Dr. Gennady Roshchupkin
Computational Population Biology group leader
Erasmus MC Medical Center

Biography

Gennady is leading Computational Population Biology group at the one of the largest medical hospital in Europe, Erasmus MC Medical Center. His research focused on developing and application of methods for the integrative analysis of large-scale biological, epidemiological and clinical data.

Gennady has a broad background in statistics, computer science, machine learning, deep learning, medical image analysis and genomics.

Since 2019 Gennady is chairing Machine Learning working group in The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium

Areas of expertise

  • Artificial Intellegence
  • Genomics
  • Quantitive Traits Analysis
  • Explainable AI
  • Federated Learning
  • Omics
  • Data Science

Education

Experience

Group Leader
Erasmus MC Medical Center, Rotterdam, the Netherlands
Since March 2020
Departments of Epidemiology, Radiology and Nuclear Medicine
leading Computational Population Biology
Postdoctoral Researcher
Erasmus MC Medical Center, Rotterdam, the Netherlands
March 2018 — March 2020
Departments of Epidemiology, Radiology and Nuclear Medicine
Senior Reseacher Engineer
Special Systems Engineering Center, Moscow, Russia
March 2013 — January 2014
Research and development engineer in the field of network security and mathematical modelling.
Participated in several projects, about machine learning and algorithm optimization for fast big data processing.
Research Engineer
Special Systems Engineering Center, Moscow, Russia
August 2011 — March 2013
Reseacher
Moscow State University, Moscow, Russia
September 2009 — February 2011
Department of Lunar and Planetary Research, Sternberg Astronomical Institute
Work in the project on the analysis of the satellite images.
Development of software for the analysis of a large number of images
Develop an algorithm to automatically search for specific patterns on the image and fast computation
Optimization of the theoretical model to estimate the age of rocks on the Moon
Reseacher
Moscow State University, Moscow, Russia
September 2008 — May 2009
Laboratory of Maidanak Observatory, Sternberg Astronomical Institute.
Work on construction of an accretion disks’ model of active galactic nuclei to determine the masses of black holes.
Reseacher
Moscow State University, Moscow, Russia
September 2007 — May 2008
Department of Extragalactic Astronomy, Sternberg Astronomical Institute. Conducted research on models of gravitational lenses to determine the masses of exoplanets.

Awards

  • Medical Delta Young Scientist award (second place) ,2017
  • International CHARGE consortium Golder Tiger Contribution Awards, 2018
  • Dutch Young eScientist Award (second place), 2018
  • Nominatedfor Erasmus University Research Prize by dean of Erasmus MC, 2019
  • Tiger webinar series award from CHARGE consortium, 2020
  • Tiger webinar series award from CHARGE consortium, 2021

Invited speaker

  • HD-READY: High Dimensional researchin Alzheimer’s Disease, Rotterdam, Netherlands, 2014
  • HD-READY: High Dimensional researchin Alzheimer’s Disease, Rotterdam, Netherlands, 2015
  • Full-HD: Full exploitation of High-Dimensionality in brain imaging Rotterdam, Netherlands, 2017
  • Full-HD: Full exploitation of High-Dimensionality in brain imaging, Stockholm, Sweden, 2017
  • BRIDGE: BRain Imaging, cognition, Dementia and next generation GEnomics, Greifswald, Germany, 2017
  • BRIDGE: BRain Imaging, cognition, Dementia and next generation Genomics, Graz, Austria, 2018
  • Invited lecturer, Cognomics Summer School 2018, Nijmegen, Netherlands
  • Invited lecturer, Neurepiomics Summer School 2018, Bordeaux, France
  • Session chair, “Better medicine through machine learning”, Health Science Research Day, Rotterdam, Netherlands, 2019
  • "Artificial intelligence inepidemiology: past, present and future”, Erasmus Summer Programme, Master Class lectures 2019.
  • Workshop organizer, “Bringing Artificial Intelligence to biomedicine”, CHARGE conference, 2019, St. Luis, USA
  • Workshop GEMSTONE consortium,“Introduction to Deep Learning”, Malta 2019
  • Mathematics of the MusculoSkeleton: Post-Genome analysis for Bone Biology, “Explainable AI and distributed learning”, Israel 2020
  • Online multi-omics data integration workshop series "Artificial Intelligence and multi-omics data: Better, Faster, Stronger", the Netherlands 2021
  • European Society Of Medical Imaging Informatics "Explainable AI and distributed learning", 2021
  • NVIDIA GTC conference "Explainable Artificial Intelligence to unravel genetic architecture of complex traits", 2021


Teaching