Top Computer Vision Engineers

Fell in love with rapid advances in Computer Vision and AI, enabling the grand new applications and tools that leverage to build or invent more Neural Network architectures that can identify objects, inferring 3D geometry of scenes, understanding Emotions, Actions and Intentions. I would wish to work in a company that gives scope to enhance my knowledge and skills in Machine Learning to make products which would serve mankind.

Researcher at Oak Ridge National Lab. My primary interest are to use cameras and AI to analyze, monitor and automate complex processes. My secondary interest is using low resource machines (Raspberry Pi, Jetsons, FPGAs) to implement edge computer vision systems.

I’m a results-driven Computer Vision and Machine Learning specialist recognized for delivering groundbreaking solutions across industries—ranging from sports and physical security to gaming. Backed by patented innovations and peer-reviewed research in CV / ML, I excel at transforming complex high-level concepts into real-world applications such as markerless motion capture, multi-view multi-object tracking, 3D reconstruction, and advanced analytics. I’m passionate about mentoring teams, leveraging AI to tackle the toughest challenges, and constantly pushing the boundaries of what’s possible.

Deep Learning / Computer Vision Engineer, Linux enthusiast

A University of California PhD with concentration in image processing, computer vision, and machine learning. He has over 20 years of industrial experiences with publications and patents, which are highly cited and adapted by major institutions. He is especially skilled at developing robust algorithms that can be used in real-life systems. During early research years in the university, he developed innovative machine learning architecture that directly incorporated human knowledge with Fuzzy Logic and then refined through Neural Networks for non-linear control systems and autonomous robotic navigation. In STMicroelectronics, he developed 3D virtual view synthesis system that was robust to the depth inaccuracies from multiple wide-baseline stereovision. In JVC, he developed professional display calibration software that helped JVC venture into high-end lucrative commercial & fighter flight simulation markets, which generated hundreds of millions of dollars of new annual revenue. In Konica Minolta, he developed image stitching algorithm that rivaled the then state-of-the-art Adobe Photoshop CS6; the stitching algorithm was deployed for HDR imaging and panoramic imaging. In Nod, he developed visual-inertial motion tracking algorithm that enabled the world’s first mobile 6 Degrees-of-Freedom controllers to move in super-fast motion with high accuracy, low jitter, low latency, and instant pose re-acquisitions that was robust to the camera lens distortion, image sensor noises, fused LED blobs, extraneous environmental lighting, occlusions, unreliable IMU rates and IMU drifts; the algorithm tracked well even when the head pose wasn't piped through the camera-IMU system. He also contributed to the advancement of autonomous driving vehicles. At Xpeng, he developed lane detection and classification with deep learning networks; Lane line Stabilization with Kalman Filter; Severe Weather Classification with deep learning networks; Intelligent High Beam Control Development and integrated into the vehicle’s software stack. He further applied his algorithmic R&D and software coding skills at OPPO, where he filed 10 patents and publication. He developed innovative NIR + RGB sensor fusion that could see through fog and haze. He also productized a number of deep learning systems, such as 3D Photos, Image to Video Generation, Video Bokeh, running efficiently on cell phones. He is passionate for exploring new technological areas; he is ready to apply his AI skills in making autonomous driving & humanoid and many more deep learning systems a reality.

With extensive experience in computer vision, machine learning, and deep learning, I have honed my skills in researching state-of-the-art technologies and applying them to diverse real-world applications such as detection, segmentation, natural language processing, foundation models, and multi-modal processing. My expertise extends across various platforms including surveillance systems, robotics and cloud servers. I have a proven track record of proposing, developing, and successfully productizing cutting-edge technologies, both independently and by leading cross-functional teams.

Graduate student experienced in using different machine learning frameworks and developer’s tools. Aiming for opportunities that help me enhance and apply my skills. Course works and skills : * Computer Vision, Machine Learning, Research, Intelligent Agents and Decision making, Data structures and algorithms, Software Engineering Methods * Python, TensorFlow, Pytorch, OpenCV, Darknet, Weights And Bias, Fastai, TensoRT, version control, Swift, Atlassian tools, Swagger, AWS