Lead a team to research and develop smart solutions using Video Analytics and Generative A.I. technologies such as Visual Question Answering, Vision Language Modeling, and LLM.

Lead a team of researchers and engineers to research an develop video analytic models and products and participate in multi-million dollar projects.

Develop machine learning algorithms to classify customer feedback and generate configuration rules for product offerings.

Apply machine learning algorithms and statistical analysis to gain insight from medical data.Involved analytic skills:- Apply machine learning algorithms to model patients and predict patients' behaviors.- Apply Natural Language Processing algorithms on data from academic publications, clinical trials, and social networks to identify Key Opinion Leaders of interested medical domains.- Perform statistical analysis on data from a sleep monitoring device.Involved technical skills: R, Python, MongoDB, web and social network crawling.

Lead researcher working on the algorithm engine for augmented reality applications with real-world 3D objects (using OpenCV and C++).Involved experiences: augmented reality, 3D tracking, vision-based localization, 3D reconstruction, SLAM, image recognition.

Lead algorithm engineer working on algorithms related to video analytic and computer vision for next generation products. Most implementations are done using C/C++; some experiments are done using MATLAB; working environments are Windows and Linux.Involved experiences: 3D tracking, gesture recognition, depth (stereo, time-of-flight) video analytic, face recognition, face/facial feature tracking, human/object tracking, background subtraction, image enhancement.

Research on 3D facial expression recognition and 3D indoor reconstruction using multiple images (using Matlab, C/C++).Involved experiences: 3D face and facial expression recognition.

Research on computer vision, statistical modelling and pattern recognition, with focuses on recognizing facial expressions and head motions. Experiments were done using MATLAB and OpenCV. Research topics include:■ Detect face and facial features in video using AdaBoost, Gabor Filter, and Support Vector Machine.■ Track facial features with a novel scheme combining Kanade-Lucas-Tomasi tracking algorithm and Probabilistic Principal Component Analysis.■ Segment and recognize head motions and facial expressions in video sequences using Hidden Markov Model, Support Vector Machine, and Layered Conditional Random Field model.