Curriculum Vitae
Education
Ph.D. in Pharmacology (Computational Drug Discovery)
University of Toronto, Toronto, Canada — 2020 - 2025
“Developing Computational Methods in Proximity Pharmacology for Enzyme Discovery, PROTAC Screening, and Conformational Space Exploration”
- Five publications on method and database development and one publications in pre-print. Presented 7 talks and posters at key conferences.
- A+ grades in world-leading post-graduate machine and deep-learning courses at the University of Toronto, taught by Jimmy Ba and Bo Wang (CSC2515, CSC2516).
- Performed computational structural analysis for four ongoing target specific collaborations to better understand mechanism of action. For example:
- Leveraged HDX mass-spectrometry data for ternary complex prediction using PROTAC screening and MD simulations.
- Conducted docking screens and MD simulations for novel small molecules to understand binding site interactions over time.
- Evaluated predicted protein-protein complexes using mutational data and MD simulations to identify the most stable conformation.
- Machine learning applied to drug discovery projects, for example:
- Implemented a multi-agent reinforcement learning algorithm to sample PROTAC-induced ternary complex conformational space.
- Developed edge identification algorithm based on K-nearest neighbour graph to pick new states for adaptive sampling.
- Designed Convolutional Variational AutoEncoder (ConvVAE) to reduce the PROTAC conformational space using invariant data to visualize free energy landscape.
B.Sc. of Science
Amsterdam University College, Amsterdam, The Netherlands — 2017 - 2020
- Graduated with honours (Cum Laude), GPA: 3.88/4.0
- Biomedical science major (Pre-med track) with organic chemistry and pharmacology courses
- 4th year thesis project (graded 9/10): Computational analysis of photoswitchable sildenafil analogs as phosphodiesterase 5 inhibitors
Research Interests
- Topic 1: Proximity pharmacology: screening of proximity pharmacology compounds (e.g. molecular glues, PROTACs, PHICs, DUBTAC, etc.) and modelling of ternary complexes induced by these compounds.
- Topic 2: Developing tools to generate free energy landscapes of complex systems using adaptive sampling tools in molecular dynamics or variational sampling techniques.
- Future topic 3: Would like to study and develop tools to design proteins using dynamic approaches, especially for peptide or antibody design.
Internships
Research Intern
Vector Institute / Maddison lab / University of Toronto — Toronto, Canada (April 2025 – Present)
- Developing code to convert cartesian coordinates to internal coordinates for solvated systems and to calculate energy using JAX jit compilation to increase efficiency.
- Evaluating sampling strategies, including but not limited to, MCMC, simulated annealing, and diffusion-based samplers to approximate the Boltzmann distribution of protein conformational spaces.
- Analyzing Boltzmann-distributed free energy landscapes to study protein conformational changes, ligand interactions, and properties of protein–protein complexes.
Pre-Amp Fellow
Amplitude Venture Capital, Toronto, Canada - (May 2024 - Aug 2024)
- Conducted in-depth explorations of novel healthcare venture hypotheses, leveraging scientific innovation, experimental iteration, and fast prototyping to identify high-impact opportunities.
- Collaborated with Pre-Amp and Amplitude Ventures leaders and portfolio companies to develop strategy around indication prioritization, novel applications for platform technology, and performed competing landscape analyses.
Publications
Please see for full list: Publications
Or more up-to-date list on Google Scholar
Awards and Grants
Best presenter at Visions in Pharmacology conference — 2023
- Presented work on benchmarking PROTAC ternary complex prediction software and roads for improvement.
Resource Allocation Competition, Digital Research Alliance of Canada — 2024
- Awarded $62,000 in computing resources for the research project that will evaluate the free energy landscape of PROTAC-induced ternary complexes using MD simulation which are accelerated with developed advanced sampling methods and variational autoencoders to reduce dimension of search space.
MITACS accelerate — 2022 - 2024
- Awarded $75,000 for ‘Genes to affordable medicines’ project to cover expenses which support the direct costs of research.
University of Toronto Fellowship — 2020 - 2024
- Awarded a fellowship of $2000 annually ($5000 for first year) for recognition of excellent academic achievement.
Technical Skills
- Python
- PyTorch, JAX, SciPy, RDKit, Numpy, Pandas
- Deep learning, reinforcement learning, variational autoencoders
- Protein structural analysis e.g. predicting ligandability, binding site interactions, and protein domains
- Fragment/small molecule/PROTAC screening and optimization
- Software: ICM, MOE, Rosetta
- MD simulations including free energy perturbations and advanced sampling methods
- Software: GROMACS, AMBER, OpenMM
- Linux scripting (HPC clusters)
Outside of Academia
Teaching assistant
University of Toronto — Toronto, Canada (2022 – 2024)
- Taught a 3rd-year pharmacology course about advancing biomedical discoveries from the laboratory into the clinic.
Captain, Varsity Field Hockey Team
University of Toronto — Toronto, Canada (2020 – 2023)
- I lead a group of 27 athletes on and off the field that resulted in 1st place in provincial OUA championships and 2nd place in USPORTS national championships in 2021 and 2023.
Languages
- English (Fluent)
- Dutch (Native)
Last updated: May 2025