Coursework

This page gives an overview of the MSc Logic coursework I have completed or planned at the University of Amsterdam, grouped by research area rather than by semester. I am currently in period 5 of the programme.

My main interests are:

Quantum computing & quantum information

NoteHow this fits my interests

This group collects courses that underpin my main focus on quantum computing and quantum information, including both algorithmic / information-theoretic courses and physics-oriented courses on hardware and many-body methods.

  • Near-Term Quantum Computing – Kareljan Schoutens (period 2, completed): Hands-on work with NISQ devices and simulators using Qiskit, focusing on algorithms such as VQE and QAOA, noise models, and error-mitigation strategies. Course project: VQA for the vibrational spectrum of SO₂.
  • Full-Stack Quantum Computing – John van de Wetering (period 4, completed): The “full stack” from abstract quantum circuits down to fault-tolerant implementations, with an emphasis on ZX-calculus, stabiliser formalism, compilation, and quantum error correction.
  • Quantum Hardware – Arghavan Safavi-Naini (period 4, completed): Physical realisations of qubits and interacting two-level systems using ions and neutral atoms; decoherence and noise processes, and an overview of leading platforms for quantum computation and sensing.
  • Advanced Numerical Methods in Many Body Physics – Philippe Corboz (period 5, in progress): Computational methods for classical and quantum many-body systems, including Monte Carlo algorithms and tensor-network techniques such as DMRG.
  • Quantum Cryptography – Florian Speelman (period 5, in progress): Security notions and protocols in quantum cryptography (e.g. QKD, oblivious transfer, bit commitment, secret sharing) and quantum-hard assumptions for post-quantum cryptography.

Artificial intelligence, machine learning & interpretability

NoteHow this fits my interests

These courses and projects support my secondary focus on AI and mechanistic interpretability, connecting general-purpose machine learning and deep learning with language models and model explainability.

  • Machine Learning and Language Models – Martha Lewis (period 1, completed): Supervised and unsupervised learning, basic reinforcement learning, and applications to language modelling; implementation of key methods in Python and standard ML libraries.
  • Deep Learning 1 – Pascal Mettes (period 2, completed): Core deep-learning architectures and training methods, including CNNs, transformers, graph neural networks, generative models, and self-supervised learning.
  • Mechanistic interpretability of variable assignment in a Transformer-based model – Fausto Carcassi (period 3, completed): Independent group research project on mechanistic interpretability of a Transformer language model using causal interventions on the residual stream to study how variable assignment in Python code is represented. More details on the projects page.
  • Reinforcement Learning – Herke van Hoof (period 4, completed): Value-based and policy-based methods, approximate and deep RL for discrete and continuous control problems, and critical evaluation of RL experiments.
  • Interpretability & Explainability in AI – Willem Zuidema (period 6, planned): Post-hoc interpretability tools (e.g. saliency, attribution, probing, influence functions), explainable-by-design models, constrained deep learning, and evaluation of interpretability techniques.

Computer science & logic

NoteHow this fits my interests

These courses provide theoretical computer science and logic foundations that support my work in quantum computing and AI.

  • Logic, Language and Computation – Nick Bezhanishvili (period 1–2, completed): Survey of research lines in logic, language, and information within the ILLC, including guest lectures and individual meetings with researchers and PhD students.
  • Information Theory – Nicolas Resch (period 2, completed): Shannon entropy and mutual information, data compression and channel coding theorems, zero-error information theory, and information-theoretic security.
  • Computational Complexity – Ronald de Haan (period 4, completed): Complexity classes and reductions, NP-completeness, nondeterminism, alternation, randomised computation, circuits, and subexponential-time complexity.
  • Game Theory – Ulle Endriss (period 5, in progress): Noncooperative and cooperative game theory, mechanism design, and applications to strategic interaction and cooperation between rational agents.
  • Introduction to Modal Logic – Nick Bezhanishvili (period 7–8, planned): Kripke semantics, bisimulations, completeness and finite model property, expressive power, and more advanced systems such as propositional dynamic logic.