Faculty
Srijith P K
Associate Professor
Department of Computer Science and Engineering
Affiliated to Department of Artificial Intelligence
My research interest lies in developing probabilistic machine learning and Bayesian data analysis techniques to solve real world learning problems. I have developed techniques based on probabilistic methods such as Gaussian processes, Differential equations, Dirichlet processes, point processes, and kernel methods to solve problems in natural language processing, information retrieval and social networks.
PhD
Siddharth Shrivastava
Department of Artificial Intelligence, IIT Hyderabad
Thesis : TBD
Research Interests:
Responsible AI
Generative AI
Vishnuprasadh Kumaravelu
IIT Hyderabad - Deakin University Joint Doctoral Program
Thesis : On Continual Learning and Domain Generalisation
Research Interests:
Continual Learning
Domain Generalisation
Machine Unlearning
Computer Vision
Prem
Prakash
Prakash
Center for Interdisciplinary Programs, IIT Hyderabad
Thesis :
Research Interests:
Astrophysics
Bayesian Statistics
Avni
Rajpal
Rajpal
External PhD from Honeywell at Dept. of Artificial Intelligence, IIT Hyderabad
Thesis : Bayesian CDAG Learning
Research Interests:
Causal Discovery
Bayesian Learning
Computer Vision
Machine Learning/Deep Learning
Dupati Srikar Chandra
IIT Hyderabad - Swinburne University of Technology Joint Doctoral Program
Thesis : Continual learning in deep neural networks
Research Interests:
Continual Learning
Domain Generalisation
Computer Vision
Deep Learning
Debolena
Basak
Department of Artificial Intelligence
Thesis : Image Captioning for Autonomous Navigation and Data Acquisition Systems
Research Interests:
Image Captioning
Natural Language Generation
Multi-task learning
Natural Language Processing
Jayashree Pougajendy
Department of Artificial Intelligence, IIT Hyderabad
Thesis :
Research Interests:
Continual Learning
Image Captioning
Computer Vision
Deep Learning
M Tech
Anubhav
Kumar
Kumar
Department of Artificial Intelligence
Research Interests:
Bayesian Deep Learning
Time Series Analysis
Natural Language Processing
Sumanta
Manna
Manna
Department of Artificial Intelligence
Research Interests:
Continual Learning
Domain Adaptation
Deep Learning
Arkaprava Majumdar
Department of Artificial Intelligence
Research Interests:
Implicit layer neural networks
Non linear dynamical systems
State Space Models
Neural Architecture Search
Vaibhav Falgun Shah
Department of Artificial Intelligence
Research Interests:
Temporal Point Processes
2D and 3D Object Detection
Domain generalization
Deep Learning
Sayanta Adhikari
Department of Artificial Intelligence
Research Interests:
Continual Learning
Machine Unlearning
Computer Vision
Explainable AI
Rishabh Karnad
Department of Artificial Intelligence
Research Interests:
Causal Learning
Bayesian Inference
Time Series Modelling
Deep Learning
Shrey Satapara
Department of Artificial Intelligence
Research Interests:
Natural Language Processing
Continual Learning
Information Retrieval
Neural Machine Translation
Alumni
PhD
Manisha Dubey
Postdoc at University of Manchester, United Kingdom
Thesis : Spatial and temporal modeling of online social networks.
Research Interests:
Probabilistic Social Network Analysis
Machine Learning / Deep Learning
Information Retrieval
Natural Language Processing
Srinivas Anumasa
Postdoc at National University of Singapore
Thesis : Neural Differential Equations : Continuous Deep learning from Differential Equations.
Research Interests:
Inference Techniques
Deep Gaussian Process
Neural Ordinary Differential Equations
Sakshi Varshney
Currently Postdoc at Alto University, Finland
Thesis : Advancing Generative Adversarial Networks for Modeling Data
Research Interests:
Deep Learning.
Computer Vision.
Generative Modelling.
Continual learning.
M Tech
Past Students
Vaibhav Singh (M.Tech, currently at Goldman Sachs, Bangalore)
Worked on convolutional Deep Gaussian Processes
Vinayak Kumar, Vaibhav Singh, P. K. Srijith, Andreas Damianou, Deep Gaussian Processes with Convolutional Kernels, Uncertainty in Deep Learning workshop at Uncertainty in Artificial Intelligence (UAI), 2018
Sherin Thomas (M.Tech, currently at Schlumberger, Pune)
Worked on Bayesian point processes for recommendation systems
Sherin Thomas, P. K. Srijith, and Michal Lukasik. 2018. A Bayesian Point Process Model for User Return Time Prediction in Recommendation Systems. In User Modeling, Adaptation and Personalization (UMAP), 2018
Shamik Kundu (M. Tech, currently at SMS data tech, Japan)
Worked on deep learnign for social media analysis
Shamik Kundu, P.K. Srijith, M. S. Desarkar. Classification of Short-Texts Generated During Disasters: A Deep Neural Network Based Approach. In FOSINT-SI at Advances in Social Networks Analysis and Mining (ASONAM) 2018.
