latest essay “The Future Shock of Medicine: How AI will Transform Disease, Death and Doctors” was recently reviewed by The Wall Street Journal along with other contributions by contemporary thought leaders. He serves as a technology and business advisor for MIT, NASA, UVA, African Innovation Alliance, US-Polish Alliance for Innovation and has served as special envoy to the Polish Space Agency.

His expertise in big data and innovation has made him a sought-after consultant in many industries. As Chief Medical Innovation Officer for Liberty BioSecurity, he helps drive innovation in genetic intelligence, national defense, biotechnology, precision medicine and augmented human performance.

As Chief Engineering Council in charge of Innovation for Hyperloop Transportation Technologies, he directs international engineering teams in technology and intellectual property development.

As the Medical Technology and Artificial Intelligence Adviser for NASA iTech, he helped evaluate research initiatives that would develop novel technology to meet the 2030 Mars Mission objectives and deep space exploration.

Dr. Morey has previously worked with IBM Watson Health as their Associated Chief Health Officer where he helped develop global AI medical technologies.

Morey has also consulted with many companies to help create and train their deep learning algorithms and neural networks to develop intelligent systems in healthcare and aerospace.

Morey sits on several AI advisory boards and has over 100 peer-reviewed publications, articles, presentations, and lectures. He also has a seat on the Informatics Leadership Council for the American College of Radiology.

He has given talks to NASA360, the Radiologic Society of North America, HIIMS, Academy Health, Health Datapalooza, Tech.Co, Frost & Sullivan Executive MindXchange, Stifel Nicolaus Healthcare Investment Conference, the Chinese Medical Association and the Senate of the Commonwealth of Puerto Rico.

Morey holds an adjunct professorship of Radiology and Biomedical Imaging at the University of Virginia and at Eastern Virginia Medical School. And he is a guest lecturer at Singularity University. Morey is also an advisor with MIT Solve, Ideas MIT, Tampa Bay Wave, and I-Corps Puerto Rico.

Dr. Morey is a Senior Advisor with the NASA Space Breathing Initiative, where he helps direct an international team of hardware and software engineers to develop a blockchain based data platform pipeline in collaboration with NASA and NetApp for COVID-19 rapid response utilizing hybrid cloud. Identified and guided hardware and software parameters well as edge device integration and clinical AI development for prescriptive analytics and integration with the US National Emergency Broadcasting System.

He also serves as a Special Advisor with the White House Office of Science and Technology Kaggle CORD19 Project. He advised the Director of Research of CORD19 which is a collaboration between the Allen Institute for AI, Chan Zuckerberg Initiative (CZI), Georgetown University’s Center for Security and Emerging Technology (CSET), Microsoft, and the National Library of Medicine (NLM) at the National Institutes of Health to create AI platform to review scholarly literature about COVID-19, SARS-CoV-2, and the Coronavirus group. Advised director on how to transform research content into machine-readable form, making the corpus ready for analysis and study.

Principal Scientist at Google DeepMind

Oriol Vinyals

Oriol Vinyals is a Principal Scientist at Google DeepMind, and a team lead of the Deep Learning group. His work focuses on Deep Learning and Artificial Intelligence. Prior to joining DeepMind, Oriol was part of the Google Brain team. He holds a Ph.D. in EECS from the University of California, Berkeley and is a recipient of the 2016 MIT TR35 innovator award. His research has been featured multiple times at the New York Times, Financial Times, WIRED, BBC, etc., and his articles have been cited over 80000 times. Some of his contributions such as seq2seq, knowledge distillation, or TensorFlow are used in Google Translate, Text-To-Speech, and Speech recognition, serving billions of queries every day, and he was the lead researcher of the AlphaStar project, creating an agent that defeated a top professional at the game of StarCraft, achieving Grandmaster level, also featured as the cover of Nature. At DeepMind he continues working on his areas of interest, which include artificial intelligence, with particular emphasis on machine learning, deep learning and reinforcement learning.
Deputy Medical Director, Department of Cardiology, Angiology, Pneumology University Hospital Heidelberg

Benjamin Meder

Prof. Dr. med. Benjamin Meder
Deputy Medical Director (Klinik für Kardiologie, Angiologie, Pneumologie)
Management (Institut für Cardiomyopathien Heidelberg)
Management (Herzkatheter)
Research group head (AG Molekulargenetisches Labor für funktionelle Molekulargenetik und translationale Biotechnology)
Co-founder and CEO of Huma.AI

Lana Feng

Dr. Lana Feng is the co-founder and CEO of Huma.AI. She has over 20 years of experience in biotech and pharmaceutical industry, mostly in precision medicine. Dr. Feng came from Novartis Oncology Business Unit where she established international partnerships for their precision medicine programs. She joined Novartis through its acquisition of Genoptix. Dr. Feng built the BioPharma division at Genoptix, where she grew the business from zero to $45M in five years by forging alliances with pharmaceutical companies and providing CDx development for targeted therapies. The division was instrumental in Genoptix’ acquisition by Novartis for $500M.

