News
[May 2025] Completed Amazon Applied Science Internship at Alexa AI.
[May 2024] Completed an Applied Science internship at Amazon.
[April 2024] Our paper on Emergent Abilities accepted to NAACL Findings
2024!
[March 2024] Our work on ReLoRA accepted to ICLR 2024!
Education
Ph.D. in Computer Science; GPA 4.00
September 2021 – Present
Advisor: Prof. Anna Rumshisky
Master of Science in Electrical Engineering; GPA 3.79
August 2011 – May 2013
Bachelor of Engineering in Electronics and Communication; GPA 4.00
September 2007 – July 2011
Experience
University of Massachusetts Lowell | May 2023 – Present
PI: Prof. Anna Rumshisky
- Researching efficient and interpretable methods for pre-training and evaluating language models.
- Analyzing pre-training dynamics to understand how language models generalize.
- Developing compute-efficient pre-training approaches.
- Building datasets and evaluations for math, reasoning, and creativity.
Amazon | May 2025 – August 2025
PI: Dr. Rinat Khaziev
- Researched and developed multilingual evaluation methods for large language models, focusing on
improving performance beyond English.
- Built and trained judge models for multi-turn conversation evaluation across multiple languages.
Amazon | May 2024 – August 2024
PI: Ikkei Itoku
- Built a synthetic data generation pipeline to address challenges of data scarcity and privacy in
HR analytics.
- Developed datasets of career-related documents with structured annotations.
- Fine-tuned Mistral-7B-Instruct model with synthetic data, enabling it to identify specific
guidelines demonstrated by employees.
Arizona State University | July 2012 – May 2013
PI: Prof. Jieping Ye
- Implemented Gene expression pattern annotation using SIFT feature extraction on images in the
Berkeley Drosophila Genome Project (BDGP).
- Constructed Codebooks using Bag of Words and Sparse Coding Approach.
Qualcomm | October 2016 – December 2021
- Developed firmware for the physical layer of Wireless LAN chips using the Wifi 802.11 protocol.
- Designed and implemented features such as Spectral Scan and Radar Detection.
NXP | June 2013 – October 2016
- Developed signal processing applications for radio communication, focusing on transmit and
receive chains on a Vector Signal Processor for Power Amplifier characterization.
- Implemented communication interfaces between host processors and co-processors to enhance
functionality in Power Amplifier characterization applications.