Faculty
Our Alumni
Doctor of Philosophy
Master of Science (by Research)
PostDoc
Aparna M
Aparna is a PhD research scholar at the Web Science Lab. Aparna holds an MS by Research degree from IIIT Bangalore for the thesis titled “Knowledge management for rural communities using low-resource, colloquial Kannada”. Her research interests include Natural Language Processing (NLP), specifically for Indian languages, as well as narrative modeling. For more information, visit here.
Publications
- Srivatsa, S., Aparna, M., Srinivasa, S., Dinesh, T.B. (2026). Safeguarding Plurality: The Digital Preservation of Diverse Worldviews. In: Sachdeva, S., Watanobe, Y., Bhalla, S. (eds) Big Data Analytics in Astronomy, Science, and Engineering. BDA 2025. Lecture Notes in Computer Science, vol 16267. Springer, Cham. https://doi.org/10.1007/978-3-032-23241-0_16
- Sharath Srivatsa, Aparna M, Malavika V, Samarth P, and Srinath Srinivasa. 2025. Parichaya: Rural Colloquial Knowledge AI Interface. In Proceedings of the 8th International Conference on Data Science and Management of Data (12th ACM IKDD CODS and 30th COMAD) (CODS-COMAD ’24). Association for Computing Machinery, New York, NY, USA, 391–394. https://doi.org/10.1145/3703323.3704271
- Sharath Srivatsa, Aparna M, Sai Madhavan G, and Srinath Srinivasa. 2024. Knowledge Management Framework Over Low Resource Indian Colloquial Language Audio Contents. In Proceedings of the 7th Joint International Conference on Data Science & Management of Data (11th ACM IKDD CODS and 29th COMAD) (CODS-COMAD ’24). Association for Computing Machinery, New York, NY, USA, 553–557. https://doi.org/10.1145/3632410.3632483
- Aparna, M., Srivatsa, S., Sai Madhavan, G., Dinesh, T.B., Srinivasa, S. (2024). AI-Based Assistance for Management of Oral Community Knowledge in Low-Resource and Colloquial Kannada Language. In: Sachdeva, S., Watanobe, Y. (eds) Big Data Analytics in Astronomy, Science, and Engineering. BDA 2023. Lecture Notes in Computer Science, vol 14516. Springer, Cham. https://doi.org/10.1007/978-3-031-58502-9_1
- Aparna M and Srinath Srinivasa. 2023. Active learning for Named Entity Recognition in Kannada. TechRxiv. Preprint. https://doi.org/10.36227/techrxiv.24580582.v1
Rahisha Thottolil
Rahisha Thottolil is a Postdoctoral Research Fellow at the Web Science Lab (WSL) and a Visiting Senior Research Associate at the University of Johannesburg, South Africa.
At WSL, she is currently working on the project Multi-Modal Mobility Solutions for Megaregions around Bengaluru, funded by the Bengaluru Science and Technology Cluster (BeST), an initiative of the Office of the Principal Scientific Adviser to the Government of India.
Her research focuses on data-driven applications in urban studies, with particular emphasis on geospatial data science, urban mobility, and regional planning. Her doctoral research addressed geospatial analysis of urban land-use expansion, predictive modeling, and road transportation network assessment in Bengaluru, contributing to evidence-based urban science and planning practices. With strong expertise in geospatial analytics and urban data science, Rahisha’s work aligns with key thematic areas of the urban life sector, including megaregional planning, urban mobility systems, and strategies to enhance the quality of urban life.
Dev Shinde
Dev Shinde is an M.S. Research Scholar at the Web Science Lab, IIIT-Bangalore, working under the guidance of Prof. Srinath Srinivasa.
At the Web Science Lab, he is currently working on developing a unified framework that addresses the challenges of cross-jurisdictional data sharing while ensuring compliance with various regulatory requirements. His work aims to bridge the gap between theoretical data protection principles and practical implementation methodologies in the context of global data flows.
His research interests include data governance, digital public infrastructure, privacy frameworks, and interoperable systems architecture.
Rishita Patel
Rishita Patel is an M.S. Research Scholar at the Web Science Lab (WSL), IIIT-Bangalore, under the guidance of Prof. Sushree Behera and Prof. Srinath Srinivasa. Her current research, titled “Multi-modal Content Generation for Navigated Learning”, investigates the applicability of diffusion-based text-to-image generation models in the educational domain—an area where factual accuracy, pedagogical alignment, and contextual relevance are paramount. She is working on fine-tuning state-of-the-art diffusion models , aiming to bridge the gap between generative AI’s creative power and the stringent demands of educational content.
