Engineered a scalable Clustered Federated Learning framework for joint anomaly detection and attack classification in resource-constrained IoT environments (paper in preparation).
Graduate Researcher
Yale University
Co-designed compression modules for Split Learning (up to ~4× less network usage). Investigating Split Federated Learning with multimodality and LLMs under communication and compute constraints. Collaborating on NSF-funded multi-university projects.
Research Engineer
Yale University / YINS
Benchmarked 7 data-loading libraries across vision datasets; developed and maintain an open-source data-loader benchmark framework. Built an Ethereum data scraper and analyzed 2TB+ of blockchain data on DeFi responses to federal monetary policy.
Research Assistant
CERTH / INAB
Led redesign and refactoring of TRIPR into a Bioconductor package; automated testing workflows with GitHub Actions.
Education
Ph.D., Electrical & Computer Engineering
Yale University
Expected May 2028. Advisor: Prof. Leandros Tassiulas. Selected courses: Intermediate Machine Learning, Distributed Systems, Graph Neural Networks, Big Data Systems.
Diploma thesis on predicting smartphone users’ emotional state from keystroke characteristics using machine learning. Advisor: Prof. Leontios Hadjileontiadis.
Skills
Programming Languages
Python
Go
Rust
R
C/C++
Bash
Frameworks & Tools
PyTorch
TensorFlow
Docker / Kubernetes
Git
LaTeX
Awards
Yale GSAS Student Fellowship
Yale Graduate School of Arts and Sciences ∙
August 2023
Graduate fellowship for Ph.D. studies in Electrical & Computer Engineering.