Each year our faculty members invest their time, effort & innovation in some great real-time projects. The projects are listed below. A student can apply for a max of 03 projects. Registration will start from 18th Feb 2026. The last date to apply will be 15th March 2026. The results will be up on the website by 15th April 2026 & the internship will commence from 11th May 2026.
Process to apply for internship
- The details of the project openings are listed below.
- Click Here to Apply. (Opened from 18th Feb 2026)
- Login with your google account
- Fill the registration form. If you want hostel select the checkbox accordingly.
- For hostel booking details please click here
- To apply for any project just click the apply button
- Done
Students who get selected for the summer internship at IIIT-Delhi will be receiving a stipend of 5k per month
Summer Internship Projects 2026 at IIIT-Delhi
| S.No. | Faculty Name | Project Name | Project Detail | Duration | Status |
|---|---|---|---|---|---|
| 1 | Kaushik Kalyanaraman and Kiriti Kanjilal | Bayesian Persuasion | "Bayesian Persuasion is a framework for modeling and theoretically studying the common language parlance of, as well as a real-world sense of, the action of persuading. Bayesian Persuasion models payoff interactions (involving suitable payoff costs) such as in that between lawyer-judge in a courtroom for defending or convicting, patients-pharmaceutical company for testing efficacy of a new drug, consumers-producers for marketing, and many more. As a specific example, a government agency may wish to persuade farmers to take up crop insurance; the mechanics of signaling such a behavioral nudge mathematically then fit in this setup and is one of our motivating interests for this problem. The theory of Bayesian Persuasion is used to determine the optimal payoffs, for characterizing their existence and computation. Computationally, an optimal solution could be NP-hard to obtain as is known to be the case for even some rather simple formulations of the problem. Thus, this would necessitate an approximate solution and characterization of both its quality and computational tractability. Given this brief background, the primary goals of this summer internship project are to study the literature, carefully understand the formalism, and apply to some example scenarios. We are looking for candidates who are well versed in many of the following topics: probability theory, Bayesian statistics, measure theory, convex optimization, computational complexity, approximation algorithms." | 2-3 Months | Physical |
| 2 | Shamik Sarkar | AI-native Wireless Networks and Wireless Sensing | Student will implement wireless PHY or RAN functionalities that natively support AI algorithms. Wireless sensing can be an important component of this project. | 2 Months | Physical |
| 3 | Sonal Keshwani | Design and development of oral healthcare products | The project aims to design and develop products related to oral care. The applicants should have the knowledge of working with sensors and Arduino IDE. Knowledge of design process and prototyping methods is preferable. | 4-6 Months | Physical |
| 4 | Sonal Keshwani | Understanding design cognition in Biologcially inspired design process | The aim of this project is to understand the cognitive process of designers in creative tasks involving biologically inspired design process. The applicants should be familar with basics of signal processing and natural language processing. | 6 Months | Physical |
| 5 | Sukanta Nandi | Computational Design and Analysis of Dielectric Metasurfaces | Dielectric metasurfaces are ideal for realizing low-loss, high Q-factor, nanophotonic devices. The goal of this summer project is to design and model metasurfaces through the use of a Finite Element Method. After successful design, the output response of the metasurface (such as- reflection and transmission) will be analyzed and possible applications will be discussed. | 2 Months | Physical |
| 6 | Mukesh Mohania | AI in Education | Develop an AI based live Tutor system for K-12 students for Science and Mathematics. This system will take students "Topics/Concepts" to learn as an input, and will generate a set of slides to explain the asked topics/concept. The student can also ask a doubt in between while explaining the slides and the system will leverage the LLM for clearing the doubts based on the context and doubt question. | 3 Months | Physical |
| 7 | vibhor kumar | makinh interactive human cell data-set explorer | using GUI and AI to make user friendly interactive system plugged in with our search engine | 3 Months | Physical |
| 8 | Shamik Sarkar | Autonomous Indoor UAVs | The student will develop and implement Reinforcement Learning algorithms for path planning of indoor UAVs | 2-3 Months | Physical |
| 9 | Anuj Kumar | Magnetic tunnel junctions based neural network | Magnetic tunnel junctions (MTJs) are the core building block of industrial non volatile magnetic memory devices. In particular, spin-orbit-torque (SOT)-MTJs offers decouple read and write paths and enable reliable switching with excellent endurance. This internship project targets the device-to-algorithm gap. We will develop a framework that understands SOT-MTJ and. their incorporates realistic non-idealities (state dispersion, read noise, limited update granularity), and benchmarks performance using industry-relevant metrics (accuracy-energy-latency trade-offs). The outcome will be a reproducible, publication-quality toolkit (code, benchmark scripts, and concise report) that demonstrates how device-aware training and calibration can convert emerging spintronic devices into practical building blocks for next-generation edge AI hardware. | 2 to 3 Months | Physical |
| 10 | Tanmoy Kundu | Multi-robot Planning and Coordination under Uncertain Conditions and Resource Constraints | "The national security initiative of Mission Sudarshan Chakra under Atmanirbhar Bharat aims to establish a multi-domain offensive and defensive security umbrella. Coordinated multi-UAV (Unmanned Aerial Vehicle) systems is one of the key techniques to realize the goal, and intelligent decision making by the robots plays a pivotal role. Decision making becomes further challenging with various uncertain factors like hostile attacks, technical glitches etc. and resource constraints such as limited connectivity, battery power etc. In this project, we will investigate some problems aligned with the above, in the domain of AI-enabled multi-robot coordination under uncertainty." | 3 Months | Virtual |
| 11 | Tanmoy Kundu | Designing Techniques for Handling NP-hardness in Charging Station Placement Problem | In automated warehouses (e.g. Amazon), teams of mobile robots work perpetually to perform repetitive tasks. As these robots are battery driven, they need to be recharged at (un)certain intervals. Automated recharge planning needs to be done in an intelligent way such that the robots do not become non-functional due to lack of battery charge. Our previous research handled some of the problems related to the above. This project will particularly extend on our previous works by designing novel techniques to handle the NP-hardness of the abovementioned problem. Proficiency in LaTeX is desirable criteria for this project. | 3 Months | Virtual |
| 12 | Tavpritesh Sethi | SAFE-Hospitals: AI for Flagging Drug Interactions in Hospital Admitted Patients | The project extends our published work on mitigating adverse drug-drug interactions in patients admitted to hospitals. | 3 Months | Physical |
Last updated: 17-02-2026