My Projects
- All
My ( Curriculum Vitae ) and the ( Resume ) are available online.
Study in Computer Science, I am an outgoing Graduate with a good team-work and competition experience. Meanwhile, I like cooking, history, swimming, running and playing soccor. I am one of the members in the SYSU and Purdue's soccor's team.
I believe technology and science can benefit the world. By the way, I hope I can have a chance for Phd position or Full-time Research Position. My personally appreciated fields may listed as follow:
Machine Learning, Artificial Intelligence, Brain Science, Quantum Computing, Learning Theory, Block Chain, Cloud Computing, Distributed/Parallel Computing, Computer Security, Life&Medical Science, Software Development.
Researching topic: Determine the feasibility of developing a cloud-based dashboard for running and monitoring pipelines in Medicine.(Advisor: Amir Bahmani, Michael Snyder)
Researching topic: Quantum Machine Learning, factoring large prime number (Advisor: Sabre Kais)
Researching topic: Graph Neural Network and Machine Learning platform (Advisor: Tiark Rompf)
Researching topic: Computer Applied Security Purdue Cerias Lab
Purdue Security Competition's Team B01lers
Software Engineer Intern: Distributed Optimize the Chemical Application with OpenMp/MPI in the Tianhe-2
(Advisor: Yunfei Du)
Researching topic: Generative Adversarial Imitation Learning
Researching topic: Multidomain's improvement of Cycle Generative Adversarial Network (Advisor: Liang Lin)
Researching topic: A traffic prediction platform / Htcondor platform. (Advisor: Zibin Zheng)
Jobs:
(1)Take part in the installation of hadoop environment
(2)Set up the high throughout distributed platform.
ICML 2020
* indicates equal contribution
[1] MMI-ALI: Multivariate-Information Adversarial Ensemble for Scalable Joint Distribution Matching
Ziliang Chen*, Zhanfu Yang*, Xiaoxi Wang*, Xiaodan Liang, Xiaopeng Yan, Guanbin Li, Liang Lin. [cite]
In Proceedings of the Thirty-sixth International Conference on Machine Learning (ICML 2019) [1] Graph Neural Reasoning for 2-Quantified Boolean Formula Solvers Zhanfu Yang, Fei Wang, Ziliang Chen, Guannan Wei, Tiark Rompf.[cite] In Proceedings of the Thirty-sixth ICML Workshop for Learning and Reasoning with Graph-Structured Data (ICML 2019 Workshop) [1] Custimizing Graph Neural Reasoning to solve 2-Quantified Boolean Formula Zhanfu Yang*, Fei Wang*, Ziliang Chen*, Guannan Wei, Liang Lin, Tiark Rompf. [1] PurPL Seminar (2019.Sep.20). Titile: Machine Learning in 2QBF.
Topic: CTF, Cryptography, SQL injection and DNS spoofing
Topic: Run our parallel optimized program in a platform within 3000W for high performance.
Jobs: Instruct for the system, archetecture and application.
Topic: Develop a Blockchain application base on the linuxONE platform
Jobs: Build up the system base on the linuxONE and develop the chaincode.
Topic: Develop parallel application base on the domestic cpu platform
Jobs: BUild up the platform and optimize part of the code.
Topic: Run our parallel optimized program in a platform within 3000W for high performance.
Jobs:
(1)Building cluster and install system
(2)Improved the achitecture, network with RDMA and test for HPL and HPCG.
(3)The parallel optimization program about Wave’s model(MPI,openMP).
(4)The deep learning program about PaddlePaddle’s traffic model(python, cuda).
Topic: A simulation program in the pre experiment of bacterial culture
Jobs: Data collection and analysis, algorithm optimization.
Topic: Run our parallel optimized program in a platform within 3000W for high performance.
Jobs:
(1)Building cluster and install system
(2)Improved the achitecture, network with RDMA and test for HPL and HPCG.
Topic: Metro Advice Service base on big data.
Jobs:
(1)Use GPU with CUDA for parallel acceleration.
(2)Optimize the algorithm model.
