CV

MSc.

University of Hamburg

Intelligent Adaptive Systems

B.Tech (Hons.)

Indian Institute of Information Technology Kottayam

Computer Science

Independent Contractor

Language Technology Group, University of Hamburg

Conducting research on actantial models, label projection, and LLM creativity.

• Implemented pipelines to automatically apply the actantial narrative model using LLMs, with paper submitted to **CHR 2026**.
• Designed LabelPigeon, a novel label projection technique utilized for low resource cross-lingual transfer, with paper accepted at **ACL 2026 Findings**.
• Quantified the creativity of LLM-generated stories via a novel narrative similarity evaluation scheme, with paper submitted to **EMNLP 2026**.

Research Intern

Language Technology Group, University of Hamburg

Conducted research on embedding models and large language model (LLM) representations.

• Conducted a general investigation on embedding models and LLM representations, developing an optimal few-shot fine-tuning regime for topic modeling.
• Devised L3Prune, a novel pruning procedure for LLM-based embedding models reducing model size by 21% with a negligible performance drop, with paper published in **RepL4NLP 2025**.

Machine Learning Intern

Institute of Human Resource Development

Developed and deployed machine learning models for speech recognition, speaker identification, and face recognition.

• Worked with the Kerala Police Intelligence Department, leading a team of 15 to develop AI systems for policing.
• Trained and deployed a state-of-the-art automatic speech recognition (ASR) model for Malayalam, along with a speaker extraction and identification system.
• Designed and implemented a Malayalam news extraction system utilizing optical character recognition.
• Developed a scalable face recognition system optimized for fast inference.

Data Science Intern

Institute of Human Resource Development

Optimized web infrastructure and data-driven decision making.

• Rebuilt web stack to streamline employee workflows, significantly improving productivity.
• Created visualizations and reports to communicate insights to stakeholders and government agencies.
• Optimized purchasing decisions based on statistical modeling.

Advocating for Character Error Rate in Automatic Speech Recognition

• Documented the shortcomings of the commonly used word error rate metric for multilingual evaluation in collaboration with Dr. Jesin James.
• Collected human preference data in 3 languages and calculated metric correlations, providing experimental evidence in favour of Character Error Rate.
• Wrote a paper arguing our position, accepted at **NAACL 2025 Findings**.

Fisher Mask Nodes for Model Merging

• Devised a novel and compute-efficient model merging algorithm under Dr. Suchithra M S.
• Evaluated performance of our method across various models in the BERT family, with performance improvement of **+6.5%** and a speedup between 57.4x and 321.7x.
• Documented research outcomes in an academic paper, published in **LREC-COLING 2024**.

ICFOSS Malayalam Speech Corpus

• Collaborated on IMaSC - The ICFOSS Malayalam Speech Corpus, a 50-hour text-to-speech dataset.
• Supervised data collection, speaker recording, and quality control.
• Trained and evaluated multiple models, achieving an average MOS score of 4.50.
• Wrote a research paper compiling our results, accepted at **LREC 2026**.

DAAD WISE Scholarship

German Academic Exchange Service

Just Use XML: Revisiting Joint Translation and Label Projection.

Findings of the Association for Computational Linguistics: ACL 2026 (pp. 34461–34478)

Do Large Language Models Always Tell The Same Stories?

arXiv Preprint, Submitted to EMNLP 2026

Large Language Models Are Overparameterized Text Encoders

Proceedings of the 10th Workshop on Representation Learning for NLP (RepL4NLP-2025) (pp. 170-184)

Advocating Character Error Rate for Multilingual ASR Evaluation

Findings of the Association for Computational Linguistics: NAACL 2025 (pp. 4926-4935)

Fisher Mask Nodes for Language Model Merging

Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) (pp. 7349–7355)

IMaSC: A Malayalam Speech Corpus for High-Quality Text-to-Speech Synthesis

Proceedings of the Fifteenth Language Resources and Evaluation Conference (LREC 2026) (pp. 5864-5872)

Performance Enhancement of Deep Neural Network Based Automatic Voice Disorder Detection System with Data Augmentation — A Case Study

Biomedical Engineering: Applications, Basis and Communications, Vol. 35

Memory Based Speech Duration Model using Exemplar Theoretic Approach

Proceedings of the International Conference on Artificial Intelligence & Speech Technologies (AIST 2019) (pp. 108–112)