Applications are invited from eligible candidates for the Summer Internships Program 2022 at IIIT Delhi.
About IIIT Delhi
Indraprastha Institute of Information Technology, Delhi is an autonomous Central University located in Delhi, India. It is a research-oriented institute with a focus on Computer Science and allied areas. As of 2021, the approved batch intake for B.Tech program is 489.
About the Internship
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.
|S.No.||Faculty Name||Project Name||Project Detail||Duration|
|1||Aasim Khan||Knowledge and Data in Election Analysis||Requires skills for using Google Analytics and modelling tools and work with a leading election think tank to understand gaps in knowledge about election models.||3 Months|
|2||Anuj Grover||Improving Last Mile connectivity from public transport||We wish to reduce the cost of GPS module so that it becomes affordable for rickshaws and autos and we can then connect them to online platforms for ease of booking and improved user experience.||3 Months|
|3||Anuj Grover||Video Editing||Design a simple interface where videos can be cut at given time-stamps and merged in desired order to create new videos.||3 Months|
|5||Debajyoti Bera||Evaluating state preparation algorithms for quantum circuits||The project will involve reading research papers on quantum state preparation, implementing them and evaluating them to identify which algorithms are most suitable for which kind of states. The focus will be on practically efficient algorithms that perform the best on NISQ devices.||2 Months|
|6||Debarka Sengupta||Random walk on cancer PPIN||We will integrate large volume of mutation data and locate them on PPI interfaces. Further we will try to perform evolutionary modeling while accounting for impact of the fraction of deliterious mutations.||3 Months|
|7||Vivek Bohara||Performance evaluation of optical intelligent Reflective surfaces for 6G cellular standards||The project will involve studing and investigating the tradeoffs for optical intelligent Reflective surfaces for 6G cellular standards. This project will require good mathematical and simulation (Matlab) skills.||3 Months|
|8||Ganesh Bagler||Artificial Intelligence Driven Computational Gastronomy Framework||Cooking forms the core of our cultural identity other than being the basis of nutrition and health. The increasing availability of culinary data and the advent of computational methods for their scrutiny are dramatically changing the artistic outlook towards gastronomy. Starting with a seemingly simple question, ‘Why do we eat what we eat?’, data-driven research conducted in our lab has led to interesting explorations of traditional recipes, their flavor composition, and health associations. Our investigations have revealed ‘culinary fingerprints’ of regional cuisines across the world. Application of data-driven strategies for investigating the gastronomic data has opened up exciting avenues, giving rise to an all-new field of ‘computational gastronomy’. This emerging interdisciplinary science asks questions of culinary origin to seek their answers via the compilation of culinary data and their analysis using methods of complex systems, statistics, computer science, and artificial intelligence. Along with complementary experimental studies, these endeavors have the potential to transform the food landscape by effectively leveraging data-driven food innovations for better health and nutrition. Complex Systems Laboratory: https://cosylab.iiitd.edu.in Computational Gastronomy is a data science which blends food with data and the power of artificial intelligence. We have an ambitious goal of creating a “Computational Gastronomy Framework” around the following themes and expertise. THEMATIC AREAS/EXPERTISE: Artificial Intelligence, Machine Learning, Deep Learning, API Development, Database/Webserver Development, Natural Language Processing, Android/iOS App Development, Novel Recipes Generation, Ayurveda Informatics, Taste/Odor Prediction, Image Processing, Food Pairing Analysis, Carbon/Water Footprinting Calculations, Food Allergens, Food & Music, and Computational Creativity.||2-3 Months|
|9||Koteswar Rao Jerripothula||Saliency Detection in Multi-object Images||There are several studies on saliency detection in single-object images, but there is very limited work done on multi-object images. This project involves developing a relevant dataset and an appropriate algorithm for the same.||2 Months|
|10||Koteswar Rao Jerripothula||Object Detection in Sculptural Arts||Our temples are filled with sculptures, both inside and outside. If they can be automatically identified, a lot of information can be retrieved from internet, helping in educating about our culture. This project involves developing a relevant dataset and an algorithm for the same.||2 Months|
