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October 30, 2020. Online,
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10 Talks
1 Day
3 Hours of content
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About the Event

The current COVID pandemic highlighted the challenge of finding effective cures in response to new pathogens. Indeed, traditional approaches to drug discovery can be prohibitively slow when little is known about the disease and the relevant experimental data are still scarce. AI-driven discovery  offers a promising way to accelerate the process. These methods can quickly analyze millions of molecules, selecting a few leading candidates that can be subsequently studied in depth using more traditional experimental techniques. This conference was present cutting edge AI approaches in this area developed by MIT researchers and their collaborators during pandemics. 
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Featured Speakers

Noubar Afeyan

Founder & CEO at Flagship Pioneering
Noubar Afeyan has dedicated his career to improving the human condition by systematically creating science-based innovations that serve as the foundation for startup companies. At Flagship Pioneering, which he founded in 2000, Noubar has created an enterprise where entrepreneurially minded scientists invent seemingly unreasonable solutions to challenges facing human health and sustainability. Flagship has fostered the development of more than 100 scientific ventures resulting in $80 billion in aggregate value, thousands of patents and patent applications, and more than 50 drugs in clinical development.

Noubar entered biotechnology during its emergence as an academic field and industry, completing his doctoral work in biochemical engineering at MIT in 1987. He has written numerous scientific publications and is the inventor of over 100 patents. He is a lecturer at Harvard Business School; and from 2000 to 2016 was a senior lecturer at MIT’s Sloan School of Management. He teaches and speaks around the world on topics ranging from entrepreneurship, innovation, and economic development to biological engineering, new medicines, and renewable energy.

Noubar was born in Beirut to Armenian parents in 1962, did his undergraduate work at McGill University in Montreal, and completed his Ph.D. in biochemical engineering at MIT in 1987.

Bonnie Berger

Head of Computation and Biology at MIT CSAIL
Bonnie Berger is the Simons Professor of Mathematics at MIT, holds a joint appointment in Electrical Engineering and Computer Science, and serves as head of Computation and Biology group at MIT's Computer Science and AI Lab. Her recent work focuses on designing algorithms to gain biological insights from advances in automated data collection and the subsequent large data sets drawn from them. She works on a diverse set of problems, including Compressive Genomics, Network Inference, Structural Bioinformatics, Genomic Privacy, and Medical Genomics. Additionally, she collaborates closely with biologists in order to design experiments to maximally leverage the power of computation for biological explorations.

After beginning her career working in algorithms at MIT, she was one of the pioneer researchers in the area of computational molecular biology and, together with the many students she has mentored, has been instrumental in defining the field. Professor Berger is an elected fellow of the American Academy of Arts and Sciences, Association for Computing Machinery, International Society for Computational Biology (ISCB), American Institute of Medical and Biological Engineering, and American Mathematical Society.

Rafael Gomez-Bombarelli

Professor at MIT
Rafael Gomez-Bombarelli joined the MIT faculty in January 2018. He received a B.S., M.S., and Ph.D. in Chemistry from Universidad de Salamanca in Spain, followed by postdoctoral work at Heriot-Watt University and Harvard University after which he was a senior researcher at Kyulux NA applying Harvard-licensed technology to create real-life commercial organic light-emitting diode (OLED) products.

Dr. Gomez-Bombarelli’s research trajectory has evolved from experimental mechanistic studies of organic molecules with emphasis on environmental toxicity to computer-driven design of molecular materials. By combining first-principles simulation with machine learning on theoretical and experimental datasets he aims to accelerate the discovery cycle of novel practical materials.

Through his research at MIT he plans to address the role of molecular transformation in materials discovery, in areas such as catalyst design, the environmentally-minded development of novel and replacement chemicals, and designing for stability in advanced materials.

Rafa's work has been featured in journals such as Technology Review and the Wall Street Journal. He was also co-founder of Calculario, a materials discovery company that leverages quantum chemistry and machine learning to target advanced materials in a range of high-value markets.
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Areas of Focus: 3-D Structure Modeling for Chemical and Biological Applications, Molecular Property Prediction, De Novo Molecular Design and Molecular Optimization, Target Identification, Antiviral and Vaccine Design and Modeling Virus Biology.

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Jian Tang
Professor at HEC Montreal
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Head of Computation and Biology at MIT CSAIL
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Marinka Zitnik
Assistant Professor of Biomedical Informatics at Harvard Medical School
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Marinka Zitnik: AI Cures Drug Discovery Conference

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