Work Experience
- Research Associate in Machine Learning, University of Cambridge, since 2020
Development of reinforcement learning approaches for molecular design in 3D
- Postdoctoral Researcher, University of Cambridge, 2018–2020
Design of Bayesian deep learning models to accelerate the discovery of novel materials
Advisor: José Miguel Hernández-Lobato
- Machine Learning Engineer, Semiconductor Research Corporation, 2018–2020
Multi-Objective Bayesian optimization method development for design space exploration of integrated circuits
Education
- Ph.D. Theoretical Chemistry, ETH Zurich, 2018
Thesis: Error-Controlled Quantum Chemical Exploration of Reaction Networks
Advisor: Markus Reiher
- MSc. Interdisciplinary Sciences (with distinction), ETH Zurich, 2015
Focus: Chemistry and Physics
Thesis: Bridging the Gap Between Theory and Experiment Using Gaussian Processes, Harvard University.
- BSc. Interdisciplinary Sciences, ETH Zurich, 2013
Focus: Chemistry.
Awards and Fellowships
- Computational Resources, 100,000 GPU hours, EPSRC, 2021–2022
- Early Postdoc.Mobility fellowship of the Swiss National Science Foundation, 2018–2020
- Ph.D. Fellowship of the Fonds der Chemischen Industrie, 2015–2017
- Best Poster Presentation, Swiss Chemical Society Meeting, Fall 2016
- Master’s degree with distinction, 2015
Talks
- IBM Research, Zurich (virtual), January 2021
Reinforcement Learning for Molecular Design Guided by Quantum Chemistry
- Bjørk Hammer’s Research Group, Aarhus (virtual), December 2020
Reinforcement Learning for 3D Molecular Design Guided by Quantum Chemistry
- Machine Learning and AI in (Bio)chemical Engineering, Cambridge, July 2020
Reinforcement Learning for Molecular Design Guided by Quantum Mechanics
- Deep structures – Joint workshop by Alan Turing Institute and Finnish Center for Artificial Intelligence, Helsinki, December 2019
GraphDG: A Generative Model for Molecular Distance Geometry
- Machine Learning and AI in (Bio)chemical Engineering, Cambridge, July 2019
Machine Learning for Chemical Reaction Networks
- Microsoft Research Cambridge AI+Pizza, Cambridge, February 2019
Exploring Chemical Reaction Networks with Gaussian Processes
- 53rd Symposium on Theoretical Chemistry, Basel, August 2017
Automated Exploration of Complex Chemical Reaction Networks
- Competence Center for Computational Chemistry Meeting, IBM Research, January 2017
Heuristics-Guided Exploration of Reaction Mechanisms
Skills
- Mentoring: Supervised two master’s students during their research projects
- Teaching: Teaching assistant for several lectures including general chemistry, inorganic chemistry, and computer science, since 2013
- Programming languages: Python and C++
- Databases: MongoDB, PostgreSQL
- Administration of high performance computing facility (2015–2018)
Journal and Conference Reviewing