|11||Mrinmoy Chakrabarty||Brain correlates of affective states in autism||Autism spectrum disorder (ASD) presents with a range of issues, e.g. decreased social-emotional reciprocity and non-verbal communication in social interactions; stereotyped repetitive movements, narrow spectrum of interests of unusual intensity and focus as well as sensory dysregulation (hyper/hyposensitivity to sensory inputs), which together manifest as different degrees of clinical severity. A school of thought proposes that the precipitation of one or more of these manifestations could be linked with internal affective/emotional states of the individuals with ASD and there is recent evidence in support of this thought (Chakrabarty M., et. al. European Journal of Neuroscience 2021). In this backdrop the incompletely understood brain bases of these affective states merit further investigation, which this internship seeks to address to a measurable extent.||2 Months|
|12||Piyus Kedia||Address sanitizers for the Linux Kernel||The goal of this project is to measure the overheads of the address sanitizers for the Linux kernel.||2 Months|
|13||Ranjitha Prasad||Bayesian Methods for Explainable AI||In this project, students will explore methods for post-hoc explainable AI for image and tabular datasets.||2 Months|
|14||Saket Anand||Autonomous Last Mile Vehicle||Working towards an autonomous campus shuttle. The tasks involved will require development and testing of various different modules of the autonomous driving solution. This would include development and testing of:|
1. Perception algorithms (using cameras and LIDARs)
2. Planning and Control algorithms (using simulation as well as real vehicular platforms)
3. Integrated system (Perception and Planning combined).
|15||Smriti Singh||Caste, Gender and Urban Space||The project would require extensive referencing work, collecting articles, archives, making a bibliography and putting together synopsis of papers.||2 Months|
|16||Sneha Chaubey||Sieve methods in number theory||Sieve method originates from an algorithm for finding all primes. The earliest known Sieve method is the Sieve of Eratosthenes which utilizes the fact that a natural number is prime if and only if it is not divisible by any prime smaller than itself. Modern Sieve methods originated with Brun around 1920. He used a new Sieve to obtain several important number-theoretic results, notably an estimate of the density of twin primes. This project involves reading and understanding these methods and applying them in different number-theoretic problems.||2 Months|
|17||Subhashree Mohapatra||Approximation of elliptic eigen value problems||Eigenvalue solver for elliptic partial differential equations using spectral element method||3 Months|
|18||Sumit Darak||Solutions for Remote Hardware Labs for online learning||Explore software and mobile applications for conducting hardware labs remotely in online learning environment||2-3 Months|
|19||Sumit Darak||Artificial Intelligence Algorithms on System-on-Chip||Design and implement AI algorithms on SoC. Prior knowledge of embedded systems, Verilog or HLS and FPGA is required.||3 Months|
|20||Sumit Darak||AI/ML for Wireless PHY||Explore various AI/ML algorithms for wireless PHY. Good understanding of AI/ML algorithms and prior experience is desired.||3 Months|
|21||Swapna Purandare||Developing tools and technology for a sustainable Planet||We are developing novel technological approaches based on UAVs, harmonic radar, network analysis and modeling, computer vision, and machine learning to improve the ecological data collection, processing, and analysis.||2 Months|
|22||Swapna Purandare||Insect specimen preparation and pinning||This work involves preparing and pinning collected insect specimen and taking pictures using microscope||2 Months|
|23||Tavpritesh Sethi||Building Real-World Data Science Solutions for COVID-19||In this project, interns will work on developing algorithms and pipelines to derive insights from massive testing, vaccination, genomics and social media datasets. You will be working in a team and data science approaches developed in our lab will form the basis of further innovation. The algorithms and pipelines will be tested in the real world setting, outcomes of this project will be research publications and real world deployment.||2 Months|
|24||Vinayak Abrol||(1) Developing novel counter measures for spoofing attacks in speaker verification (SV) system. (2) Bandwidth extension (BWE) in deep acoustic models||(1) The primary aim is to develop robust SV systems by highlighting the vulnerability of audio models. Recently, DNNs have been shown to be extremely brittle under adversarial and malicious attacks using generative models for speech synthesis. Thus, our goal is to develop novel counter measures against such attacks on SV systems, such that a robust front-end detection system can be deployed to compliment the back-end SV system.|
(2) The aim of BWE is to estimate the missing high frequency information i.e., extend the bandwidth of the signal. It is difficult to simultaneously model narrow-band and wide-band speech. Further there are computational constraints which limits the sampling rate for low latency applications. This project will explore novel approaches for BWE to improve the performance of deep acoustic models.
