Hey,

My name is Akash. I am a master's student studying Computational linguistics at the University of Rochester (Go Yellowjackets !!). I enjoy coding, cooking, traveling, and clicking photographs. This website is an attempt to document everything on my mind in one place. Here I share some of my thoughts on various topics, I present some of the photos I clicked and of course my portfolio and resume for potential employers.

"Memento Mori”

Blog

Photographs

Rushress library

Campus Starbucks

Library Lot

Pitsford dairy farm

https://open.spotify.com/embed/playlist/4woP5l6JGT7hbhqkqBIiVX?utm_source=generator

Resume

<aside> 👋 I build resource-optimized, interpretable ML models with my code. I have two years of experience as an ML engineer where I collaborated with multiple partner teams such as Business, Product Management, Strategy, and Business Management to deploy solutions into production.

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Contact

📧 [email protected]

🔗 linkedin.com/in/akashchaudhari

👾 https://github.com/akashchaudhari98

Experience

Graduate Research Assistant

University of Rochester, USA (May 2023 - Present)

Developed a neural CKY parser to parse combinatory categorical grammars. Developed an encoder model to convert CCG types into embeddings and a decoder model to convert them back. Trained multiple combinator controller models implementing CCG rules to combine two embedded types. Brought all these models together to form a neural CKY parser. The goal of this research was to introduce logical information into sentence embeddings.
My thesis explores the development of a model aimed at identifying & retrieving a set of documents that describe the “exact same event” as articulated in a user document. The model incorporates a ranking mechanism to evaluate and prioritize the retrieved documents based on the extent and granularity of the information they contain. This research aims to enhance the precision of information retrieval in the context of “event-centric” document analysis.

Machine learning Engineer

Hansa Cequity, Mumbai, India – (Aug 2021 - Aug 2022)

Aspect-based opinion analysis:
- Developed an NLP pipeline to extract product aspects from unstructured text data. Utilized both lexicon-based methods and transformer models, to determine the polarity of opinions expressed about each aspect.
Automating Call Center analysis:
- Architected and deployed end-to-end NLP pipelines using Hugging Face transformers for automated insight extraction from call center transcripts. Developed custom preprocessing scripts to handle noise, speaker diarization, and multilingual data.
- Trained and fine-tuned BERT-based models for sentiment analysis, entity recognition, and topic classification.
Deployed multi-stage ML pipeline to run inference on 8M points using docker. Established continuous monitoring and logging systems to track model performance, detect anomalies, and facilitate timely updates.

Machine learning Engineer

Zinc Technologies, Mumbai, India – (July 2020-August 2021)

Zinc technologies use ML, and NLP to help writers write better books. We provide analysis and recommendations to improve scripts to perform well in the market.
- Developed ****NLP models for book analytics. Trained a classification model to identify the genre of a script, & mapped it to books that had previously performed well in the market in a similar category.
- Used transformer models like BERT to analyze changes in the genre as the story progressed. Trained models to compare the two books & rate them based on fluidity, reading complexity, & genre absorption.

Machine learning Intern

Tata Consultancy Services, Mumbai, India – (Dec 2019-March 2020)

Developed machine reading comprehension and document Q&A model to answer questions on a document uploaded by the user.