How can we use modern algorithms to create new ideas and opportunities for scientific and industrial research and development? Leading scientists present algorithms from their work. Industry leaders find new use cases.
Monday 27th November 2023
Monday 27th November 2023 (Afternoon)
Professor George Church
Professor Church and their lab have published extensively on synthetic neurobiology and AI-LLM design of proteins, gene therapies and organs. They have co-founded 48 companies, where most of the recent ones have core ML/ML (Machine Learning+ Multiplex Libraries), e.g. DynoTx, ShapeTx, Jura, Patch, Nabla, ManifoldBio. Professor Church was one of the six instigators of Obama's BRAIN Initiative—and directed one of the 3 teams in the $100M IARPA MICrONS project to develop new technologies to obtain connectomes and integrate them with brain activity map data.
Professor Mina Konakovic Lukovic
Professor Lukovic leads the algorithmic design group at CSAIL, MIT. Their research focuses on computer graphics, computational fabrication, 3D geometry processing and machine learning, including architectural geometry and design of smart materials. Before this position, they held a prestigious Schmidt Science Postdoctoral Fellow at MIT CSAIL working in the Computational Fabrication Group.
Professor Robert Glushko
Professor Glushko, of the Cognitive Science Program at UC Berkeley, is a distinguished researcher and business leader. Their research in academia and industry (including Bell Labs) and directorship of several companies helped establish the backbone of business and commerce on the internet. In addition, they have endowed a number of professorial, doctoral and undergraduate prizes within the field of cognitive science and have written several books, including Document Engineering and The Discipline of Organizing.
Professor Dan V. Nicolau Jr
Professor Nicolau is a mathematician, computer scientist and physician, with leading research on algorithms, biological computation and neuroimmunology. They are also a serial entrepreneur, with their most recent venture into the automated statistical management of large-scale clinical trials.
Professor Hidenori Tanaka
Professor Tanaka is a Group Leader in the NTT Research program at Harvard University, where they study the physics of natural and artificial intelligence. They use advanced algorithms to extract and understand computational mechanisms from deep neural networks.
Dr Kelly Miller
Dr Miller is a senior lecturer in applied physics at Harvard. She completed her Ph.D. in Applied Physics from Harvard in 2015. Her research investigates the use of modern AI techniques to build advanced physics tutors. At Harvard, Kelly teaches interactive, project-based courses in both physics and engineering. She is also a co-founder of Perusall, a collaborative reading platform designed to help get students prepared for class.
Dr James Whittington
Dr Whittington is an artificial intelligence researcher and computational neuroscientist and has introduced many of the leading frameworks in biologically inspired AI. They have recently become the chief technical adviser at Zyphra, a start up that develops technologies based on their work on local computing algorithms.
Dr Mayank Agrawal
Mayank Agrawal is co-founder and CEO of Roundtable, a Y-Combinator backed company providing AI infrastructure for user and market researchers. Previously, Mayank completed his PhD in Psychology and Neuroscience at Princeton University where he published in Science, PNAS and Psychological Review
Dr Shahar Bracha
Dr Bracha is a world expert on algorithms in synthetic biology, where they are developing approaches to find new molecular tools from natural environments as well as learning from nature about how to engineer new ones, with applications in neuroscience, brain recording, ecology and carbon capture. They also advise at Epeius Pharma, a start-up based on their PhD research.
Dr Dan Roberts
Dr Roberts is an AI Fellow at Sequoia Capital and a Research Affiliate at the Center for Theoretical Physics at MIT, where they also research ways in which the tools and perspectives from theoretical physics can be applied to artificial intelligence. Beyond this, Dr Roberts is a serial entrepreneur and co-authored a book on of The Principles of Deep Learning Theory.
Dr Greg Kestin
Dr Kestin is currently the Associate Director of Science Education and a Lecturer on Physics. Over his career, he has conducted research in nuclear physics, particle physics, fusion energy, gravitational wave physics and science education. As a Digital Producer at NOVA | PBS he created award-winning media, from documentaries to educational interactives to an original video series, "What the Physics?!"
Dr Clara-Lea Bonzel
Dr Bonzel is a data Scientist and technical manager at Harvard Medical School, expert in analyzing large-scale electronic health records data. They advise on machine learning phenotyping algorithms at the US department of Veterans Affairs, Boston Children's Hospital and Mass Gen.
Dr Momchil Tomov
Dr Tomov is a computational neuroscientist that wants to build themselves out of the discovery loop. Using advanced theory and AI algorithms they are working on creating an "algorithmic neuroscientist" that can automatically extract meaningful theories from neural data. In addition they are a senior research scientist at Motional, working on planning algorithms for self-driving cars.
Felix Sosa
Felix is an AI researcher and entrepreneur, completing his PhD in computational cognitive science at Harvard and the Center for Brains, Minds and Machines (MIT). They work on formal analysis of learning algorithms based on program synthesis and programming languages and hold visiting researcher status at Google DeepMind.
Leroy Sibanda
Leroy is a founder in stealth mode and graduate student at MIT, working on complex systems design and analysis in AI, robotics and electrical engineering.
Jeremy Dohmann
Jeremy is a research scientist at Databricks and was formerly a leading member of MosaicML. They manage a team of researchers building out LLM-based database technologies and regularly publish guides on training and integrating modern ML.
Taylor Beck
Taylor Beck is a writer, a teacher and a former neuroscience researcher. They hold a BA from Princeton in Neuroscience, an MS from MIT and an MA from NYU. Their journalism and essays have appeared in The Atlantic, Scientific American and the Los Angeles Review of Books, among other publications.
