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Research Assistant

Delft University of Technology

Conducting research on Relational Deep Learning and graph neural networks.

• Researching Relational Deep Learning by benchmarking Tabular Transformers against state-of-the-art graph learning models (RDL, RelGT, ft-PNA, ft-FraudGT)
• Investigating graph coarsening strategies to extend applicability to heterogeneous relational graphs
• Working under supervision of Prof. Kshitij Anan at the Data Intensive Systems Lab

Data Science Intern

Robeco

Developed data visualization and attribution analysis tools for ESG and emissions data.

• Built web-based tool to visualize company hierarchies and emissions data inheritance for 3+ million companies
• Researched and developed novel attribution method incorporating trading data to measure fund decarbonisation
• Improved candidate selection pipeline by 50% while lowering inference time

AI Software Engineer Intern

Lufthansa Group

Designed microservices for document processing and semantic search using AI/ML.

• Designed microservice with Django to extract and categorize grant documents using Meta's Llama framework
• Leveraged vector databases and NER for semantic search and instantiated BERTopic model
• Exhaustively evaluated models using F1 score with text summarisation, achieving combined score of 0.77
• Automated search of academic papers and ranked them by relevance with transformers

Part-time Software Engineer

Paro Software

Developing features for subscription-based payment processing and document management tools.

• Migrated payment providers for subscription-based tools handling over $10k weekly volume
• Developed analytics and reporting features for subscription renewals and discounts
• Automated license-key generation and delivery, reducing wait time from 1 day to 10 seconds
• Streamlined invoice generation for efficient document access
• Migrated and refactored medical charity website with 100,000+ monthly visitors

Bridging Program

Delft University of Technology

Applied Mathematics

• Proofs
• Analysis
• Real Analysis
• Optimization
• Measure and Probability Theory
• Partial Differential Equations
• Numerical Methods

Minor

Politecnico di Milano

Mathematics and Statistics

• Numerical Analysis for Machine Learning
• Systems and Methods for Big and Unstructured Data Operations Research

Bachelor of Science

Delft University of Technology

Computer Science and Engineering

• OOP
• Probability Theory & Statistics
• Linear Algebra
• Calculus
• Machine Learning
• Big Data Processing
• Data Mining
• Computational Intelligence
• Algorithms & Data Structures
• Algorithm Design

IE High Potential Scholarship

IE University

Undergraduate Excellence Scholarship

University of Edinburgh

Graph Learning Methods on Tabular Data

Researched local and global attention mechanisms for Graph Transformers in Relational Deep Learning.

• Implemented custom relation-aware local attention mechanisms
• Achieved state-of-the-art results on classification and regression benchmarks

Bayesian Clustering of Nations by Educational Performance

Developed Bayesian approaches to clustering nations using PISA educational dataset.

• Designed semi-parametric approach and Nested Dirichlet Process
• Presented findings at Italian Society of Statistics (SIS 2025) in Genoa

Tree Biomass Prediction

Hackathon project developing regression model to predict tree biomass using ensemble methods.

• Part of Team Epoch at Delft Algorithm Programming Contest