Her research interests lie at the intersection of multimodal AI, semantic reasoning, and responsible content generation. Her work explores how models trained for general-purpose creativity can be adapted to serve domain-specific, high-precision use cases like STEAM education.
Ashashree Sarma
MS by Research Scholar
Web Science Lab (WSL), IIIT Bangalore
Ashashree Sarma is a researcher at the Web Science Lab (WSL), IIIT Bangalore, working at the intersection of Network Science, Learning Analytics, Graph-based AI, and Intelligent Information Systems. Her research focuses on understanding how interactions between entities—whether learners, knowledge resources, or mobility networks—shape collective outcomes and decision-making processes.
Her current interests include:
- Network Science and Complex Systems
- Graph Neural Networks (GNNs)
- Graph Retrieval-Augmented Generation (Graph RAG)
- Learning Analytics and Educational Data Mining
- Multi-Agent and Social Learning Systems
- Knowledge Graphs and Semantic Systems
- Human-Centered AI and Personalized Learning
Under the guidance of Prof. Srinath Srinivasa and Prof. Sushree Sangeeta Behera, she contributes to interdisciplinary research that combines machine learning, network modeling, and data-driven decision support systems.
Current Projects :
Social Synchrony in Learning Networks
This project investigates how learner interactions influence collective learning outcomes. Drawing upon network science and learning analytics, the work models learning communities as evolving networks and studies how social synchrony emerges through learner-to-learner interactions.
Project Page:
https://wsl.iiitb.ac.in/social-synchrony-in-learning-networks/
Multi-Modal Mobility Solutions for Megaregions around Bengaluru
This project explores the use of AI, graph-based modeling, and mobility analytics to understand and improve transportation systems across rapidly growing urban megaregions. The work aims to support data-driven planning for sustainable and interconnected mobility infrastructures.
Project Page:
https://wsl.iiitb.ac.in/multi-modal-mobility-solutions-for-megaregions-around-bengaluru/
Publications
Modeling Outcomes-led Learner Behavior and Emergent Social Synchrony
Ashashree Sarma, Sushree Behera, Srinath Srinivasa, and Prasad Ram. Proceedings of the Twelfth ACM Conference on Learning @ Scale (L@S 2025), Palermo, Italy.
DOI: https://doi.org/10.1145/3698205.3733959
Research Presentations
- Learning @ Scale (L@S) 2025, Palermo, Italy
- Educational Data Mining (EDM) 2025
- WebSciX 2025
- RISE 2025
Media Coverage
Google Maps for Learning: IIIT-B Researchers Develop AI Navigator for Personalised STEM Learning
Featured in The Hindu as part of the broader Navigated Learning initiative.
Academic Background
Prior to joining IIIT Bangalore, Ashashree was a Research Intern at the Da’ Spatio Rhobotique Lab, IIT Guwahati, where she worked on research problems at the intersection of Artificial Intelligence and Data Science. She received her B.Tech in Computer Science and Engineering from Assam Engineering College in 2023. Her experience spans both academic research and industry projects involving Data Science, Machine Learning, and Artificial Intelligence.
Links
LinkedIn
https://www.linkedin.com/in/ashashree17321/
GitHub
https://github.com/ashashree2000
Google Scholar
https://shorturl.at/yKH1K
Suhan Roy
I am currently pursuing Masters by Research in the Web Sciences Lab here at IIIT Bangalore. Prior to joining IIITB I have worked in Capgemini Engineering for three years as a Senior Associate and also worked as a Research Assistant in The Visual Conception Group Lab at IIIT Delhi. I am currently working on the Online Learning Navigator Project in partnership with Gooru Labs. My Research Interests are Optimizations in Machine Learning, Deep Learning and Vision Language Models.
Sushree Behera
Dr. Sushree S. Behera received her Doctoral degree from the School of Electrical Sciences, Indian Institute of Technology Bhubaneswar where she worked in the area of Biometrics and Computer Vision using Deep Learning. Prior to that she completed her MTech from the Department of Electrical Engineering, Indian Institute of Technology Indore. Before joining IIIT Bangalore, she worked as a Post- Doctoral Research Fellow at Jio Institute, Navi Mumbai, India, from April 2023 to November 2023. Her research interests lie in the fields of Biometrics, Computer Vision, Medical Image Analysis, Deep Learning, and Machine Learning.
