Biography

I am a Ph.D. Candidate in the Computer Science department at the University of California, San Diego working with Prof. Jingbo Shang. I completed my Bachelor Of Technology in Computer Science And Engineering from the Indian Institute of Technology, Kanpur in 2017. For summer 2023, I am interning at FAIR London, Meta AI with Dr. Jane Yu and Dr. Jason Weston, working on improving the tool use capability of large language models. Previously, I interned at Microsoft Semantic Machines in 2022, and Amazon Science in 2021.

Current Research

My research is centered on understanding data and the development of data-driven approaches to enhance NLP pipelines, with a particular emphasis on reducing annotation and training costs. I’m actively exploring the following inquiries:

• Data Quality for Performance I examine the data landscape through the lens of difficulty, diversity, and noise, striving to understand whether we could find the optimal volume of data necessary for achieving specific performance targets.

• Leveraging Noisy Data Given that noisy data is often more readily available and cost-effective to obtain compared to clean data, I’m exploring the extent to which we can advance NLP tasks with noisy data and weak supervision [1], [2], [3].

• Enhancing Model Awareness How can we empower language models to be self-aware of their capabilities and train them to provide well-calibrated predictions, making their scores more reliable? I’m also interested in enabling them to use external tools & resources when they are not confident.

I’m also extremely enthusiastic about designing goal-driven language assistants, and this area presents an abundance of intriguing questions to explore. In my vision statement, I delve deep into some of the questions including:

• Empowering Language Assistants One fundamental feature I envision for language assistants is their capacity to seamlessly integrate with a diverse range of tools. How can we train these assistants to adapt and effectively utilize tools that are new or previously unseen?

• Enhancing Collaboration Building an assistant that can collaborate with humans to simplify their tasks is a pivotal challenge. This entails improving the assistant’s ability to ask clarifying questions, thereby fostering a productive partnership.

• Proactivity in Assistants Are existing language assistants proactive, and how do we define and quantify their proactiveness? Exploring ways to train an assistant to be proactive is another intriguing aspect of this research.

Apart from Academics, I enjoy spending time playing Ukulele, playing Football(soccer) and I rarely write too. Checkout my blog!