Nicholas Erup Larsen
MSc in Mathematical Modelling and Computation at DTU. 
Self-Play RL Agent ->
Reached 8th out of 114 in the first competition sprint with a 2.72M-parameter global-context ResNet trained for 1.8B agent steps
Algorithmic Trading System ->
Bachelor's thesis on training, backtesting, and deploying neural networks to trade cryptocurrency perpetual futures across multiple exchanges
Stock Website ->
The only website in the world to display a stock alongside its dynamically updating financials as far as I'm aware
Self-Supervised Learning for Time Series ->
My first paper ever written, exploring self-supervised learning for time-series price data and reporting promising regression results. It has since been cited by two other papers
Visiting Student
Tsinghua University
Self-Play RL Agent – Generals Competition
Project · July 2026 – August 2026 · Write-up
• Reached 8th out of 114 in the first sprint with a 2.72M-parameter global-context ResNet using 20.7 ms per move (150 ms limit)
• Trained for 1.8B agent steps using league and self-play techniques to use and explore samples more efficiently
Quantitative Research
Student Analyst · Copenhagen Energy Trading · October 2025 – July 2026
• Researched, developed, and deployed profitable algorithmic trading strategies for day-ahead and intraday auctions across EU bidding zones
• Developed real-time PnL dashboards with Panel and optimized SQL queries
• Built a modular backtesting framework for systematic, fast experimentation
• Developed bidding-curve models for aFRR markets and helped optimize physical BESS assets
• Maintained and designed Excel-based bidding tools used daily by the trading desk
Algorithmic Trading System
Bachelor's thesis · Solo developer & researcher · November 2024 – June 2025
• Built an end-to-end system for training, backtesting, and deploying neural networks to trade cryptocurrency perpetual futures through REST and WebSocket APIs
• Achieved statistically significant improvements over open-source state-of-the-art time-series forecasting models
• Architected a unified execution layer across centralized exchanges, decentralized exchanges, and prediction markets
MSc in Mathematical Modelling and Computation
Technical University of Denmark, DTU · September 2025 – Ongoing
Fixed Income Research
Assistant Analyst · Nykredit Markets · September 2025 – November 2025
• Refactored production Python scripts for large bond-market analyses, improving runtime and readability
• Implemented lightweight data infrastructure to reduce redundant Bloomberg and market-data queries
• Migrated complex Excel/VBA models into reproducible pipelines, reducing manual work and human error
• Introduced Git and documentation practices to improve maintainability
AI & Full Stack Engineer
Project lead and developer · Leadership Advisor Group · March 2024 – February 2025
• Automated in-house workflows with AI to extract valuable insights from large amounts of unstructured, messy text data
• Developed a full-stack, cloud-hosted web application integrating OpenAI's API with a custom NLP pipeline that substantially improved the quality of the LLM output
• Led requirements gathering, defined project scope, interviewed and hired new people, and delivered a site that exceeded client expectations
Exchange Semester in Electrical and Computer Engineering
The University of Texas at Austin · September 2024 – December 2024
| Course | ECTS |
|---|---|
| 5th semester (Fall 2024) | |
| • Data Science Lab | 8 |
| • Software Design and Implementation I (C Programming) | 6 |
| • Exploring User Interaction | 6 |
| • Communication for Executive Leadership | 6 |
| • Visual Storytelling | 6 |
BSc in Artificial Intelligence & Data
Technical University of Denmark, DTU · September 2022 – June 2025
| Course | ECTS |
|---|---|
| 6th semester (Spring 2025) | |
| • Bachelor's thesis | 15 |
| • Bioengineering (Polytechnical Foundation) | 5 |
| 5th semester – Exchange (Fall 2024) | |
| 4th semester (Spring 2024) | |
| • Active Machine Learning and Agency | 5 |
| • Introduction to Reinforcement Learning and Control | 5 |
| • Symbolic Artificial Intelligence | 5 |
| • Database Systems | 5 |
| • Project Work | 10 |
| • Physics 1 | 10 |
| 3rd semester (Fall 2023) | |
| • Project in Statistical Evaluation for AI & Data | 5 |
| • Introduction to Machine Learning and Data Mining | 5 |
| • Advanced Engineering Mathematics 2 | 5 |
| • UX Design Prototyping | 5 |
| • Fundamental Chemistry | 5 |
| 2nd semester (Spring 2023) | |
| • Introduction to Mathematical Statistics | 5 |
| • Algorithms and Data Structures 1 | 5 |
| • Signals and Data | 5 |
| • Artificial Intelligence and Human Cognition | 5 |
| • Advanced Engineering Mathematics 1 | 10 |
| 1st semester (Fall 2022) | |
| • Advanced Engineering Mathematics 1 | 10 |
| • Introduction to Intelligent Systems | 10 |
| • Discrete Mathematics | 5 |
| • Introduction to Programming & Data Processing | 5 |
Business & Science Elite (HHX)
Niels Brock · August 2018 – June 2021
• Mathematics A
• Microeconomics A
• Macroeconomics A
• English A
• Danish A
