Priyank Jaini bio photo

Priyank Jaini

Fourth Year Ph.D. Student
Artificial Intelligence Lab
University of Waterloo

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Introduction


Hello! I am a fourth year doctoral student at the Artificial Intelligence Lab, David R. Cheriton School of Computer Science at the University of Waterloo under the co-supervision of Prof. Pascal Poupart and Prof. Yaoliang Yu. I am also affiliated with the Waterloo Artificial Intelligence Institute and the Vector Institute.

I am the recepient of the Cheriton Scholarship (2017-2019), Borealis AI Fellowship (2019), and the Huawei Graduate Fellowship in Artificial Intelligence (2019).

My research interests are broadly in the area of

  • Machine Learning : Deep Generative Modes, Tensor Decompositions, Mixture Models, Probabilistical Graphical Models, Sum-Product Networks, Online Learning, Bayeisan Learning, Optimization
  • Health Informatics : Assistive Technologies and Behaviour Recognition
  • Computational Neuroscience : Task-Specific Natural Scene Statistics

Please check out my research page for more details.

Recent News
  • April 2017 : PhD Seminar 2 completed. I talked about an online Bayesian transfer learning algorithm for sequential data modeling. I also talked about the application of the algorithm on three real world problems of activity recognition, sleep stage classification and network traffic prediction. [slides]
  • April 2017 : Linking Normative Models of Natural Tasks to Descriptive Models of Neural Response has been submitted to the Journal of Vision.
  • February 2017 : Online Bayesian Transfer Learning for Sequential Data Modeling has been accepted at the 5th International Conference on Learning Representations (ICLR 2017) to be held in Toulon, France.
  • January 2017 : Linking Normative Models and Methods for Neural Systems Identification has been accepted at Computational and Systems Neuroscience (COSYNE), 2017.
  • December 2016 : Accuracy Maximization Analysis for Natural Tasks and Principles of Multiplicative Noise and Filter Correlation in Neural Coding has been accepted at Public Library of Science (PLoS) Computational Biology.
  • November 2016 : Accuracy Maximization Analysis with Class-conditional Gaussians : Linking Normative and Descriptive Quadratic Models of Neural Response has been submitted to PLoS Computational Biology.
  • November 2016 : Received Huawei Noah's Ark Lab Distinguished Collaborator Award 2016 along with Pascal Poupart (Principal Investigator) for outstanding contributions in the joint Huawei-Waterloo research project.
  • November 2016 : Online Bayesian Transfer Learning for Sequential Data Modeling has been submitted to the 5th International Conference on Learning Representations (ICLR 2017).
  • October 2016 : PhD Seminar 1 completed. I talked about online and distributed Bayesian Moment Matching algorithm for Gaussian Mixture Models and its application to Sum-Product Networks with Continuous Variables. [slides]
  • July 2016 : Online Algorithms for Sum-Product Networks with Continuous Variables has been accepted at the International Conference on Probabilistic Graphical Models (2016) to be held in Lugano, Switzerland from September 06 - September, 09. [pdf]
Education and Past Work

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