Junhao Hua

PhD student at ZJU

My academic website has much more information.

Bio. I am currently a PhD Student at College of ISEE, Zhejiang University, China, working with Chunguang Li on Variational Bayesian Algorithms and their applications in Distributed Systems.
Research interests

My Ph.D research work covers a range of issues: variational Bayesian inference, stochastic / distributed optimization, probabilistic graphical models, transfer learning, multitask learning and sensor networks.

Currently, I am interesting in varies approaches to deep learning (CNN, GAN, Deep Bayesian Learning, etc.) and their applications to computer vision (image processing, video analysis, etc.).

On a side for fun I maintain several Projects (e.g. ActionRecognition, AgeEstimation, VBClusterings, UnixFileSystem).

Education & Experience.

  • 2013 - now: Ph.D. student, Circuits and Systems, Zhejiang University. Adviser: Chunguang Li.
  • Summer 2012: C/C++ Engineer Internship at State Stree(Hangzhou).
  • 2009-2013: Bachelor's Degree, double major in Computer Science and Automation, Zhejiang University of Technology. Adviser: Shengyong Chen.
Publications [Google scholar]

  • Junhao Hua, Chunguang Li, Distributed Variational Bayesian Algorithms for Robust Kalman Filtering over Networks, submitted to IEEE Transactions on Signal and Information Processing over Networks.
  • Junhao Hua, Chunguang Li, Distributed Variational Bayesian Algorithms for Extended Object Tracking, submitted to IEEE Transactions on Aerospace and Electronic Systems.
  • Junhao Hua, Chunguang Li, Distributed Jointly Sparse Bayesian Learning with Quantized Communication, IEEE Transactions on Signal and Information Processing over Networks, accepted，2018.
  • Junhao Hua, Chunguang Li, Hui-Liang Shen, Distributed Learning of Predictive Structures from Multiple Tasks Over Networks, IEEE Transactions on Industrial Electronics(TIE), preprint, DOI: 10.1109/TIE.2016.2588463.
  • Junhao Hua, Chunguang Li, Distributed Variational Bayesian Algorithms over Sensor Networks, IEEE Transactions on Signal Processing (TSP), vol.64, no.3, pp.783-798, Feb. 2016.