Profile

Research interests

Stanislav leads a team focused on machine learning, automation, and data analysis in protein engineering–a fascinating area of research at the interface of biochemistry, biophysics, computer science, and mathematics. The team’s goal is to delve into data–such as experimental measurements, protein sequences and alignments, or computer simulations–to gain insights into the underlying biophysical mechanisms and create reliable and interpretable tools for the design of improved protein variants. Those enhanced variants can then be used in numerous applications, from healthcare to the food industry and bio-degradation. Stanislav’s background is in nonlinear systems analysis of various processes in biology, physics, and economics: modelling, optimisation, and parameter estimation, theoretically and practically.

Education

2013 Ph.D. in Differential Equations, Dynamical Systems, and Optimal Control, Lomonosov Moscow State University, Russia
2011 MA in Economics, New Economic School, Moscow, Russia
2009 MSc. in Applied Mathematics and Informatics, Lomonosov Moscow State University, Russia

Teaching

Artificial Intelligence in Biology, Chemistry, and Bioengineering
Molecular biotechnology
Seminar of Loschmidt Laboratories
Hands-on Computational Design Course

Scientific output

16 research articles
H-index 6
Calfitter software tool for protein thermal denaturation data analysis

Awards

2018 Marie Skłodowska-Curie Actions @ MUNI Fellowship, Masaryk University, Brno
2011 Don Patinkin Prize for excellence in study, teaching, and research, New Economic School, Moscow
2011 Best Teaching Assistant Award, New Economic School, Moscow
2010 Peter Aven’s scholarship, New Economic School, Moscow
2009 State Support of the Leading Scientific Schools, Lomonosov Moscow State University
2008 Moscow Mayor’s Office Fellowship, Lomonosov Moscow State University

Links

Linkedln
ResearchGate
ORCID
Personal webpage