Research
Data-efficient alforithms (active learning) for applications in chemistry
Summer Semester 2026
Molecular Design
Curriculum Vitae
- since 09/2026: Ph.D. student in the Jacob Group, TU Braunschweig (continuation of Ph.D.)
- 10/2025 - 11/2025: Research stay in the Gryn'ova Group, University of Birmingham
- 10/2023 - 09/2026: Ph.D. student in the Proppe Group, TU Braunschweig
- 10/2020 - 08/2023: Master of Science, Computer Science, TU Braunschweig
Master thesis supervised by Prof. Martin Johns - 10/2017 - 09/2020: Bachelor of Science, Computer Science, University of Leipzig
Conferences and Workshops
- 06/2026: Southern Lower Saxony Theoretical Chemistry Meeting, Hannover
Vortrag: Generative Design of Amines for Sustainable CO2 Capture - 03/2026: Braunschweiger JungeChemieTagung, Braunschweig
Vortrag: Generative Design of Amines for Sustainable CO2 Capture - 03/2026: Chemical Compound Space Conference, München
Poster: Generative Design of Amines for Sustainable CO2 Capture - 10/2025: SusML Workshop - Towards sustainable exploration of chemical spaces with machine learning, Dresden
Poster: Data-efficient Discovery of Amines for Sustainable Post-combustion Carbon Capture - 06/2025: International Conference on Chemical Structures, Noordwijkerhout
Poster: Active Learning for Chemical Space Exploration - 09/2024: STC – Symposium on Theoretical Chemistry, Braunschweig
Poster: Active Learning for Chemical Space Exploration - 05/2024: Chemical Compound Space Conference, Heidelberg
Poster: Active Learning for Chemical Space Exploration
2: Uncertainty Quantification for In Silico Chemistry
Tom Frömbgen, Elizaveta Surzhikova, Jürgen Dölz, Jonny Proppe, Barbara Kirchner, Christoph R. Jacob
Online VersionPreprint Version
1: regAL: Python Package for Active Learning of Regression Problems
Elizaveta Surzhikova, Jonny Proppe
Mach. Learn.: Sci. Technol. 2025, 6, 025064
Online VersionPreprint Version
