Faraneh Haddadi

PhD candidate at Loschmidt Laboratories in Brno, Czech Republic, specializing in machine learning and AI applications for protein engineering and biochemistry. Expertise includes developing a classification method for identifying functional protein pockets, now integrated into EMBL-EBI’s ChannelsDB, and successfully adapting advanced image processing techniques for analyzing 3D molecular dynamics data. Proficient in leveraging structural biochemistry data with explainable AI methods to uncover critical functional determinants of biomolecules, while innovating machine learning approaches to address complex scientific challenges. Committed to advancing research through the integration of cutting-edge technology and analytical methodologies.

• [2023] Machine Learning-Guided Protein Engineering, ACS Catalysis DOI: 10.1021/acscatal.3c02743 Kouba, P, Kohout, P, Haddadi, F, & Other Authors.
• [2024] Large-scale Annotation of Biochemically Relevant Pockets and Tunnels in Cognate Enzyme-Ligand Complexes, Journal of Cheminformatics DOI: 10.1101/2023.03.29.534735 Vavra, O, Tyzack, J, Haddadi, F, Stourac, J, Damborsky, J, Mazurenko, S, Thornton, J, Bednar, D.

• Prague ELIXIR CZ Annual Conference 2021 Machine Learning for Annotating Cavities - presentation
• Lyon ISMB/ECCB Conference 2023 Capturing Protein Dynamics and Their Determinants Using Explainable Artificial Intelligence - poster

• Artificial Intelligence in Biology, Chemistry, Bioengineering - Masaryk University - Practicals. (2022-2023)
• Principles of Compiler Design - K.N Toosi University of Technology and Alzahra University - Seminars. (2014-2019)
• Math, Statistics, and Probability - Private teaching institute, Karaj, Iran - Lessons. (2014-2019)