Bayesian Reasoning And INtelligence (BRAIN)

Welcome to the web page of Bayesian Reasoning And INtelligence (BRAIN) research group associated with the Computer Science and Engineering and Artificial Intelligence Departments at Indian Institute of Technology Hyderabad. Our research group works on probabilistic machine learning and deep learning models to solve problems arising in the domain of artificial intelligence such as natural language processing and computer vision. We bring advances in AI by developing learning algorithms based on Deep learning, large language models, Bayesian learning, continual learning, causal learning, multimodal learning, stochastic processes and differential equations. We also work on using ML to solve problems arising in application areas such as social networks, event logs, astrophysics, fluid dynamics, sustainability, healthcare, and mobility.

News

Paper by Preethi G on Pseudo-Inverse Prefix Tuning for Effective Unlearning in LLMs accepted at CIKM 2025.
Paper by Arkaprava Majumdar on Neural Wave Equations for Irregularly Sampled Sequence Data accepted at ICLR 2025.
Co-organized the Continual Causal Bridge program at AAAI 2025. More details here.
Paper by Srikar Dupati on Linked Adapters: Linking Past and Future to Present for Effective Continual Learning accepted at PAKDD 2025
Paper by Sayanta Adhikari on AdaPrefix++: Integrating Adapters, Prefixes and Hypernetwork for Continual Learning accepted at WACV 2025.
Paper by Vishnuprasadh Kumaravelu on EvoCL: Modelling Continual Learning over Evolving Domains accepted at WACV 2025.
Paper by Vaibhav Shah on Drift-aware Neural Hawkes Process for Time-to-Event Modelling accepted at CODS-COMAD 2024.
Paper by Shrey Satapara on TL-CL: Task And Language Incremental Continual Learning accepted at EMNLP 2024.
Paper by Manisha Dubey on HyperHawkes : Time-to-Event Modeling with Hypernetwork based Hawkes Process accepted at KDD 2023.
Paper by Srinivas Anumasa on Continuous Depth Recurrent Neural Differential Equations accepted at the ECML-PKDD 2023.
Manisha Dubey successfully defends her thesis on Improving Spatio-temporal modeling with Hawkes process . Congratulations !
JICA funding for the Causal Inference project in colloboration with Dr. Emtiyaz Khan from RIKEN-AIP, Japan.
Srinivas Anumasa successfully defends his thesis on Continuous Deep Learning with Neural Differential Equations. Congratulations !
Sony Research Award on Continual Learning. Research positions available at all levels, interested students/researchers may contact.
Co-organizing the 14th Asian Conference on Machine Learning (ACML) 2022 in Hyderabad, India. More details here
SERB funding for the project on continual learning for vision and language. Ph.D., M.Tech (RA) and Project Assistant positions available ! Students interested in long term internship may also contact.
Paper by Srikar Dupati on Continual Learning with Dependency Preserving Hypernetworks accepted at WACV 2023.
Sakshi Varshney successfully defends her thesis on Advancing Generative Adversarial Networks for Modeling Data. Congratulations !
Paper by Manisha Dubey on Hawkes Process Classification through Discriminative Modeling of Text accepted at IEEE IJCNN 2022.
Paper by Srinivas Anumasa on Latent Time Neural Ordinary Differential Equations accepted at AAAI 2022.
Manisha Dubey receives Intel India Research Fellowship
Paper by Sakshi Varshney on Continual Adaptation Modules for Generative Adversarial Networks accepted at NeurIPS 2021.
Paper by Manisha Dubey on Multi-view Hypergraph Convolution Network for Semantic Annotation in LBSNs accepted at ASONAM 2021.
Srikar Dupati selected for the PMRF PhD scholarship.
Co-organizing Natural Language Processing session in the AIML vertical in Vaibhav Summit 2020. More details here
Unrestricted research grant from Accenture Technology for learning from alternative data sources.
Nvidia Project on Bayesian deep learning for computer vision and autonomous driving.
DST funding for two projects, Towards Developing Next-generation Deep Learning, and Machine Learning for Astrophysical Data Analysis. Ph.D. and M.Tech (RA) positions available !
Organising IITH and RIKEN-AIP joint workshop on Artificial Intelligence during March 15-16, 2019 at IIT Hyderabad.
Talk on convolutional deep Gaussian processes at IIT Bombay and AIRC Tokyo.
#Keralaflood Please visit our website which live stream tweets on resources availability and requirement kerala flood resources. Talk on Kerala floods rescue related efforts at ICSET 2018.
Talk on deep Gaussian processes at the 3rd Indian workshop on machine learning during july 1-3
JICA funding for the Bayesian Deep Learning project in collaboration with Dr. Emtiyaz Khan from RIKEN Centre for Advanced Intelligence project, Tokyo.
Talk at the Workshop on Analysis and Inference from Unstructured Data during Oct 9-10 at Indian Institute of Science on Social Network Analysis using Point Processes.
SERB funding for social network analysis project using point processes, deep learning and topic modelling.

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