279 Campus Drive
Stanford, CA 94305
Information Session
- Thursday, October 10th from 4:30-6:00 PM | Munzer Auditorium (Beckman Center)
- Open to Postdocs, Graduate and Undergraduate students
D. E. Shaw Research (DESRES), based in New York City, develops and uses advanced computational technologies to understand the behavior of biologically and pharmaceutically significant molecules at an atomic level of detail, and to design precisely targeted, highly selective drugs for the treatment of various diseases. Among its core technologies is Anton, a proprietary special-purpose supercomputer that DESRES designed and constructed to vastly accelerate the process of molecular dynamics simulation. DESRES uses Anton machines and high-speed commodity hardware, together with machine learning methods and other computational techniques, in both internal and collaborative drug discovery programs.
Join us for an overview of our work and current openings.
Appetizers will be served during the light networking reception! (Please Note: While we are not permitted to bring food inside the auditorium, you are welcome to enjoy it after the talk outside the auditorium/in the hallway.)
About the Speakers
Henri Palacci Henri earned a Ph.D. in biophysics and machine learning from Columbia University and an M.S. in applied mathematics and statistics from École Polytechnique in France. At Columbia, Henri focused on the application of non-equilibrium statistical physics to statistical learning and systems such as self-assembling enzyme structures and motor proteins. More recently, Henri has worked at Anagenex, a drug discovery startup applying machine learning to DNA-encoded libraries, and at Flagship Labs 85, a startup working on lipid nanoparticle optimization for RNA delivery.
Milena Mathew Milena graduated with a B.S. in Electrical Engineering and Computer Science from the University of California at Berkeley. During her undergraduate research, Milena worked on modeling color centers using density functional theory to identify new qubit candidates and on developing control software for photonics experiments. Milena also worked as part of the Quantum AI team at Google, modeling frequency dependence of single qubit calibration parameters to speed up recalibration of frequency tunable transmons.