About me:
- Candidate for the Master of Business Analytics at MIT, a program focused on Machine Learning under modern optimization lens, and operations research.
- Involved in research work at the MIT Operations Research Center, working to apply computer vision tools to the industry of EV charging stations installations.
- Background in Industrial Engineering, having studied at Polytechnic of Milan and Delft University of Technology.
Interests include multimodal ML, Vision, Optimization, and Greek Cuisine
Relevant Projects:
| Name | Topic | Methods | Report | Code |
|---|---|---|---|---|
| EV charging feasibility computer vision framework | Computer Vision | CNN ViT Space-time attention |
MIMO Poster | Core code private Pipeline + Labelling UI |
| Video-to-audio AI | Computer Vision | Embeddings Vector Database Multimodal models Audio Generation |
Video Presentation Report |
Code Dataset Pipeline ImageBind Fork AudioCraft fork |
| LLM-based pre-processing framework for tabular ML | Machine Learning | Embeddings Fine-tuning |
Report | Code |
| Optimization-aware active learning | Optimization | Duality Active learning Tabular ML |
Report | Code |
| Optimization of urban multi-modal hubs (Analytics Lab, 1st place) | Optimization | Multi-objective opt. Traffic modeling |
- | Streamlit UI |
| Instructing agents with LLM | Reinforcement Learning | PPO Reward Design |
- | - |
| LLM router (AGI House Hackathon, 2nd place) | LLM | Prompt Optimizer Moodel Embeddings |
Demo | LLMLingua fork |