Hey, I’m a Sophomore at Indian Institute of Technology, Kanpur majoring in Computer Science and Engineering, broadly interested in the areas of Deep learning and applied machine learning. I am genuinely interested in contributing to open source, Machine learning ecosystem. .
My sophomore year research work is centred around exploring new and challenging dataset MemexQA. Under the supervision of Badri Narayan Patro at delTA Lab IIT Kanpur, We developed a VQA based model to tackle real-life question answering problems on multimedia collections such as personal photo albums.
Lately, I've been fascinated by the application of Generative Adversarial Network to counter digital manipulation techniques. Being able to model the real world and generate realistic data has many exciting applications. When such data is generated with an intent to deceive the user (or the computer system) into believing that the fake data being generated is real, and these attacks span across multiple media including image, speech & audio, and text.
Last summer, I spent some time exploring Generative Adversarial Network and multi-modal GANs, in particular. I was also involved in SOC, IITK, where are team, developed a web-based platform for managing documents and application and proceedings made by the concerned users. I’ve had some exposure to NLP and its applications , though I’m much less acquainted with the subject that I would like to be.
BTech in Computer Science and Engineering, 2018-Present
Indian Institute of Technology Kanpur, India
developed a VQA based model to tackle real-life question answering problems on multimedia collections such as personal photo albums
Studied Convolutional nueral networks and Generative adversarial networks in-depth . Implemented and played with DCGAN, class conditioned GANs like ACGAN,CGAN,InfoGAN and Style Transfer GANs like DiscoGAN, CycleGAN and StarGAN . Implemented dataloader and progress bar feature in TorchGAN(research framework to train GANs) and tried implementing a YAML parser to train GANs automatically .
Made a voting app (Microsoft codefundo++ Hackathon 2019) using Microsoft Azure Blockchain services for a more secure election.
Developed a web-based platform for managing documents and application and proceedings made by the concerned users.
Studied the theory of encoder decoder sequence models, soft attention and hard attention and reproduced the results in Show, Ask, Attend, and Answer
Studied LIME, technique that explains the predictions of any classifier in an interpretable and faithful manner. "Why Should I Trust You?": Explaining the Predictions of Any Classifier