Résumé/CV

Data scientist and experienced programmer specialized in computer vision, deep learning models on edge devices, multi-spectral remote sensing, and large vision models across diverse domains, with over 12 years of experience (5+ years in academia, 7+ years in industry).

• • As a Tech Lead in the Physical AI team, led the development of device-efficient, generative-AI-powered machine learning models on IoT devices for Walmart’s barcode intelligence, and currently scaling the solution to 600+ stores.

• • Have domain expertise and hands-on experience with advanced ML/DL architectures, including Generative Adversarial Networks (GANs), the Segment Anything series, the YOLO series, CLIP, Grounding DINO, and Transformers, as well as the development of custom deep learning architectures across diverse disciplines.

• • Have advanced proficiency in Python, including frameworks such as PyTorch and TensorFlow, and professional software development experience with C++, Visual Basic, Go, and R.

• • Demonstrate a unique strength in applying multidisciplinary domain expertise across cross-functional corporate teams and academic environments, designing and delivering end-to-end intelligence systems from device-level solutions to server-side dashboards while maintaining CI/CD pipelines.

• • As a technology advocate in the data science field, led the integration of in-house generative AI and agentic systems across multiple retail solutions.

• • Doctoral research focused on predicting disease epidemic cycles using real-time satellite imagery through computer vision, machine learning, and statistical modeling techniques.