Ryan Holcomb
Dr. Ryan E. Holcomb is employed as a Principal Scientist for Legacy BioDesign LLC, a contract research organization specializing in the formulation of therapeutic proteins and peptides.
Brent Kendrick
Brent Kendrick is founder and owner of First Principles Biopharma, LLC, specializing in biopharmaceutical data sciences, data analysis automation, and consulting in formulation/analytical development/product characterization.
This course is designed to help you learn and apply advanced data tools for IIoT and smart manufacturing. The curriculum ranges from foundational concepts to in-depth, hands-on activities using production data, and covers a variety of cutting-edge approaches such as deep reinforcement learning control, encryption for data outsourcing, and predictive data analytics algorithms.
This comprehensive course provides up-to-date assessments, case studies, and important knowledge on issues that affect you and your organization — response organizations, cyber security, supply chain, crisis leadership, artificial intelligence, crisis communications, news media, social media, and all levels of government response — from the experts involved with these efforts. We also examine strategies for program, job, and career improvement. You will have the opportunity to interact with our lecturers and with your peers from industry, academia, and government. Participants can also practice what is learned: the course concludes with a highly interactive crisis simulation in which participants take active roles in a multiple event crisis, including a realistic news media briefing.
Tim Kraska
Tim Kraska is an Associate Professor of Electrical Engineering and Computer Science in MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), where he co-leads the Data Systems Group. He is also the Founding Co-Director of MIT Data System and AI Lab (DSAIL).
Zhengzhen Tan is a Lecturer in MIT’s School of Architecture and Planning, Executive Director of the MIT Sustainable Urbanization Lab, and Director of the China Future City Program. Her research and teaching is focused on sustainable urban development, digital innovation, and entrepreneurship. She is the editor of “Towards Urban Vibrancy: Patterns and Practices of Asia’s New Cities” (MIT SA+P Press, 2020), and the author of the digital cities chapter in this book. Prior to joining MIT, she worked as an urban planner and urban designer with extensive practice in both the public and private sectors in Shanghai, Singapore, London, and Vancouver.
Professor Siqi Zheng is the STL Champion Professor of Urban and Real Estate Sustainability at MIT and Faculty Director of both the MIT Center for Real Estate and MIT Sustainable Urbanization Lab. Her research focuses on urban and environmental economics, urban development, and real estate markets, with a special focus on China. She is widely published in both English and Chinese language journals and serves as Associated Editor of Journal of Economic Surveys, an editorial board member of Journal of Housing Economics and International Real Estate Review, and the Vice General Secretary of the Global Chinese Real Estate Congress. Prior to joining MIT, she was a professor and director of Hang Lung Center for Real Estate at Tsinghua University, China.
Delve into the economic fundamentals and business strategies of sustainable real estate development, management, and investment. In this highly interactive course, you will join real estate professionals from around the world to develop the analytical skills and frameworks you need to approach sustainability as a real estate business strategy.
Julian Shun
Julian Shun is an Associate Professor of Electrical Engineering and Computer Science at MIT and a lead investigator in MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). His research focuses on the theory and practice of parallel algorithms and programming, with particular emphasis on designing algorithms and frameworks for large-scale graph processing and spatial data analysis. He also studies parallel algorithms for text analytics, concurrent data structures, and methods for deterministic parallelism. Prior to joining MIT, he was a postdoctoral Miller Research Fellow at UC Berkeley. His honors include the NSF CAREER award, DOE Early Career Award, ACM Doctoral Dissertation Award, the CMU School of Computer Science Doctoral Dissertation Award, Google Faculty Research Award, Google Research Scholar Award, SoE Ruth and Joel Spira Award for Excellence in Teaching, Facebook Graduate Fellowship, and best paper awards at PLDI, SPAA, CGO, and DCC.
Graph analytics provides a valuable tool for modeling complex relationships and analyzing information. In this course, designed for technical professionals who work with large quantities of data, you will enhance your ability to extract useful insights from large and structured data sets to inform business decisions, accelerate scientific discoveries, increase business revenue, improve quality of service, detect fraudulent behavior, and/or defend against security threats.