Konda Reddy Mopuri

I am an Assistant Professor at the Department of Artificial Intelligence, Indian Institute of Technology Hyderabad. Here, I lead the Data-Driven Intelligence & Learning Laboratory (DiL). My office (704/C) is located in the C-block.

My research interests are broadly in the fields of Artificial Intelligence, Machine learning (specifically Deep Learning), Data Science and Engineering, and Computer Vision.

Google Scholar  /  Publications

DiL Lab  /  Teaching

Email: krmopuri 'at' ai 'dot' iith 'dot' ac 'dot' in

• Jan 2026: Offering a course on Computer Vision.
• Nov 2025: I am not planning on hosting interns (summer/winter, online/offline). I'm sorry for not responding to such email applications.
• Nov 2025: One paper accepted in WACV-2026. Congratulations Saumyaranjan and Dr. Aravind Reddy.
• Sep 2025: One paper is accepted in NeurIPS-2025 under the Datasets and Benchmarks track. Congratulations Shanawaj, Madhumitha, and Harsh Udai.
• Sep 2025: One paper on "Coreset-Driven Re-labeling" is accepted in TMLR. Congratulations, Saumyranjan.
• Jul 2025: Offering a course on Foundations of Machine Learning. (First meeting is on 28th July)
• Apr 2025: Paper accepted in TMLR on Coresets for efficient Deep Learning. Congrats Saumya and Anudeep.
• Apr 2025: We have one paper on "Alzheimer’s Disease Detection via Inducing Domain Priors in Vision Transformers" accepted in XAI4CV2025 workshop at CVPR 2025. Congratulations, Madhumitha, Sunayana, Shanawaz and Susmit!
• Feb 2025: We have one paper on "Machine Unlearning in Text-to-Image Diffusion Models" accepted in CVPR 2025. Congratulations, Naveen, Karthik, and Rutheesh!

The following are our active research projects. Please visit our lab page to know more about our research.

• Dataset Condensation (or, Distillation)
• Computer Vision for Neurodegenerative Disorders
• Unlearning in Text-to-Image Diffusion Models
• Compositionality in Vision Representations
• Long Video Understanding
• Test-Time Adaptation of Vision Models
• Robustness of Computer Vision Models

• Mar 2024: Invited to speak at the DAPCom-2024 conference
• Feb 2024: Invited to speak at the TRAI seminar on AI and Challenges
• July 2023: Organized a tutorial on Data-free Knowledge Extraction from Deep Neural Networks as part of the NCVPRIPG 2023 conference.
• June 2023: Gave an introduction to the Foundations of Data Science at the ACM Summer School on Algorithmic Techniques in Computational Biology.
• March 2023: Gave a talk on introduction to Explainability in AI at the Asi@connect capacity building project.

Source taken from here.