Aonan Zhang


Research Scientist at ByteDance
Email: aonan.zhang@bytedance.com
I'm a research scientist at ByteDance. Our Bytedance applied machine learning research team at Seattle is hiring! Feel free to contact me if you are interested in.

I finished my Ph.D at Department of Electrical Engineering at Columbia University, working with Prof. John Paisley. Before that, I finished my BS and MS at Department of Computer Science at Tsinghua University, where I was working with Prof. Jun Zhu.

My research interest lies in many perspectives in machine learning. In particular, most of my research answers when (nonparametric) Bayesian methods make sense in theory and/or in practice. Here is my CV.

Publications

A. Zhang, J. Paisley:
Random Function Priors for Correlation Modeling
International Conference on Machine Learning (ICML), Long Beach, USA, 2019 [Arxiv][Github]

A. Zhang, Q. Wang, Z. Zhu, J. Paisley, C. Wang:
Fully Supervised Speaker Diarization
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, 2019 [Arxiv][Github][Video][Official Google AI Blog]
Media reports: VentureBeat, SiliconANGLE, InfoQ, futurism, cnBeta, Sina Tech, iThome, ChinaEmail, eepw, QbitAI, oschina.

A. Zhang, J. Paisley:
Deep Bayesian Nonparametric Tracking
International Conference on Machine Learning (ICML), Stockholm, Sweden, 2018 [PDF]

S. Gultekin, A. Zhang, J. Paisley:
Asymptotic Simulated Annealing for Variational Inference
IEEE Global Communications Conference (GLOBECOM), Abu Dhabi, UAE, 2018 [PDF]

A. Zhang, J. Paisley:
Markov Latent Feature Models
International Conference on Machine Learning (ICML), New York, NY, 2016 [PDF]

A. Zhang, S. Gultekin, J. Paisley:
Stochastic Variational Inference for HDP-HMM
International Conference on Artificial Intelligence and Statistics (AISTATS), Cadiz, Spain, 2016 [PDF]

A. Zhang, J. Paisley:
Markov Mixed Membership Models
International Conference on Machine Learning (ICML), Lille, France, 2015 [PDF]

A. Zhang, J. Zhu, B. Zhang:
Max-margin Infinite Hidden Markov Models
International Conference on Machine Learning (ICML), Beijing, China, 2014 [PDF]

F. Xia, N. Chen, J. Zhu, A. Zhang, X. Jin:
Max-margin Latent Feature Relational Models for Entity-Attribute Networks
International Joint Conference on Neural Networks (IJCNN), Beijing, China, 2014 [PDF]

A. Zhang, J. Zhu, B. Zhang:
Sparse Relational Topic Models for Document Networks
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), Prague, Czech Republic, 2013. [PDF]

A. Zhang, J. Zhu, B. Zhang:
Sparse Online Topic Models
International World Wide Web Conference (WWW), Rio de Janeiro, Brazil, 2013 [PDF]

Last update: Oct 29th, 2019