A professional and innovator in deep learning and machine learning, GenAI and LLM, spanning many application fields such as computer vision, natural language processing, information retrieval, recommendation systems, vector search, self-supervised learning to solve real life challenges in the big-data world.Published several papers and holder of several patents in ML and networking/telecommunication field and the google citation link is https://scholar.google.ca/citations?user=SsokqwcAAAAJ&hl=en. Passion & Solid understanding and research over auto-ml framework, neural architecture search, model interpretability, model compression, counterfactual analysis, and optimization theories & algorithms.Expert knowledge in leveraging computing accelerators for accelerated computing, including multi-gpu mixed-precision training to 8 bit inference to save cost and reduce training/inference time.Led and Conducted projects in multiple domains, ranging from natural language understanding, computer vision to GenAI/LLM application building and deployment.Expert knowledge and experience working with machine Learning/big-data projects (e.g., pytorch/tensorflow/pyspark deep learning framework) over big-data scenarios from distributed mixed precision training to deployment.Extensive Experience in training large amounts of data using distributed GPU and cloud computing platforms on AWS & GCP cloud infrastructure.Hands-on experience with developing and managing the efficient data processing pipelines for transforming the raw data from various sources to insightful report: raw data collection, analysis and final visualization (Map-Reduce, multi process multi-threaded Python, SQL, Spark, etc).Well-rounded algorithm engineer with passion for optimization and great team player with an analytical mind and big-picture.