Barcelona, Spain
Guido Biosca Lasa
ML Engineer & CS Student
CS student at UPC Barcelona, working on model compression at Multiverse Computing. I like ML problems that don't have easy answers.
About Me
Studying Computer Engineering at UPC in Barcelona. I got into ML because it sits right at the edge of what's currently possible — and I find it hard to look away from that.
Right now I'm at Multiverse Computing working on CompactifAI, their model compression tool. The goal is making large AI models smaller and cheaper to deploy using tensor network techniques. It's genuinely hard in the interesting way — the theoretical foundations are solid, the implementations aren't always.
Before that: fall detection from wearable sensor data at a healthcare startup, backend and data pipelines for satellite imagery at Telespazio. On the side I'm usually building something — most of my personal projects start from a question I couldn't find a good answer to.
Experience
Working on CompactifAI, a large-scale model compression project that uses quantum-inspired tensor network methods to shrink large AI models without sacrificing performance.
- Implementing compression techniques based on tensor networks to reduce model size while preserving accuracy
- Building production-ready pipelines to improve deployment feasibility and reduce inference costs
- Translating theoretical research into scalable ML solutions alongside research and engineering teams
Built backend systems and data processing pipelines for satellite imagery analysis. Also managed a small team of two interns.
- Implemented Python data pipelines to process satellite imagery with a focus on robustness and data integrity
- Designed REST APIs, database schema, authentication and data-validation logic
- Managed a backend team of two interns: task assignment, code reviews and delivery planning
- Improved production system reliability through refactoring, testing, and debugging
Machine Learning & Data Analyst Intern
Jul 2024 — Dec 2024
Built fall and position detection models for a healthcare project using wearable wristbands with accelerometer and gyroscope sensors.
- Developed fall and position detection models from time-series sensor data, minimizing false positives
- Processed and cleaned large volumes of high-frequency sensor data from accelerometers and gyroscopes
- Built scalable Python workflows to aggregate, filter, and synchronize data from multiple sources
- Created internal tools to automate data analysis, visualization, and feature extraction
Projects
Selected projects showcasing end-to-end ML system design
Bayesian GNNs for Molecular Dynamics
Extended PaiNN — an equivariant GNN for molecular dynamics — with Bayesian layers to add uncertainty estimates on top of energy and force predictions. Forces derived via autodiff, not learned directly.
Algorithmic Trading Bot
Built and ran a trading bot in live crypto markets. Momentum-based strategies, sub-second execution across 10,000+ markets, with a Telegram interface to monitor and control everything from your phone.
Real-Time Crypto Data Pipeline
Pulls real-time prices and order book data from multiple exchanges every second. Handles 48-hour retention automatically and exposes everything through a local API with live dashboards.
Wearable Fall Detection
CNN trained on raw accelerometer and gyroscope streams from wrist wearables to detect falls in real time. Main challenge: making it reliable enough to actually use without drowning in false positives.
Mapping Crypto Communities on Reddit
Co-mention graph of thousands of cryptocurrencies from r/CryptoMoonShots posts — to map which coins get talked about together, who's driving the conversation, and what the sentiment looks like per community.
WayHer – Women's Safety App
Route mapping app focused on women's safety. Functional prototype with a live demo and an extensible data model designed for future mobile integration.
Skills
ML & Data
Languages
Tools & Systems
Computer Science
Education
Academic foundation and professional certifications
Exchange — Master-level courses
Computer Science
Technical University of Denmark (DTU)
Sep 2025 — Present
Advanced coursework in Machine Learning, Deep Learning, and Graph Neural Networks. Hands-on projects including GNNs for molecular dynamics simulations.
Bachelor's Degree
Computer Engineering
Universitat Politècnica de Catalunya (UPC BarcelonaTech)
Sep 2022 — Present
Strong foundation in algorithms, data structures, complexity analysis, and optimization.
Get in Touch
Interested in working together? Let's connect.
Open to internships, collaborations, or just an interesting conversation about ML. Drop me a line.