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Piyush Rai
PhD (University of Utah)
Associate Professor, Department of Computer Science and Engineering
Research Interest
Latent Variable Models, Probabilistic Modeling, Approximate Inference, Nonparametric Bayesian Methods
Office: KD-319, CSE Department, IIT Kanpur
Specialization
Machine Learning, Bayesian Statistics
Education
PhD, Computer Science (School of Computing, University of Utah). PhD thesis title: Learning Latent Structures via Bayesian Nonparametrics: New Models and Efficient Inference
PhD thesis supervisor: Hal Daume III
BTech, Computer Science and Engineering (IIT-BHU, Varanasi)
Teaching Area
Machine Learning
Probabilistic Machine Learning
Previous Work Experience
1. Oct 2015 - now: Assistant Professor, Department of Computer Science and Engineering,Indian Institute of Technology Kanpur
2. Oct 2015 - now: Adjunct Assistant Professor, Electrical and Computer Engineering,Duke University
3. Sept 2013 - Oct 2015: Assistant Research Professor (started as a Postdoctoral Associate), Electrical and Computer Engineering, Duke University
4. Aug 2012 - Aug 2013: Sheldon Ekland Olson Postdoctoral Fellow, Statistics and Data Sciences Dept. University of Texas at Austin
5. 2004 - 2006: Software Engineer (ST Microelectronics, Silicon Graphics)
Selected Publications
Some of the recent papers are listed below (The full list can be found on my webpage)
1. Non-negative Matrix Factorization for Discrete Data with Hierarchical Side-Information. Changwei Hu, Piyush Rai, Lawrence Carin (AISTATS 2016)
2. Topic-Based Embeddings for Learning from Large Knowledge Graphs. Changwei Hu, Piyush Rai, Lawrence Carin (AISTATS 2016)
3. Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings. Piyush Rai, Changwei Hu, Ricardo Henao, Lawrence Carin (NIPS 2015)
4. Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors. Changwei Hu, Piyush Rai, Lawrence Carin (UAI 2015)
5. Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data. Changwei Hu, Piyush Rai, Changyou Chen, Matthew Harding, Lawrence Carin (ECML 2015)
6. Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors. Piyush Rai, Yingjian Wang, Shengbo Guo, Gary Chen, David Dunson, Lawrence Carin (ICML 2014)
Awards & Fellowships
1. Best Student Paper Award at ECML-PKDD (2015)
2. National Science Foundation (USA) EAGER Award (2015)
3. Dr. Deep Singh and Daljeet Kaur Faculty Fellowship at IIT Kanpur (2015)
4. NIPS 2013 Reviewer Award for exceptional quality reviewing
5. Recipient of Sheldon Ekland-Olson Postdoctoral Fellowship from UT Austin (2012)
6. Research Excellence and Leadership Award from University of Utah (2010)
7. University Honor for Outstanding Academic Performance at IIT-BHU Varanasi (2003)