Chaoyang He (何朝阳) Ph.D. Student in Computer Science University of Southern California, Los Angeles, USA Team Manager and Staff Engineer at Tencent (2014-2018) Senior Software Engineer at Baidu (2012-2014) Email: chaoyang.he@usc.edu me@chaoyanghe.com

Chaoyang He is a Computer Science Ph.D. student focusing on Machine Learning at University of Southern California, Los Angeles, USA. Previously, he was an R&D Team Manager and Principal Engineer at Tencent (2014-2018), a Team Leader and Senior Software Engineer at Baidu (2012-2014), and a Software Engineer at Huawei (2011-2012).

Currently, his academic advisors are Professor Salman Avestimehr (USC, machine learning theory, distributed computing), Murali Annavaram (USC & Facebook, machine learning system, computer architecture), and Tong Zhang (HKUST, machine learning optimization)

He has a strong background in Internet industrial level computer science, including cloud computing architecture, machine learning, and data computing platform, distributed systems, mobile computing, and embedded operating system. He has more than three years of experience in Internet R&D management, leading a team with 10-20 software engineers and researchers to build commercial Internet products. The Internet Products that he worked for include Tencent Cloud, Tencent AI in Car (WeChat Automotive), Tencent Games, Tencent Maps, Baidu Maps, and Huawei Smartphone.

His primary research research is machine learning algorithms, models, systems and related applications in Computer Vision, Natural Language Processing, and Data Mining (Transportation, Games, Finance, Health Care, etc.). He is particularly interested in large-scale machine learning problems:

• Decentralized learning, distributed learning, federated learning
• Automated machine learning (AutoML), neural architecture search (NAS)
• Large-scale graph neural networks (million level graph nodes)
• On-device deep learning, model compression
• Computer vision: visual relationship detection (VRD)
• Different learning paradigms: Multi-Task Learning/Transfer Learning, GAN/VAE, Reinforcement Learning, Unsupervised/Semi-supervised Learning, etc.
• Large-scale distributed machine learning system
• Machine learning theory, convex/non-convex optimization
• Any AI-related Mathematics and complex computer systems

Papers

• FedNAS: Federated Deep Learning via Neural Architecture Search
  Chaoyang He, Murali Annavaram, Salman Avestimehr
  Preprint, 2020
[bib] [arXiv]
Keywords: AutoML, Neural Architecture Search, Federated Learning, Computer Vision


• Bipartite Graph Neural Networks for Efficient Node Representation Learning
  Chaoyang He^*, Tian Xie^*, Yu Rong, Wenbing Huang, Yanfang Li, Junzhou Huang, Xiang Ren, Cyrus Shahabi
  2020

        @article{he2019bipartite,
          title={Bipartite Graph Neural Networks for Efficient Node Representation Learning},
          author={He, Chaoyang and Xie, Tian and Rong, Yu and Huang, Wenbing and Li, Yanfang and Huang, Junzhou and Ren, Xiang and Shahabi, Cyrus},
          journal={arXiv preprint arXiv:1906.11994},
          year={2019}
        }
    

[bib] [arXiv]
Keywords: Graph Neural Networks, Self-supervised Learning, Adversarial Learning, Efficient Neural Architecture


• Central Server Free Federated Learning over Single-sided Trust Social Networks
  Chaoyang He, Conghui Tan, Hanlin Tang, Shuang Qiu, Ji Liu
  Preprint, 2020

        @article{he2019central,
          title={Central server free federated learning over single-sided trust social networks},
          author={He, Chaoyang and Tan, Conghui and Tang, Hanlin and Qiu, Shuang and Liu, Ji},
          journal={arXiv preprint arXiv:1910.04956},
          year={2019}
        }
    

[bib] [arXiv]
Keywords: Distributed Machine Learning, Convex Optimization, Federated Learning, Online Learning


• MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation
  Chaoyang He^*, Haishan Ye^*, Li Shen, Tong Zhang
  To appear in CVPR 2020 (IEEE/CVF Conference on Computer Vision and Pattern Recognition 2020)

        @inproceedings{MiLeNAS,
          title={MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation},
          author={He, Chaoyang and Ye, Haishan and Shen, Li and Zhang, Tong},
          booktitle={Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
          year={2020},
        }
    

[bib] [arXiv]
Keywords: Neural Architecture Search, AutoML, Machine Learning Optimization, Computer Vision.


