Michael Samoilov, August 2010

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Michael Samoilov from UC Berkeley will be visiting Caltech on 2-6 August. This page contains his schedule for the week.

Agenda

Monday

  • Arrive 9:30-10
  • 10-12: meet with Richard; plans for the week
  • 12-1: lunch with Richard
  • 1-2: CDS seminar
  • 2-4: Richard + biomodeling students
  • 7:00: Dinner with Richard and RuthAnne (pick up at Ath)

Tuesday

  • 10:00-11:00: Dionysios Barmpoutis
  • 1:00-2:00: Richard + students
  • 2:00-3:30: Niles, Richard, Michael (meet in Niles office)
  • 3:30-5:00: Richard

Wednesday

  • 9-11: Elliot Meyerowitz (computation group meeting; 156 Church)
  • 11-12: Erik Winfree (204B Moore)
  • 1-3 pm: Richard + students
  • 3 pm: CDS tea
  • 4 -5 pm: Vanessa Jonsson

Thursday

  • 1-3 pm: Richard + students

Friday

  • 11-12: Rob Phillips, 159 Broad
  • 12-1:30: (Murray group meeting)
  • 1:30-3:30: Richard + students
  • ~6:30 pm: depart for Airport

Bio

Michael Samoilov is a Research Staff Member at the California Institute for Quantitative Biosciences (QB3) at UC Berkeley. Dr. Samoilov earned his Bachelor’s degree with Honor in Physics and Mathematics from Caltech (1991). He then went on to do graduate work at Stanford University, beginning with high-energy physics and astrophysics, for which he was awarded an M.S. in Physics (1994), and continuing at the biophysics program where he received a Ph.D. in Biophysics (1997). After spending several years developing stochastic trading strategies for leading finance companies and running a Webby Award-winning multimedia start-up, Michael was drawn back to science by the emergence of novel biological systems engineering and analysis paradigms driven by the advances in single-molecule, single-cell and bulk high-throughput experimental methods. His most recent work includes investigating the role of discrete and stochastic dynamics in biological circuits, developing biochemically - and biophysically-driven methods for structural identification and functional analysis of biological networks, as well as studying information and signal processing characteristics of biomolecular reaction systems.