Hi there! I'm Anirudh, a second-year Ph.D. student in Computer Science at Cornell University, where I am advised by Prof. Tanya Goyal. My research interests are primarily in the field of Natural Language Processing. Some of the research directions I'm especially excited about include:
Previously, I earned my Master's degree in Computer Science at UMass Amherst. There, I was fortunate to collaborate with Prof. Mohit Iyyer on studying the impact of LLM quantization on long-context and long-form text generation scenarios, and with Haw-Shiuan Chang and Prof. Hamed Zamani, on evaluating creativity and instruction-following ability in LLMs. Even earlier, I graduated from BITS Pilani, India, with a dual major: B.E. in Computer Science and M.Sc. in Mathematics. As part of my undergraduate thesis, I worked for over a year with Prof. Subrata Chakraborty at the University of New England, Australia, on projects involving computer vision for healthcare (such as medical image analysis, autism detection, and psychological testing).
News
✈ Nov 2025: Presented our paper on quantization at EMNLP in Suzhou, China.
🎓 May 2025: Graduated from UMass Amherst with a Master of Science in Computer Science!
✎ May 2025: Check out our new paper on the impact of quantization on long-form and long-context tasks!
🏫 April 2025: Accepted a PhD offer from Cornell University under the supervision of Prof. Tanya Goyal at Cornell NLP.
🏫 February 2025: Appointed as a grader for the COMPSCI 696DS: Industry Mentorship Independent Study - Data Science course at UMass.
Older updates
📄 September 2024: Paper on instruction-following and creative writing accepted at the 6th Workshop on Narrative Understanding at EMNLP 2024!
⚙ September 2024: Started working on an independent study with Prof. Mohit Iyyer at UMass NLP to study the impact of LLM quantization on factuality, instruction-following, and long-context reasoning.
📄 August 2024: Systematic review on the applications of artificial intelligence for suicide detection accepted by the journal Information Fusion (Q1; IF: 14.7; Cite Score: 33.2).
📄 July 2024: Systematic review on the applications of deep learning in radiology for lung cancer diagnostics accepted by the journal Expert Systems with Applications (Q1; IF: 7.5; Cite Score: 13.8).
⚙ January 2024: Collaborating with Amazon on an industry mentorship project to study the impact of prompt specificity on LLMs (advised by Prof. Andrew McCallum and Haw-Shiuan Chang).
➜ August 2023: Excited to pursue my second Master's degree - this time in Computer Science at UMass Amherst!
🎓 August 2023: Graduated with distinction from BITS Pilani, India, with a dual major (B.E. Computer Science, M.Sc. Mathematics) and a CGPA of 9.15/10!
📄 February 2023: Paper on predicting video game development problems using ensemble techniques accepted at the Innovations in Software Engineering Conference (ISEC) 2023.
⚙ January 2023: Started my internship as a database administrator at First Meridian, Bangalore.
✈ December 2022: Presented papers at the DICTA (Sydney) and ACIS (Melbourne) conferences in Australia.
⚙ November 2022: Started working with Prof. Rajendra Acharya on medical image analysis using artificial intelligence.
📄 October 2022: Paper on the relationship between deep learning models and human personality traits accepted at the Australasian Conference on Information Systems (ACIS).
📄 October 2022: Paper on hidden and face-like object detection using deep learning techniques accepted at the International Conference on Digital Image Computing: Techniques and Applications (DICTA).
⚙ August 2022: Started working on my undergraduate thesis with Prof. Subrata at the University of New England, Australia.
⚙ January 2022: Started working as a data science intern at Epsilon India to generate personalized email subject lines.
📄 December 2021: Paper on predicting video game development problems using word embeddings accepted in the Proceedings of ICON 2021: 18th International Conference on Natural Language Processing.
🏫 August 2020: Appointed as a teaching assistant for the course Elementary Real Analysis at BITS Pilani.
📄 June 2020: Published my first paper on mathematically modeling the spread, peak, and reduction of COVID-19 in the journal Infectious Disease Modelling (Q1; IF: 3.0; Cite Score: 18.3).
⚙ May 2020: Started working as a summer research intern at Ecom Express, New Delhi, to study travel network optimization using Pyomo.
🏫 January 2020: Appointed as a teaching assistant for the course Probability and Statistics at BITS Pilani.
🎓 August 2018: Admitted to Birla Institute of Technology and Science, Pilani (BITS Pilani) for a dual major in Computer Science and Mathematics.
Publications
My Google Scholar. I have published under the names Anirudh Atmakuru and A Anirudh.
* denotes equal contribution
2025
2024
2023
2022
2021
2020
Responsibilities
Teaching Assistantship
- Grader - COMPSCI 696DS: Industry Mentorship Independent Study - Data Science - UMass Amherst (January 2025 - May 2025)
- Elementary Real Analysis - BITS Pilani (August 2020 - November 2020)
- Probability and Statistics - BITS Pilani (January 2020 - April 2020)
Reviewing
Volunteering
- I volunteered actively for over two years to conduct free classes for underprivileged children in India as a part of the Nirmaan Organization(2018-2020).
Miscellaneous
I'm from the lively city of Chennai, India. In my free time, I love listening to Carnatic music, and whenever I can, playing cricket, swimming, or biking. Lately I've been venturing into running and mystery/thriller novels. Traveling and backpacking excite me, and I enjoy discovering new places and trying anything adventurous, such as skiing, scuba diving, and skydiving.
Contact me: Open to collaborations and conversations about research. Also happy to chat with any high schooler/undergrad/MS student if I can be of any help.
