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Zejia_CV_final

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Zejia_CV_final

  1. 1. ARTIFICIAL INTELLIGENCE | MACHINE LEARNING| DEEP LEARNING NEURAL NETWORKS | MATHEMATICAL MODELING | PROGRAMMING SKILLS | COMMUNICATIVE SKILLS KEY ACCOMPLISHMENTS • Recognized expertise in Artificial Intelligence, Machine Learning, Algorithms Design and Analysis, and Mathematical Modeling. • Experienced in deep learning networks, Stacked Auto-encoders, Convolutional Neural Networks and hierarchical visual cortex models for image classification and object recognition. • Expert in state based reinforcement learning concepts, mechanisms, and techniques, and on-line learning neural network based neuromodulatory system design for reinforcement learning. • Skilled in Android application programming, mobile application user interface design, mobile device based image classification systems design, and mobile device based machine learning algorithm implementation. • Proficient with mainstream modern deep learning packages (e.g. Tensorflow, Caffe and cuda-convnet), programming tools (e.g. CUDA, OpenCV, OpenGL and OpenCL) and Unity simulation. ACADEMIC BACKGROUND • Ph.D. in Computer Science (GPA: 3.84)• Michigan State University, USA • 2012-present § Advisor: Juyang (John) Weng § Specialization: Cognitive Science § Research Interests: Artificial Intelligence, Machine Learning, and Neural Networks § Expected graduation date: April, 2017 • Bachelor of Science in Mathematics and Applied Mathematics • Fudan University, China • 2008-2012 § Advisor: Jin Cheng § Dissertation: Convergence Properties of the Algebraic Reconstruction Technique and its Application RESEARCH/SCHOLARLY ACTIVITIES PUBLICATIONS • Zheng, Z. and Weng, J. “Mobile Device Based Outdoor Navigation With On-line Learning Neural Network: a Comparison with Convolutional Neural Network”. IEEE Conf on Computer Vision and Pattern Recognition Workshop (CVPRW). June 2016. • Zheng, Z. and Weng, J. “Challenges in Visual Parking and How a Developmental Network Approaches the Problem”. International Joint Conference on Neural Networks (IJCNN), July 2016. • Zheng, Z., He, X, and Weng, J. “Approaching Camera-based Real-World Navigation Using Object Recognition”. INNS BigData International Conference, Aug 2015. • Zheng, Z., Li, Z., Nagar, A. and Park, K. “Compact Deep Neural Networks for Device Based Image Classification”. IEEE Int’l Conf on Multimedia & Expo Workshop (ICMEW), July 2015. • Zheng, Z., Li, Z., Nagar, A. “Compact Deep Neural Networks for Device Based Image Classification”. Mobile Cloud Visual Media Computing: From Interaction to Service: 201-217, Springer, July 2015. • Zheng, Z., and Weng, J. “Approaching Real-World Navigation Using Object Recognition Network”. International Joint Conference on Neural Networks (IJCNN), June 2015. • Zheng, Z., Weng, J., & Zhang, Z. WWN: Integration with coarse-to-fine, supervised and reinforcement learning. In Neural Networks (IJCNN), 2014 International Joint Conference on (pp. 1517-1524). IEEE. July 2014. • Zheng, Z., Qian, K., Weng, J., & Zhang, Z. Modeling the effects of neuromodulation on internal brain areas: Serotonin and dopamine. In Neural Networks (IJCNN), The 2013 International Joint Conference on (pp. 1-8). IEEE. August 2013. • Zheng, Z. & Weng, J. “Comparison between WWN and Some Prior Networks” International Conference on Brian Mind (ICBM) June 2013. • Zheng, Z., Kui, Q., Weng, J. & Zhang, Z. “Reinforcement in Internal Areas, Coarse-to-Fine Motors, and Integration with Supervised Learning” Transaction on Autonomous Mental Development (Working paper). Z E J I A Z H E N G 1870 E Shore Dr., Apt C2 East Lansing, MI 48823 Tel.: 517.703.4794 Email: zhengzej@msu.edu Blog: zejiazheng.com
  2. 2. RESEARCH EXPERIENCE • ZOOX (Stealth mode robotics startup) • Summer Intern • Supervisor: Paulius Micikevicius • 2016.5-2016.9 § Worked with Zoox Computer Vision Group, lead by James Philbin. § Designed and programmed Zoox Deep Learning Inference Engine for autonomous driving systems. § Studied GPU memory allocation and deallocation mechanisms for pre-trained deep learning neural networks; Inference Engine is currently being used as a standard for real-time neural network deployment on Zoox vehicles; it saves more than 40% GPU memory required to run inference with modern deep neural network architectures (e.g. VGG variants, Inception net, etc.) compared to Caffe’s approach. • Samsung Research America • Summer Intern • Advisor: Dr. Zhu Li • 2014.5-2014.8 § Worked with Compact Descriptor for Visual Search Group. § Constructed compact deep convolutional neural network for mobile device based image recognition. § Minimized memory footprint of device based image classifier by 32% compared to typical convolutional neural network; developed efficient contribution evaluation method for classifier kernels; network recognizes single image within 0.1 sec on mobile devices. • Embodied Intelligence Laboratory • Michigan State University • Advisor: Dr. Juyang (John) Weng • 2012-present § Designed online learning mobile agent that learns to navigate in real-world environment with real-time attention modeling. § Programmed Android application for outdoor navigation. The system navigates successfully around campus using built-in camera and GPS, with the ability of direction correction and obstacles avoidance. System learns to recognize objects and transfer learned concepts to unfamiliar environments. § Constructed reinforcement learning modules under the framework of Developmental Network; simulated the effect of neurotransmitters in inner brain areas; network learns to navigate in simple maze without human supervision. § Utilized an instructional scaffolding learning scheme to train multi-concept learning agents from single concept learning agent; reduced manual labeling in supervision by over 80%; Agent learns to refine concept of location according to its interaction with external environment. § Research supported by Microsoft Research, Redmond • Information Science Laboratory • Fudan University • Advisor: Dr. Peizhong Lu • 2011-2012 § Developed novel clock synchronization algorithm for wireless sensor networks. § Applied parameter estimation techniques to large time stamp data collected from wireless sensor network. § Constructed simulation platform for pairwise synchronization and network wide synchronization. • Research Center of Nonlinear Sciences • Fudan University • Advisor: Dr. Wei Lin • 2010-2011 § Evaluated patient diagnosis report using statistical correlation and time series analysis models. § Analyzed Hemodialysis results with belief propagation network. § Collected data to improve evaluation results at Huashan Hospital, Shanghai. PROFESSIONAL HONORS AND AWARDS • Second Prize at China Undergraduate Mathematical Contest in Modeling • Paper: Pollution Analysis and Prediction Based on Neural Networks • Sep 2012 • Outstanding Undergrad Scholarship of Fudan University • 2011-2012 • Second Prize at Huadong Cup, the 12th Mathematical Modeling Contest for Undergraduates (ranked 4th out of 640 teams) • Paper: Mathematical Analysis and Modeling for Elevator Scheduling • Apr 2010 • Fudan Scholarship for Fundamental Sciences • 2009-2011 RELEVANT EXPERIENCE CONTRACTED STATISTICIAN Geosun Illumination Co. – Ningbo, China Jan 2012-May 2012 • Designed and led construction of long term employee performance database using SQL for 200 sales representatives. • Developed a novel employee long term performance rating system through analysis of the ELO chess-player rating system. TEACHING ASSISTANT Computer Science and Engineering- Michigan State University SS2015, FS2014 and SS2014 • CSE 331 Data Structure and Algorithm. Designed programming projects for the course. Grading and office hour instructions and support. • CSE 260 Discrete Mathematics. Lecture and discussion for undergraduate students. Z E J I A Z H E N G Page 2
  3. 3. TECHNICAL SKILLS • Programming: • C/C++ • Matlab • Python • JAVA • Android • Unity • Libraries/Tools: • LATEX • Qt4 • Matlab/Python/JAVA GUI Design • CUDA programming • OpenGL • OpenCV REFERENCES • Dr. Juyang (John) Weng, Computer Science and Engineering • Michigan State University, East Lansing, MI 48824 • phone: 517.353.4388 • email: weng@cse.msu.edu • Dr. Fathi Salem, Electrical and Computer Engineering • Michigan State University, East Lansing, MI 48824 • phone: 517.355.7695 • email: salem@egr.msu.edu • Dr. Eric Torng, Computer Science and Engineering • Michigan State University, East Lansing, MI 48824 • phone: 517.353.3543 • email: torng@cse.msu.edu • Dr. Zhu Li, Compact Descriptor for Visual Search Group • Samsung Research America, Richardson, TX 75082 • email: zhu1.li@samsung.com • Dr. Wei Lin, School of Mathematical Science • Fudan University, Shanghai, China 200433 • phone: +86.021.55665141 • email: wlin@fudan.edu.cn Z E J I A Z H E N G Page 3

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