|25||Sanjit Kaul & Saket Anand||Networked Autonomous Vehicles||Interns will work on creating an indoor testbed using cameras and Jetson bots. This will require an ability to program with python, work with off-the-shelf hardware like the Jetson bot and NVIDIA Jetson GPUs, WiFi access points and USB WiFi, off-the-shelf cameras, and familiarity with openCV. In addition, interns with exposure to deep learning and preferably even reinforcement learning, will work on learning data driven policies to make the Jetson bots autonomous. The bots will talk to cameras and with each other over WiFi.||3 – 6 Months. Extensions are possible.|
|26||Vibhor Kumar||Adaptive deep learning for medical image processing||Here we will try to develop web based predictive system for predicting neuro-degenerative and other disorder using image data like ctscan and MRI||2-3 Months|
|27||Vivek Kumar||Understanding and evaluating a runtime scheduler for user level threads||This project is about understanding the implementation of an open-sourced user level thread scheduler and implementing new scheduling policies||2 Months|
|28||Vivek Kumar||Designing a lightweight framework for working with processor specific counters / tools||This project is to implement a lightweight daemon to improve the access to hardware performance counters, processor frequency scaling, etc||2 Months|
|29||Mukulika Maity||Measurement Study of Response Times of Apps in India||In this project, we quantify the Quality of Experience of using the android apps using response time i.e., the time needed to reflect UI changes corresponding to a user’s action. This can be, for example, the time needed to reflect an item has been added to the cart for Add product to cart action on Amazon app. In this work, we design a tool called EvalApp which uses automation to record the response times of a total of 30 actions for 12 apps popular in India. We then crowdsource this desktop app to a total of 60 users working from home from across north and central India and perform a causal analysis of the factors that affect the response times of actions.||3 Months|
|30||Mukulika Maity||Youtube Video Streaming over Google’s QUIC||One of the most commonly used transport protocols, developed by Google, QUIC, adapts to such failures by falling back to TCP. In this work, we investigate the fallback behavior of QUIC on Youtube video streaming. In total, we collect over 2600 streaming hours of data over various bandwidth patterns, from 5 different geographical locations and various video genres. To our surprise, we observe that the legacy setup (TCP) either outperforms or performs the same as the QUIC-enabled browser for more than 60% of cases. We are in process of designing solutions to improve QUIC’s performance.||3 Months|
|31||Mukulika Maity||Optimization of Next Generation Wireless Networks||This project aims to improve WiFi performance in dense scenarios like classrooms, conferences, airports, and so on. It aims to utilize next-generation wireless standards WiFi 6/7 to improve performance in dense scenarios through efficient resource management techniques. It also opens the door to a new avenue of application of WiFi in industrial IoT settings, edge node deployments, and so on.||3 Months|
Students who get selected for the summer internship at IIIT-Delhi will be receiving a stipend of 5k per month
How to Apply?
- Click on Apply Here.
- 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.
- The last date to apply is 31st March 2022.
- The results will be up on the website by 15th April 2022
- The internship will commence from 6th May 2022.