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Binary Brain
Data Scientist
June 27, 2026 – Present
Visual-Representation-Learning-JEPA
April 18, 2026 – Present
A clean, from-scratch PyTorch implementation of I-JEPA trained on STL-10. Built to benchmark representation-space vs. pixel-space prediction against MAE.
View Projectekf-rpl-omnetpp
January 4, 2026 – Present
An EKF-enhanced RPL routing protocol implementation in OMNeT++ for high-mobility IoT and robotic swarms.
View ProjectSemantic-Anomaly-Distillation
December 30, 2025 – Present
Real-time traffic accident detection via cross-resolution knowledge distillation from Foundation Models (DINOv2) to Edge Devices (MobileNetV3).
View ProjectVisual-Representation-Learning-MAE
December 14, 2025 – Present
A PyTorch implementation of Masked Autoencoders (MAE) on the STL-10 dataset, demonstrating how self-supervised learning significantly improves classification accuracy and convergence speed on limited labeled data.
View ProjectSQM_Test
May 13, 2025 – Present
An autonomous agentic framework that generates, tests, and refines Python code, benchmarked against human developers using industry-standard quality metrics like Pylint and Maintainability Index.
View ProjectMastering-Fighter-Jet-Survival-Tactics
June 7, 2024 – Present
Hybrid A* path planning + DQN reinforcement learning system in Unity ML-Agents — trains a fighter jet to navigate obstacle mazes and evade missile threats using real-time behavioral switching and a custom PID flight controller.
View ProjectStackyDashDemo
June 23, 2020 – June 23, 2020
A demo unity project for Stackydash mobile game
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily skewed towards personal, research-oriented machine learning and robotics projects. While this demonstrates strong technical curiosity and initiative, there is limited evidence of experience in collaborative, production-oriented data science environments or projects with direct business impact. The current role as 'Data Scientist' at 'Binary Brain' is listed as current but with a future start date, making it difficult to assess real-world cultural fit based on past professional experience. The breadth of skills is good for a research-focused role, but might require adaptation for a more traditional enterprise data science setting.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong inclination towards independent research and development. The focus on personal projects suggests self-motivation and a proactive approach to learning and applying new technologies. However, there is no direct data to assess collaboration, communication, or stress handling in a team environment.