Yurong Chen

Leading AI Research Lab at Intel Labs China, responsible for driving cutting-edge research on core AI algorithms and tech innovations in efficient AI model development and optimization tools to advance Intel AI SW/HW platforms and solutions from Client/Edge to Cloud.

Led Vision & AI Lab at Intel Labs China, responsible for driving research innovation in cutting-edge visual AI and mainstream/next-gen AI technologies to advance Intel AI SW/HW platforms & solutions from Edge/Client to Cloud.

Led Cognitive Computing Lab at Intel Labs China, responsible for driving cognitive computing, especially visual cognition including visual analytics and understanding and machine learning research for Intel next-generation platforms. He is also the co-owner of Intel Labs “Visual Understanding and Synthesis” program, driving research innovation in smart visual data processing technologies on Intel platforms across Intel Labs.

Led Cognitive Computing Lab at Intel Labs China to drive leading cognitive computing, especially, visual analytics and understanding research for Intel next-generation platforms.

Led Application Research Lab at Intel Labs China to drive application research and Joint Path-finding in the area of applications with Intel business units.

Led the facial gesture tracking SDK development and 3D avatar model generation/animation for an internal venturing project for Intel first mobile chat app Pocket Avatars (officially launched in June 2014). Built the team in a short time, well defined the developing process, drove high productivity to hit key milestones, which resulted in a successful PA technology transfer to Intel BU for productization.

Conducted embedded benchmarking and workload analysis research. Led the Embedded Benchmark suite (EBench) development and release work to support embedded system research (ESR). Delivered 2 versions of EBench which can drive embedded architecture design.Led the team to successfully deliver the first set workloads for SmartTVmark & report system level analysis on the Intel CE4100 platform. Conducted workload analysis and advanced visual analytics (VA) app driven system SW/HW acceleration research for IA platforms. Explored opportunities for embedded vision app prototyping and related core technologies (algo, HW/SW system & interface) research.

Led the 3D content creation project for immersive connected experience. Led the team to successfully deliver the state-of-the-art 3D content generation research results and prototype system. Showed “3D Model Creation for Amateurs” demo with incremental results in IDF Beijing, R@I day, IDF San Francisco, ILC Open Day and Intel China Innovation Day, respectively. The demo got well received by the industrial, academic and internal audience including CTO and some Intel Fellows. The team also published an oral paper in CVPR 2010.

Led a team to release and maintain the Model-based Computing Benchmark suit (MCBench), and supported users across & outside Intel (PARSEC) to influence the evolution of multi/many-core systems. Delivered a set of video feature extraction workloads and conducted performance analysis. Optimized 12+ video feature extraction algorithms with generic, SIMD and cache-conscious optimization techniques and parallelized 6+ most compute intensive ones by extracting thread-level parallelism. Conducted media/video mining workload analysis for future many-core architectures. Summarized emerging media/video mining applications and their representative workloads for future many-core systems and conducted cycle accurate simulation based analysis with team members.

Performed parallel computing, performance analysis and workload characterization research in many application domains such as data mining in bioinformatics, game-tree search, text mining, audio search and content-based video information retrieval.

Conducted postdoctoral research on large-scale scientific computing, unstructured grid generation software for petroleum reservoir simulation and parallel computing in the Parallel Computing Lab.

Worked as a key member to research fast methods and their efficient implementation for solving the power flow equations in a subproject of the National “973” Project on power system stability. Researched numerical methods for solving large-scale nonlinear equations in an NSF key project. Published 5 papers (2 SCI, 3 EI) and got 3 first prize scholarships and 2 professional scholarships. Worked as a student assistant, and a head of youth league.

Worked as a student assistant, a head of youth league and a student group leader.