CV

Last updated: Mar 2025.
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Education

ETH Zürich
MSc ETH in Computer Science, Sep 2020 – Mar 2023

• Major in Machine Intelligence and minor in Programming Languages and Software Engineering.
• Thesis: “Exploring Data Collection Dynamics Through Data Valuation.”

University of Copenhagen
BSc in Computer Science, Sep 2017 – Jun 2020

• Specialization in Data Science with coursework focused on machine learning.
• Thesis: “The Carbon Footprint of Training Deep Learning Models.”

University of California, Merced
UCEAP Reciprocal Program, Aug 2019 – Dec 2019

• Exchange study part of my BSc CS at UCPH with coursework focused on machine learning.

Experience

UBS
Quant, Jan 2025 – Present

• Selected via internal transfer to join a team of quants based on strong quantitative, machine learning, and programming skills.
• Develop and implement advanced algorithms for network analysis, focusing on processing and extracting insights from large-scale graph data.
• Develop internal workshops on generative AI with a focus on natural language processing.

Quant Developer, Jun 2023 – Jan 2025

• Design and develop big data tools and solutions for Treasury Risk Control’s balance sheet analytics.
• Lead developer for a library calculating cash flows from position-level data, enhancing risk management through detailed sensitivity analysis using automatic differentiation.
• Drive code infrastructure improvements, including CI/CD pipelines and migration to Databricks and Spark, enhancing data processing speed and reliability.
• Implement machine learning models for predictive analytics and risk assessment, resulting in more accurate forecasting and better-informed risk management decisions.

Alexandra Institute
AI / Machine Learning Specialist, Mar 2023 – Jun 2023

• Dual role in applied research and expert consultancy in machine learning, focusing on natural language processing and utilizing pretrained transformers.

University of Copenhagen
Teaching Assistant, Jan 2020 – Jul 2020

• Assisted in teaching the Data Science course, covering databases, machine learning, and data pipelines.

Nykredit
Software Developer, Oct 2018 – Jan 2020

• Developed financial software for internal advisors as part of an agile C# development team.
• Built and maintained solutions for mortgage loans in .NET, significantly reducing processing time.
• Implemented continuous deployment pipelines using Jenkins and BitBucket to fully automate integration testing and deployment, thereby improving efficiency and reliability.

Publications

• Carbontracker: Tracking and predicting the carbon footprint of training deep learning models
  L. F. W. Anthony, B. Kanding, and R. Selvan
  ICML Workshop on Challenges in Deploying and monitoring Machine Learning Systems, 2020
  Paper Code

• Carbon footprint of selecting and training deep learning models for medical image analysis
  R. Selvan, N. Bhagwat, L. F. W. Anthony, B. Kanding, and E. B. Dam
  International Conference on Medical Image Computing and Computer-Assisted Intervention — MICCAI 2022, 2022
  Paper

Highlighted projects

Carbontracker
github.com/lfwa/carbontracker
Open-source tool for tracking and predicting the energy consumption and carbon emissions of training deep learning models in Python. Freely distributed under the MIT License. Corresponding publication arXiv. Over $120$k downloads on the Python Package Index (PyPI) as of writing.

Datadynamics
github.com/lfwa/datadynamics
Library and environment for simulating data collection dynamics in multi-agent settings, primarily targeting exploration of data valuation approaches. Freely distributed under the BSD 3-Clause License.

Reinforced Graph Neural Networks for Collaborative Filtering
github.com/lfwa/reinforced-gnn
Introduced a novel architecture that generates predictive compatibility scores for never-before-seen content in recommendation systems. Combines graph neural networks with deep feed-forward networks enhanced by reinforcement signals.

Static Taint Analysis For Ethereum Contracts
github.com/lfwa/vulnerable-ethereum-contracts
Designed and implemented a static taint analyzer in Datalog for Ethereum smart contracts, detecting vulnerable contracts that risk being deleted with funds transferred to untrusted addresses.

Supporting Alternative SMT Solvers in Viper
github.com/viperproject
Expanded the symbolic-execution based automated verification backend in Scala for Viper by adding support for multiple SMT solvers, such as cvc5, enhancing verification capabilities.

Skills

Programming Languages

• Python, C#, SQL, Rust, Scala, F#, Java, C, Datalog

Databases

• PostgreSQL, Oracle

Frameworks and Tools

• PyTorch, TensorFlow, Gym(nasium), PettingZoo, scikit-learn, NumPy, pandas, Matplotlib, Git, Spark, Hadoop, Neo4j, QuantLib, networkx