• Advances and Open Problems in Federated Learning
  Peter Kairouz, H Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Keith Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael GL d'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adria Gascón, Badih Ghazi, Phillip B Gibbons, Marco Gruteser, Zaid Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konečný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrede Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X Yu, Han Yu, Sen Zhao
  To appear in Foundations and Trends in Machine Learning (FnTML), 2019

        @article{kairouz2019advances,
          title={Advances and open problems in federated learning},
          author={Kairouz, Peter and McMahan, H Brendan and Avent, Brendan and Bellet, Aur{\'e}lien and Bennis, Mehdi and Bhagoji, Arjun Nitin and Bonawitz, Keith and Charles, Zachary and Cormode, Graham and Cummings, Rachel and others},
          journal={arXiv preprint arXiv:1912.04977},
          year={2019}
        }
    

[bib] [arxiv]
with Google AI, Seattle, WA, USA


• Collecting Indicators of Compromise from Unstructured Text of Cybersecurity Articles using Neural-Based Sequence Labelling
  Zi Long, Lianzhi Tan, Shengping Zhou, Chaoyang He, Xin Liu
  International Joint Conference on Neural Networks (IJCNN), 2019

        @inproceedings{long2019collecting,
          title={Collecting Indicators of Compromise from Unstructured Text of Cybersecurity Articles using Neural-Based Sequence Labelling},
          author={Long, Zi and Tan, Lianzhi and Zhou, Shengping and He, Chaoyang and Liu, Xin},
          booktitle={2019 International Joint Conference on Neural Networks (IJCNN)},
          pages={1--8},
          year={2019},
          organization={IEEE}
        }
    

[bib] [arxiv]
Keywords: Natural Language Processing, Attention-based Bi-LSTM


• ADMSv2: A Modern Architecture for Transportation Data Management and Analysis
  Chrysovalantis Anastasiou, Jianfa Lin, Chaoyang He, Yao-Yi Chiang, Cyrus Shahabi
  SIGSPATIAL Workshop 2019

        @inproceedings{anastasiou2019admsv2,
          title={ADMSv2: A Modern Architecture for Transportation Data Management and Analysis},
          author={Anastasiou, Chrysovalantis and Lin, Jianfa and He, Chaoyang and Chiang, Yao-Yi and Shahabi, Cyrus},
          booktitle={Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances on Resilient and Intelligent Cities},
          pages={25--28},
          year={2019}
        }
    

[bib] [paper]
Keywords: System Architecture Design, TensorFlow/PyTorch, Spark, HIVE, Node.JS, MongoDB

Technical Report

(If you are interested in the following topics, please email me to discuss the potential collaboration.)
• 2018 - Data-Driven Cloud Computing Platform and Machine Learning System for the Internet of Vehicles
• 2016 - The Large-Scale Distributed System and Real-Time Location Data Mining
• 2017 - TAI: An Intelligent Operating System and Open Platform
• 2016 - Speech Recognition System for Connected and Autonomous Driving Car
• 2016 - WeGameMap: Real World Map Rendering Engine for Location-Based Mobile Game
• 2015 - WeLink: a High-Performance Vehicle-Mobile Networking Library
• 2014 - TMAP: A System Framework for Mobile Maps and Navigation
• 2016 - Efficient Spatial Anti-Aliasing Rendering for Line Joins on Vector Maps
• 2014 - WeCross: a Mobile and Vehicle C/C++ Cross-Platform Library
• 2017 - A High Precision Private Car Trajectory Dataset and an Open Source Location Data Computing Platform
• 2017 - A Open Source High Reliable Location SDK for the Automotive Industry
• 2013 - The First Generation Mobile Navigation SDK Design in China
• 2012 - Map State Switching under Multi-trigger Condition Based on Finite State Machine Design Pattern
• 2012 - A General Downloader Engine for iOS/Android Platform
• 2012 - The Best Practice for Java Native Interface (JNI) Development on Android Operating Platform
• 2014 - Taxi-Calling Platform and the Open Source Code
• 2015 - A UX design of Bluetooth Steering Wheel Wireless Controller and the communication system design
• 2016 - Sliding Window Algorithm Template to Solve All the Leetcode Substring Search Problem.

Patents

(Published when I was at Tencent, Baidu, and Harbin Institute of Technology; Citations: 20+)
• Method for recognizing semantics, device storage medium and electronic device
  Patent number: CN109933774A
• A kind of voice recognition processing method and device
  Patent number: CN107293294A
• The data-pushing of vehicle cloud platform, treating method and apparatus
  Patent number: CN108833489A
• Method and apparatus for playing instant message sound on vehicle-mounted terminal
  Patent number: CN105530171A
• Resource obtaining method, terminal and vehicle terminal
  Patent number: CN105610978A
• Information interaction method and vehicle terminal
  Patent number: CN105791395A
• A kind of application development method, device, equipment and development frame
  Patent number: CN107179916A
• The rendering method and device of map, storage medium, electronic device
  Patent number: CN109544658A
• Selective recording method after realizing break-in of dispatching console in digital cluster system
  Patent number: CN101969444A

• The cities that I have lived for more than one year: Los Angeles, Shenzhen, Beijing, Wuhan, and Harbin. I expect to live more places in my life!
• The Startup, Investment, Research are three most thrilling uncertainty of humans and nature in this world. Enjoy!
• Whenever I am not thinking about research, I enjoy most of the outdoor activities and also spend a lot of time in English reading.
• I have a lovely daughter.
• Facebook: WeChat: