W2. A Crash Course in AI: 0-60 in Three

TUESDAY, October 6 | 8:30 - 11:30 AM

ABOUT THIS WORKSHOP:

Have you ever been curious to apply machine learning to large amounts of data but were not sure of the concepts to use? Have you ever wondered how to get started on AI? Well, you have come to the right place! This workshop will help you learn AI like never before (our instructors guarantee it!). The workshop is a crash course on AI where you will learn the fundamentals and applications of AI/ML in Pharma. Come join us, learn, and network!

WORKSHOP AGENDA:

8:30 am Introduction & Chairperson Remarks

Cindy Crowninshield, RDN, LDN, HHC, Executive Event Director, Cambridge Healthtech Institute

Bino John, PhD, Associate Director, Data Science - Clinical Pharmacology & Safety Sciences, AstraZeneca R&D

8:45 Introduction and Fundamentals of AI: From KNN to DNN

Bino John, PhD, Associate Director, Data Science - Clinical Pharmacology & Safety Sciences, AstraZeneca R&D

9:45 Coffee Break

10:00 A Deep Dive into Deep Learning

Gustavo Arango, PhD, Senior Data Scientist - Oncology Bioinformatics, AstraZeneca

10:45 Making Sense of Your Data Using ML

John Van Hemert, PhD, Research Scientist, Bioinformatics, Corteva Agri Science, A Dow-Dupont Division

11:30 Workshop Ends

INSTRUCTORS:

Bino John, PhD, Associate Director, Data Science - Clinical Pharmacology & Safety Sciences, AstraZeneca R&D

Bino John, PhD, currently leads a variety of Artificial Intelligence (AI) Initiatives at AstraZeneca (AZ). As an Associate Director at AZ, he is leveraging Deep learning and other advanced AI approaches to accelerate Drug development. Before joining AZ in 2018, Bino led a variety of computational biology initiatives and teams at Dow and then Dow-DuPont. In those roles, his efforts included enabling machine learning/AI and integrative big-data informatics capabilities for genomics research for the Agricultural Sector. He earned an Integrated Master’s degree in Chemistry from the Indian Institute of Technology (Mumbai) in 2000 and subsequently received his PhD from The Rockefeller University in Biomedical Sciences in 2003. His thesis research in computational structural biology with Dr. Andrej Sali was followed by postdoctoral studies in computational genomics with Dr. Chris Sander at the Memorial Sloan-Kettering Cancer Centre. In 2005, Bino joined the University of Pittsburgh as a faculty, where he focused on using high-throughput methods for cancer biomarker discovery, resulting in the discovery of novel molecules and molecular pathways.

Gustavo Arango, PhD, Senior Data Scientist - Oncology Bioinformatics, AstraZeneca

Gustavo Arango is a PhD in computer science, Masters and Undergrad in Electrical Engineering who has been working in diverse areas through his scientific career, including: digital signal processing, web development, machine learning, bioinformatics, natural language processing and deep learning. Currently, he is working in the oncology bioinformatics team at AstraZeneca where he is applying deep neural networks to learn patterns from genomics data. Prior, he received his PhD (2019) from the department of Computer Science at Virginia Tech, where he developed bioinformatics tools to process metagenomics data. Particularly, by using machine learning and deep learning to leverage accurate predictions of antibiotic resistance genes from second and third generation sequencing technologies.

John Van Hemert, PhD, Research Scientist, Bioinformatics, Corteva Agri Science, A Dow-Dupont Division

Formally trained in Computational Biology, Multivariate Statistics, and Machine Learning, John worked in Discovery R&D at DuPont Pioneer since 2011. Projects are balanced between developing computational methods that enrich the discovery pipeline and characterize its products – some of which appear in scientific and IP literature. He led statisticians, computational biologists, and data scientists around the world, working on everything from experiment design, to drone imagery analysis, to molecular biotechnology development. Before that, he was a Staff Scientist at Iowa State University in the Crop Genome Informatics Laboratory where he led modernization of the Plant Expression DataBase (PlExDB). Prior, John received his PhD (2010) from the Electrical and Computer Engineering Department at Iowa State University in Bioinformatics and Computational Biology, where he worked on Systems Biology of the Grapevine for an international consortium of researchers and published several papers in biological network analysis and mining. He also holds Bachelors’ degrees (2006) from the University of Northern Iowa, by the Computer Science Department and Business College.

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