Prior to Genoptix, Dr. Feng was an early employee and held key positions at GeneOhm Sciences, which was acquired by Becton Dickinson for $300M, and Nanogen which went public in 1998.

Dr. Feng is a member of Bayhelix, an organization of global healthcare leaders of Chinese heritage. She was the winner of BRAVO Rising Star Award from National Association of Women Business Owners (NAWBO), and Industry Innovation Award from Blossom Ventures presented at the annual Women’s Entrepreneurship Summit.

Optum Advisory Services Population Health Practice Lead and Former State Health Officer North Dakota

Mylynn Tufte

Mylynn K. Tufte, MBA, MSIM, RN

Mylynn uses technology to improve health equity, social determinants of health, and care for vulnerable populations. She has helped organizations develop and implement innovative solutions that improve health care for diverse populations.
Her experience includes working with:
• Federal, state, local and tribal governments
• National and regional health plans
• Integrated delivery networks
• Academic and community medical centers
• Physician groups
• Accountable care organizations

Prior to rejoining Optum, Mylynn served as the State Health Officer for North Dakota, where she led the state department of health during the COVID-19 public health emergency, established health policy, and developed and implemented strategic priorities.
Mylynn earned a BSN from Case Western Reserve University, and an MBA and Master of Science in Information Management (MSIM) from Arizona State University. Mylynn has also been a national speaker and instructor on population health, health policy and leadership.

Director, MIT Sloan Health Systems Initiative

Anne Quaadgras

Anne Quaadgras is the Director of the MIT Sloan Health Systems Initiative and a Senior Lecturer at MIT Sloan.

Her work focuses on health systems transformation, and the role of information technology in supporting that change.

Prior to her doctoral work, Anne was a management consultant for fifteen years, specializing in improving decision-making and investment processes in the chemical, pharmaceutical, and financial services industries.

She holds a Bachelor’s and Master’s degree in chemical engineering from MIT. Anne earned her doctorate in information systems at Boston University, where her dissertation research explored how globally distributed groups of experts recognize and respond to operational problems.

Google Research and Duke University

Katherine Heller

Katherine is an Assistant Professor at Duke University, in the Department of Statistical Science and at the Center for Cognitive Neuroscience. Prior to joining Duke she was an NSF Postdoctoral Fellow, in the Computational Cognitive Science group at MIT, and an EPSRC Postdoctoral Fellow at the University of Cambridge. Her Ph.D. is from the Gatsby Unit, where her advisor was Zoubin Ghahramani.

Katherine's research interests lie in the fields of machine learning and Bayesian statistics. Specifically, she develops new methods and models to discover latent structure in data, including cluster structure, using Bayesian nonparametrics, hierarchical Bayes, techniques for Bayesian model comparison, and other Bayesian statistical methods.

She applies these methods to problems in the brain and cognitive sciences, where she strives to model human behavior, including human categorization and human social interactions.

CEO/Founder, Women At The Table

Caitlin Kraft-Buchman

Caitlin Kraft-Buchman is CEO/Founder of Women at the Table, a growing global CSO based in Geneva, Switzerland – and the first organization to focus on systems change by helping feminists gain influence in sectors that have key structural impact: economy, democracy and governance, technology, and sustainability. A serial coalition builder focused on impact, she is the founder of International Gender Champions (IGC) a leadership network of female & male decision-makers that breaks down gender barriers for system change. After four years it includes hubs in Geneva, New York, Vienna, Nairobi, The Hague, and most recently Paris, and counts 300+ Champion heads of organizations including the Secretary General of the UN, heads of the UNHCR, ICRC, IOM, IFRC, WTO, ILO, WHO, WIPO, ISO, ITU, Ambassadors, and Civil Society. As IGC Board Member she is also responsible for IGC’s Trade Impact Group (Buenos Aires Declaration on Trade and Women’s Economic Empowerment, 2017); Disarmament Impact Group (nominated for Arms Control Person/s of the Year, 2018); Standards Impact Group (Gender Responsive Standards Declaration, 2019); International Justice Impact Group (The Hague Principles on Sexual Violence, 2019).

Caitlin also founded and co-leads the new < A+ > Alliance for Inclusive Algorithms with Ciudadania Inteligente, a global coalition of technologists, activists and academics who focus on affirmative action for algorithms and creating gender equality, so that machine learning does not embed an already biased system into our future.


