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Jakub Tomczak

Associate Professor

BIOGRAPHY

Jakub Tomczak is a generative AI leader with more than 15 years of experience in machine learning, deep learning and generative AI. He has a proven track of leading research projects, carrying out cutting-edge research  and securing funds . He is experienced in and enjoys managing people.

Tomczak is an effective team leader encouraging initiative and independence, and facilitating cross-functional collaboration, serving as a fractional AI leader for companies (e.g., eBay, Qualcomm) and startups. He is a program chair of NeurIPS 2024, the largest AI conference, and the author of the first fully comprehensive book on generative AI, “Deep Generative Modeling.” Tomczak is also the founder of Amsterdam AI Solutions LLC and a co-founder of GenSiLab Inc.

EDUCATION

  • Ph.D. in Computer Science – Wroclaw University of Technology
  • M.Sc. in Computer Science – Blekinge Institute of Technology
  • M.Sc. in Computer Science – Wroclaw University of Technology

RESEARCH

  • Generative AI Systems
  • Generative Modeling
  • Probabilistic Modeling
  • Deep Learning
  • AI4Science

PUBLICATIONS

  • G. Palla, S. Babu, P. Dibaeinia, J.D. Pearce, D. Li, A.A. Khan, T. Karaletsos, J.M. Tomczak, Scalable Single-Cell Gene Expression Generation with Latent Diffusion Models, ICML 2026
  • A. Izdebski, J. Olszewski, P. Gawade, K. Koras, S. Korkmaz, V. Rauscher, J.M. Tomczak, E. Szczurek, Synergistic Benefits of Joint Molecule Generation and Property Prediction, Transactions on Machine Learning Research, 2026
  • J. Linders, J.M. Tomczak, Knowledge Graph-extended Retrieval Augmented Generation for Question Answering, Applied Intelligence, 2025
  • J. Kaleta, P. Skiers, J. Dubinski, P. Korzeniowski, T. Trzcinski, J.M. Tomczak, K. Deja, JointDiffusion: Joint representation learning for generative, predictive, and self-explainable AI in healthcare, Computerized Medical Imaging and Graphics, 2025
  • A. Kuzina, H. Chen, B. Esmaeili, J.M. Tomczak, Variational Stochastic Gradient Descent for Deep Neural Networks, Transactions on Machine Learning Research, 2025
  • A. Kuzina, J.M. Tomczak, Hierarchical VAE with a Diffusion-based VampPrior, Transactions on Machine Learning Research, 2024
  • J.P. Engelmann, A. Palma, J.M. Tomczak, F.J. Theis, F.P. Casale, Mixed Models with Multiple Instance Learning, AISTATS 2024

AWARDS

  • 2024 Oral presentation at AISTATS 2024
  • 2023 Transactions of Machine Learning Research (TMLR) Expert Reviewers recognition
  • 2020 Oral presentation at CVPR 2020
  • 2018 Oral presentation at AISTATS 2018
  • 2018 Two oral presentations at UAI 2018

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