Bio ML seminar series
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Bio ML seminar series

Biology is moving faster than ever, and we’re making rapid progress in modeling useful biological systems in silico.

ML is poised to have a huge impact on the entire field in the next decade — and we are running a seminar series (sponsored by Pillar VC) with researchers and leaders leveraging ML to stay at the cutting edge of biology: they’re working to change healthcare through vaccine development, antibody design, single cell analysis, and all sorts of protein engineering. Come join us to see how you can make GPUs go brrr in the service of designing life-saving therapeutics instead of just making them paint cartoons for you.

Event List

Spring 2024

Jan 29 — Sam Rodriques, founder of Future House | recording

Sam Rodriques is a researcher and entrepreneur with a focus on biotechnology. He founded the Applied Biotechnology Laboratory at the Francis Crick Institute in 2021, aiming to integrate bioengineering and business for medical and biological advancements. Sam's notable inventions include a new nano-fabrication method, a technique for neural activity sensing via bloodstream probes, and advancements in RNA sequencing. He's also developed a method for protein sequencing and a technique for mapping brain connections. In 2023, Sam established Future House in San Francisco, a project dedicated to creating an AI Scientist.

Feb 12 — Dave Mathus and Keith Cheveralls, Arcadia Science

Dave and Keith will discuss Arcadia’s recently released nematode embryogenesis classifier and walk attendees through their central biological research question, the time-course imaging data, the intricacies of the classifier, and the greatest challenges they encountered in the project. This will be an interactive session where feedback and discussion are highly encouraged.

Feb 15 — BioML Lecture from Aakarsh Vermani | recording
Feb 26 — Thomas Kalil, CIO of Schmidt Futures

Thomas Kalil is the Chief Innovation Officer at Shmidt Futures, where he leads initiatives to harness technology for societal challenges, improve science policy, and identify and pursue 21st century moonshots.

Prior to Schmidt Futures, Tom served in the White House for two Presidents (Obama and Clinton), helping to design and launch national science and technology initiatives in areas such as nanotechnology, the BRAIN initiative, data science, materials by design, robotics, commercial space, high-speed networks, access to capital for startups, high-skill immigration, STEM education, learning technology, startup ecosystems, and the federal use of incentive prizes.

Mar 4 — Rhiju Das, Stanford/HHMI investigator | recording

Join us for the 9th seminar from the BioML group in Machine Learning at Berkeley. We're hosting Rhiju Das, Professor of Biochemistry at Stanford University School of Medicine, and are really excited for his talk on RNA Modeling.

After training in particle physics and cosmology at Harvard, Cambridge, University College London, and Stanford, Dr. Das did postdoctoral research in computational protein folding at the University of Washington with David Baker. On returning to Stanford, Dr. Das set up his lab to focus on computer modeling and design of RNA molecules, which underlie important molecular machines in biology and medicine. As a core part of this research, Dr. Das leads Eterna, an open science platform that crowdsources intractable RNA design problems to 250,000 players of an online videogame and provides scoring feedback based on actual wet-lab experiments.

Dr. Das has been recognized by the Burroughs-Wellcome Career Award at the Interface of Science, the Stanford Medicine Endowed Faculty Scholar award, and selection as an investigator of the Howard Hughes Medical Institute

Mar 18 — Stephan Eismann, ML lead at Atomic AI

Stephan leads the ML Team at Atomic AI. Prior to joining Atomic, he did his PhD in the AI Laboratory at Stanford University where his research focused on the development of novel ML algorithms for problems in structural biology. Originally from Germany, he studied physics in Heidelberg and London before coming to the US.

April 15 — Jacob Ulirsch — Illumina AI. signups soon!
April 22 — Alex Telford — Convoke Bio. signups soon!

Fall 2023

Oct 2 — Peyton Greenside, co-founder BigHat Biosciences

A pioneer of deep learning applied to life science problems, Peyton has developed computational, statistical, and AI/ML techniques to model, understand, and optimize biological sequences in academia and industry. Peyton was an inaugural Schmidt Science Fellow, a computational biologist at the Broad Institute, a scientific founder of Valis, and holds a PhD from Stanford University (Accel Innovation Scholar), an MPhil in Computational Biology from Cambridge University (Herchel Smith Scholar), and a BA in Applied Math from Harvard.

She founded BigHat Biosciences in 2019, enabling drug developers to create antibodies and complex therapeutics much faster than usually possible.

Oct 9 — Soham Sankaran, founder PopVax

Soham Sankaran is the founder of PopVax, an Indian biotechnology company based in Hyderabad building a novel thermostable, low-cost, and safe second-generation mRNA platform for rationally-designed broadly-protective multi-epitope vaccines. Soham dropped out of the PhD program in the Computer Science department at Cornell, where his research was focused on robotics and distributed systems. He previously did sociology research at the Human Nature Lab, part of the Yale Institute for Network Science.

Oct 23 — Elliot Hershberg, writer/investor at The Century of Biology

Elliot Hershberg is a Scientist, Writer, and Investor dedicated to accelerating The Century of Biology. His diverse experiences in biotechnology include designing cancer vaccines, developing computational tools for spatial genomics technologies, and working as a software engineer on a modern genome browser. Elliot's mission is to push the boundaries of biological advancements.

Berkeley-ML-CB-talk-2023.pdf20879.8KB
Nov 6 — Simon Kohl, founder Latent Labs

Simon is the founder of Latent Labs, a company developing generative foundation models for all molecules of life. Latent’s mission is to make synthetic biology programmable. The team is currently based in London and joined by heavy hitters from DeepMind, University of Oxford and Cambridge.

Simon has led DeepMind’s protein design team and helped set up DeepMind’s wet lab at the Francis Crick Institute in London. Before that, he was a member of the AlphaFold2 team, where he contributed to the core deep learning algorithm, including developing the uncertainty estimate that is now widely known as pLDDT.

Dec 5 — Brian Hie, supervisor of the Laboratory of Evolutionary Design

Brian's lab conducts research at the intersection of biology and machine learning. Before starting his own lab, Brian did his PhD at MIT, his postdoc at Stanford Medicine, and was a visiting researcher at Meta AI where he worked on designing a programming language for protein design, along with ESM-2 and ESMFold.

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