Chen Li Email & Phone Number

A Computer Science concentrated in Machine Learning At Columbia Unversity. Received Bachelor of Sciences, Mathematics for Computation at University of California, Los Angeles, I received extensive training in constructing mathematical models and using computer simulations to deal with real-world problems. At the same time, I took a large number of computer science courses and I have been involved in research in the university's artificial intelligence lab since my junior year. Coursework:-- Linear Algebra, Real Analysis Honor, Complex Analysis, Discrete Math, Numeric Methods, Multivariable Calculus, Differential Equations- Computer Orginazation, Operation System, Statistical Models, Programming Languages, Data Structure, Computer Graphics, Algorithms&ComplexityExperience:-- Machine Learning Research Intern Laboratory for Sustainable Additive Manufacturing- Data Analysis Intern PARISlab@UCLA- Cloud Computing Summer Research Camp

• Machine Learning Research Intern

  Laboratory For Sustainable Additive Manufacturing

  Aug 2020 - Present - Los Angeles County, California, United States

  Current Project with California Department of Transportation:-• Lead development of a program using point clouds to supervise flow of multiple types of traffic on California highways. • Train and Compar effect of several point cloud objection detection models on KITTI dataset. • Investigate creation of KITTI dataset and developguideline of dataset for project based on Velodyne LidarMachine Learning-based Real-time Monitoring System for Smart Connected Worker to Improve Energy Efficiency:• Led construction of a system to monitor working state of 3D printers in real time. • Directed team through entire process from collecting training data to deploying model to Jetson Nano. • Programmed a TensorRT-based object detection model and achieved a mean Average Precision at 0.5 of 0.97 for motiondetection of three main components inside printer at a FPS around 40 on Jetson Nano. • Summarized work as part of Machine Learning-based Real-time Monitoring System for Smart Connected Worker to ImproveEnergy Efficiency, published in Journal of Manufacturing Systems.