Experience
-
Zurich, Switzerland
Student Researcher
Google
- Key Contribution: The first LLM that plays chess at the world champion level using human search budget.
- Hosts: Eric Malmi and Aliaksei Severyn
- Publication: First co-author of a spotlight paper at ICML 2025 — https://arxiv.org/abs/2412.12119
- Planning with LLMs: Enhanced LLMs with search-based planning techniques to improve multi-step reasoning.
- Asynchronous MCTS: Introduced dynamic virtual counts to balance exploration–exploitation with few simulations.
- Prompt Engineering: Assisted in designing board-game prompts and test-time internal search linearization.
- Technology Stack: Python, Transformer Pre-Training, Supervised Fine-Tuning, Tree-Search Methods
-
Zagreb & Cambridge
Senior AI Researcher
Cantab Predictive Intelligence (tech startup)
- Key Contribution: Lead a team of four researchers on a few projects running in parallel.
- Behavioral Credit Scoring: Gradient-boosting model for default risk, achieving a market-leading Gini of 75%.
- AI-Driven Marketing: Boosted heart drug sales by 10% via data-driven A/B-tested campaign for pharma client.
- Personalized Newsletter: Built a hybrid recommender (content-based + collaborative); 1.5% CTR in PoC.
- Delivery Delay Estimation: Predicted COVID-era mall delays using ARIMA and supervised learning.
- Technology Stack: Python, PyTorch, PySpark, Databricks, Statsmodels, AWS/Azure, Sklearn, Numpy, Pandas, Git
-
Budapest, Hungary
Quantitative Researcher
Morgan Stanley
- Key Contribution: Built scalable models for risk, liquidity, and trade execution in financial systems.
- Systemic Risk Model: Built a parallel hill climber heuristic, solving the problem in 3 minutes, averaging 5% from optimal.
- Cash Traceability System: Developed a real-time uncollateralized debt tracker from daily data feeds.
- E-Trading Limits Calibration: Tuned model to block high-risk trades via statistical analysis of client behavior.
- Listed Derivatives Liquidity: Developed a PoC liquidation model driven by intraday futures data.
- Technology Stack: Python, CPLEX, OR-Tools, Q/kdb+, PyQ, SQL, Pandas
-
New York, London & Budapest
Software Engineer
Morgan Stanley
- Annual Grad Program: Participated in a 15-week program for 50 globally selected students.
- Margin Calculator Microservice: Implemented and unit-tested features for NYSE and HGK stock exchanges.
- Technology Stack: Java, C++, Spring Beans, JUnit
-
Zagreb, Croatia
Junior Teaching Assistant
University of Zagreb
- Euclidean Spaces: Delivered problem-solving lectures after achieving the top score in a class of 70.
Education
-
Zurich, Switzerland
PhD in Artificial Intelligence (expected: June 2025)
ETH Zurich
- Key Contribution: Operating a fleet of tens of thousands of agents in real time while satisfying safety constraints.
- Thesis: Safe and Scalable Ride-Sourcing Vehicle Rebalancing: A Constrained Mean-Field RL Approach
- Supervisors: Prof. Francesco Corman and Prof. Andreas Krause
- Research Area: Reinforcement Learning, Multi-Agent Systems, Sequential Decision Making, Data-Driven Algorithms
-
Zagreb, Croatia
MSc in Mathematical Statistics
University of Zagreb
Read Thesis- Thesis: Network Optimization in Railway Transport Planning
- Supervisor: Prof. Marko Vrdoljak
- Distinction: Graduated with honors.
-
Bielefeld, Germany
Visiting Student
University of Bielefeld
- Research Visit: Two semesters funded by Erasmus+ during which I wrote my MSc thesis.
- Host: Prof. Andreas Dress
-
Zagreb, Croatia
BSc in Mathematics
University of Zagreb
Skills
Research
RL
LLMs
MCTS
Safe RL
MFRL
MFC
BO
Programming
Python
C++
SQL
Java
C
Bash & CLI
Q/kdb+
Cloud & Packages
Git
PyTorch
AWS & Databricks
Numpy
Sklearn
Pandas
PySpark
Languages
90%
English
100%
Croatian
10%
German