Résumé/CV

Data scientist and technical leader specialized in Deep Learning 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 project Tech Lead, led the deployment of iOS/Android efficient and React-supported deep learning models on IoT/edge devices for the recognition of over a million items at Walmart.

• • Have deep domain knowledge and hands-on experience with advanced ML/DL architectures, such as Generative Adversarial Networks (GANs), Segment Anything series, YOLO series, CLIP, Grounding DINO, Transformers, etc., in the Retail Industry.

• • Doctoral research focused on predicting disease epidemic cycles using real-time satellite images, such as Planet, LandSat, MODIS, and mathematical models like TabNet, LASSO (causal inference), and LSTMs.

• • Proficient in Python (also in PyTorch and TensorFlow), C, and GoLang; designed end-to-end processes from image capture to processing, including dashboard integration with maintaining CI/CD pipelines.

• • Possesses a unique strength in adopting multidisciplinary techniques in cross-functional corporate and academic settings.

• • Supported large-scale projects with modeling expertise in deploying satellite- and drone-based projects for agricultural operations, mentoring junior team members, and teaching programs at universities like Purdue University .