Education
- 07/17-09/22: Ph. D., Indian Institute of Technology Bhubaneswar, India. Thesis title: Deep attention networks for Periocular Recognition in Cross-spectral Environments.
- 07/15-06/17: M. Tech, Indian Institute of Technology Indore, India. Thesis title: Periocular recognition in cross-spectral scenario.
- 07/10-06/14: B. Tech, Veer Surendra Sai University of Technology, Burla, India. Project title: Planar array antenna optimization using bio-geographic-based optimization.
Teaching Experience
- 01/24–Present: Digital Image Processing, IIIT Bangalore
Research Experience
- 04/24 – 11/24: Postdoctoral Research Fellow, Department of Artificial Intelligence and Data Science, Jio Institute, Navi Mumbai, India.
- Application of Generalized zero-shot learning-based approaches for general image recognition
- 09/22-03/24: Senior Research Fellow, School of Electrical Sciences, IIT Bhubaneswar, India
- Coordinate determination of fall of shot from aerial images
- 07/22-09/22: Project Associate, School of Electrical Sciences, IIT Bhubaneswar, India
- Developing attention-assisted deep segmentation models to segment micro-aneurysms from retinal fundus images
- Developing robust segmentation models to perform segmentation of point-of-contact from double-identity fingerprint images.
Research Publications
Journals
- Sushree S. Behera and Niladri B. Puhan, “Dual-spectrum Network: Exploring Deep Visual Feature to Attribute Mapping for Cross-spectral Periocular Recognition,” Journal of Electronic Imaging, vol. 32, no. 3, pp. 033031–0330331, June 2023. DOI: https://doi.org/10.1117/1.JEI.32.3.033031
- Niladri B. Puhan and Sushree S. Behera, “Holistic Feature Reconstruction-based 3-D Attention Mechanism for Cross-spectral Periocular Recognition,” IEEE Transactions on Information Forensics and Security, vol. 18, pp. 435–448, 2023. DOI: 10.1109/TIFS.2022.3224854
- Sushree S. Behera and Niladri B. Puhan, “High boost 3-D Attention Network for Cross-spectral Periocular Recognition,” IEEE Sensors Letters, vol. 6, no. 9, pp. 1–4, Sept. 2022. DOI: 10.1109/LSENS.2022.3204710
- Sushree S. Behera, Niladri B. Puhan, and Sapna S. Mishra, “Perturbed Attention-Assisted Siamese Network for Cross-spectral Periocular Recognition,” IEEE Transactions on Biometrics, Behavior, and Identity Science, vol. 4, no. 2, pp. 210–221, 2022. DOI: 10.1109/TBIOM.2022.3174620
- Sushree S. Behera, Sapna S. Mishra, Bappaditya Mandal, and Niladri B. Puhan, “Variance-guided Attention-based Twin Deep Network for Cross-spectral Periocular Recognition,” Image and Vision Computing, vol. 104, no. 104016, 2020. DOI: https://doi.org/10.1016/j.imavis.2020.104016
Conferences
- Sushree S. Behera, Bappaditya Mandal, and Niladri B. Puhan, “Twin deep convolutional neural network-based cross-spectral periocular recognition,” In IEEE National Conference on Communication (NCC), pages 1–6, 2020. DOI: 10.1109/NCC48643.2020.9056008
- Sushree S. Behera, Bappaditya Mandal, and Niladri B. Puhan, “Cross-spectral periocular recognition: A survey,” in Lecture Notes in Electrical Engineering, vol. 545, Springer, Singapore, 2019, pp. 731–741. DOI: 10.1007/978-981-13-5802-9_64
- Sushree S. Behera, Mahesh Gour, Vivek Kanhangad, and Niladri Puhan. “Periocular recognition in cross-spectral scenario,” In IEEE International Joint Conference on Biometrics (IJCB), pp. 681–687, 2017. DOI: 10.1109/BTAS.2017.8272757
- Ana. F. Sequeira, Lulu Chen, …, Sushree S. Behera, Mahesh Gour, and Vivek Kanhangad,“Cross-eyed 2017: Cross-spectral iris/periocular recognition competition,” In IEEE International Joint Conference.
Sponsored Projects
| Project Title | Sponsoring Agency | Status |
| Generative AI-Driven Navigated Learning for STEAM Education | Gooru India Foundation for Learning Innovation | Ongoing 2024-2027 |