Elke A. Rundensteiner

BS Computer Science J.W. Goethe University, Frankfurt, Germany
MS Computer Science Computer Science, Florida State University, Tallahassee, Florida
PhD Computer Science University of California, Irvine, California
As founding Director of the interdisciplinary Data Science program here at WPI, I take great pleasure in doing all in my power to support the Data Science community in all its facets from research collaborations, new educational initiatives to our innovative Graduate Qualifying projects at the graduate level.

Having served as primary advisor and mentor of over 35 PhD students who have secured successful professional careers in computing, I'm proud of all the great accomplishments of students I have had the opportunity to collaborate with. With an h-index of 55, I have authored well over 400 publications, numerous patents, and software systems released to public domain. My research work, widely cited, has been supported by government agencies including NSF, NIH, DOE, FDA, and DARPA, and by industry including HP, IBM, Verizon Labs, GTE, NEC, AMADEUS, Charles River Analytics, and by labs such as MITRE Corporation. I've enjoyed holding leadership positions in the big data field, including having served as Associate Editor of prestigious journals including IEEE Transactions on Data and Knowledge Engineering and VLDB Journal and as area chair on premiere professional big data conferences, including ACM SIGMOD, VLDB, IEEE ICDE, and others.

My research focuses on how to make use of data and information in an effective manner, towards achieving goals in business, scientific discovery, and digital health. With the inter-connectivity of the internet, the availability of computing power, and big data everywhere, access to the right piece of information at the right moment, possibly fused together from numerous information sources, remains one of the most critical capabilities that can set you apart from others. Together with undergraduates, graduate students, post-docs, and other faculty, I strive to develop big data, machine learning and data visualization technologies to discover and explore important nuggets and patterns in massive data sets in real-time in applications from fraud detection, digital health, emergency management, business intelligence, to event analytics.

I love every moment working with students and colleagues at WPI and in industry on cutting-edge data science research and project activities. At the undergraduate level, I work with students both on MQP and IQP projects focused on computer science and data science research challenges often in collaboration with companies and other organizations.

VP of Data Science, ConcertAI

Judith Mueller

“We are pleased to welcome Judith to the ConcertAI leadership team and know that her deep knowledge and leadership in data science will accelerate our innovations in Precision Oncology and Patient Solutions across an array of new AI technology product initiatives,” said Jeff Elton, PhD and CEO of ConcertAI.

Judith was recently at GNS Healthcare as Senior Director of Research and Data Science where she led a number of data science teams that applied machine learning methods to complex data sets in healthcare and life sciences, for oncology and other therapeutic areas. Prior to GNS Healthcare, Judith led research in computational macromolecular modeling in the life sciences industry and developed methodologies for technology assessment and parametric yield improvements in the high-tech industry. Judith obtained her PhD from McGill University, Montreal, in physics, and MS in physics from the RWTH in Aachen, Germany.

“I am a passionate computational physicist who thrives on challenges,” said Judith. “I’m excited to be joining the healthcare industry’s leader for AI-powered real-world evidence solutions and look forward to working closely with our partners and customers to advance even more exciting and high–value AI technologies.”

Assistant Professor, Department of Radiology, Emory University School of Medicine

Judy Wawira Gichoya, MD, MS

Judy Wawira Gichoya, MD, MS, is Assistant Professor in the Department of Radiology and Imaging Sciences at Emory University School of Medicine. An interventional radiologist, Dr. Gichoya specializes in ??? interventional radiology procedures.
Dr. Gichoya is a member of the Cancer Prevention and Control Research Program at Winship Cancer Institute. She holds professional memberships with Radiological Society of North America, American College of Radiology, Society of Interventional Radiology, Society of Imaging Informatics in Medicine and American Medical Informatics Association.
Dr. Gichoya earned her Medical Degree from Moi University in Kenya. She completed her medical internship at Kiambu District Hospital. She earned a Masters of Science in Health Informatics from Indiana University Purdue University in Indianapolis, Indiana. In addition, she completed post-doctoral training in informatics at Regenstrief Institute in Indianapolis, Indiana, and a residency in diagnostic radiology at Indiana University. Prior to arriving at Emory, she completed a fellowship in interventional radiology at Oregon Health Sciences University in Portland, Oregon.

AI in Healthcare Summit
Programme Highlights

STEMM MIT CSAIL AI in Healthcare is a highly curated programme, covering the most relevant topics of AI in healthcare, including the ways in which AI is being used during the current pandemic.

Points of discussion will include AI and ML enabled Robotics, Diagnostics and Treatments, Data Gathering and Management, Pharmaceuticals, Ethics, and Clinical Research Developments to help face the Challenges of Current and Future Healthcare Systems.









Apply to Participate

The Summit program includes:

  • Keynote Speeches from Top AI Experts
  • Panel Discussions and Roundtables with Leaders from Academia and Industry
  • Poster Sessions (>1000 Presentations)
  • Research Oral Talks
  • Researchers Elevator Pitch
  • Online Expo
  • Curated Networking Platform




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