Portfolio

Gabor Gorondi

Software engineer focused on applied AI, product-oriented ML systems, and computer vision tools. Currently finishing AI Engineering at UdeSA.

Based between San Francisco and Buenos Aires. Open to AI/ML research and product engineering roles.

    Projects that best represent my work.

    Full-stack product work, applied ML/AI, robotics, RL, and a few side projects.

    Chrome extension that filters bots, spam, and AI slop on X using custom ML pipelines. Built across a TypeScript extension frontend, FastAPI services, Redis queues, Dockerized backend, Supabase storage, and custom detection models.

    • Chrome Extension
    • TypeScript
    • FastAPI
    • Redis
    • Supabase
    • PyTorch
    • LightGBM
    • XGBoost

    Reinforcement learning final project: a plain PyTorch PPO-Clip implementation trained from scratch on CarRacing-v3, plus experiments on how aggressively the visual state can be compressed while still learning effectively.

    • Reinforcement Learning
    • PPO-Clip
    • PyTorch
    • CarRacing-v3
    • PCA

    Wall-mounted pen plotter built from scratch with stepper motors, belt drive, and custom control electronics. Iterated from Arduino Nano to ESP32 plus Raspberry Pi and used it to produce large-format plotted drawings.

    • Hardware
    • Arduino
    • ESP32
    • Raspberry Pi
    • Motion Control

    Interactive data story about unregulated Chinese fishing near the Argentine EEZ. Won second place in a 2025 national data visualization competition organized by Argentina's science and innovation secretariat.

    • Data Visualization
    • Interactive Web
    • Storytelling
    • Award-Winning

    Webcam-based eye gaze prediction system trained on a custom multi-user dataset with varied head poses and lighting. Benchmarked ridge baselines against CNNs, ResNets, and MobileViT models and beat WebGazer-style regression.

    • Deep Learning
    • Computer Vision
    • Webcam Gaze
    • PyTorch
    • MediaPipe

    RF-DETR on VisDrone

    Repo soon(In progress, Private Repo)
    RF-DETR VisDrone fine-tuning preview

    Thesis subproject focused on pedestrian detection from drone viewpoints. Fine-tuned RF-DETR on VisDrone to outperform the quality of readily available open-weight YOLO baselines for aerial pedestrian detection.

    • Object Detection
    • RF-DETR
    • VisDrone
    • Fine-Tuning
    • Drone POV

    Weekend hackathon research project where an RL agent learns to doomscroll 'optimally' by maximizing a synthetic brain-activation reward predicted by Meta's TRIBE v2 fMRI Transformer. Built across reward modeling, PPO training runs, replay/export tooling, and a public Next.js demo.

    • Reinforcement Learning
    • PPO
    • PyTorch
    • SB3
    • Cloud GPU Training
    • Next.js
    • Hackathon

    Dynamic-Obstacle-Aware Safe Landing Zone Prediction

    Final thesis(In progress, Private Repo)
    Thesis simulator preview

    Emergency drone landing system for dynamic urban scenes. It predicts obstacle motion, builds a spatiotemporal risk map, and selects the safest landing point and touchdown time under UAV motion constraints.

    • Computer Vision
    • UAVs
    • MOT
    • Trajectory Prediction
    • Python
    • SITL

    Implemented FastSLAM for a Turtlebot, combining probabilistic localization and mapping into an end-to-end robotics project.

    • Robotics
    • FastSLAM
    • Turtlebot
    • Localization
    • Mapping

    Trained a Deep Q-Network from scratch in PyTorch for the Centipede environment, focusing on the fundamentals of value learning rather than library abstractions.

    • Reinforcement Learning
    • DQN
    • PyTorch
    • From Scratch

    Software engineering and applied AI

    I'm a software engineer currently finishing a degree in AI Engineering at Universidad de San Andrés, in Buenos Aires. My work focuses on applied AI systems that are both technically serious and product-oriented. I love robotics, reinforcement learning, and agentic systems. I also have a good eye for visual storytelling and love photography.

    Formal training.

    UdeSA logo

    Buenos Aires, Argentina. Expected graduation: July 2026. Part of the program's first graduating cohort.

    Work Experience

    Glimpse product preview

    Worked on backend data infrastructure and product features at a Google Trends intelligence startup whose Chrome extension served roughly 100k users. Built internal tooling, user-facing features, and led a $100k/year hedge fund client project. Also handled ops.

    • Calibrated data pipeline on core product features.
    • Contributed multiple user-facing features.
    • Led 3 month project for a top NY hedge fund client worth +$100k ARR.
    • Python
    • Flask
    • Postgres
    • Pandas
    • scikit-learn
    • linux
    The Network preview

    Early hire part-time contributor at a seed-stage startup focused on people search and serendipity. Supported product and data workflows including scraping, parsing, data cleanup, analysis, and other early-stage operational work.

    • Cleaned and normalized messy people-search data across inconsistent input formats.
    • Supported a tiny team across data and ops tasks in an experimental startup.
    • Python
    • Pandas

    Contact info and links.

    Based in SF / Buenos Aires and currently focused on applied ML/AI roles. Email is the fastest way to reach me.

    Portfolio / Gabor GorondiBuenos Aires, Argentina