Devesh Pant

I’m currently working as an Associate Machine Learning Scientist at Wadhwani AI, where I work on bulding AI solutions for sectors like health and agriculture. My focus is on training and deploying NLP and computer vision models for real-world social impact in India.
Earlier, I completed my MS (by Research) in Computer Science at IIT Delhi, with a thesis focused on robust text recognition in challenging scenarios, under the guidance of Prof. Chetan Arora and Prof. Aaditeshwar Seth I still find myself reading OCR papers on weekends — guess my Master’s work did a number on me 😃.
I’m broadly interested in large language models, foundational vision models, and multi-modal architectures. I’m passionate about creating scalable, accessible AI tools that can serve diverse and widespread communities.

news

Jun 15, 2025	Health Sentinel accepted in NLP4PosImpact workshop in ACL 2025 in Vienna 🚀
Jan 20, 2025	Promoted to Asociate Machine Learning Scientist - 2 🥳
Aug 20, 2024	Graduated from IIT Delhi 🎓
Sep 01, 2023	Joined Wadhwani AI as Asociate Machine Learning Scientist - 1 💼

selected publications

Health Sentinel: An AI Pipeline For Real-time Disease Outbreak Detection

Devesh Pant, Rishi Raj Grandhe, Vipin Samaria, and 13 more authors

2025

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Early detection of disease outbreaks is crucial to ensure timely intervention by the health authorities. Due to the challenges associated with traditional indicator-based surveillance, monitoring informal sources such as online media has become increasingly popular. However, owing to the number of online articles getting published everyday, manual screening of the articles is impractical. To address this, we propose Health Sentinel. It is a multi-stage information extraction pipeline that uses a combination of ML and non-ML methods to extract events-structured information concerning disease outbreaks or other unusual health events-from online articles. The extracted events are made available to the Media Scanning and Verification Cell (MSVC) at the National Centre for Disease Control (NCDC), Delhi for analysis, interpretation and further dissemination to local agencies for timely intervention. From April 2022 till date, Health Sentinel has processed over 300 million news articles and identified over 95,000 unique health events across India of which over 3,500 events were shortlisted by the public health experts at NCDC as potential outbreaks.
Robust OCR Pipeline for Automated Digitization of Mother and Child Protection Cards in India

Devesh Pant, Dibyendu Talukder, Aaditeshwar Seth, and 7 more authors

ACM J. Comput. Sustain. Soc., Sep 2023

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The Universal Immunization Programme in India has a mandate to fully vaccinate all of India’s 27 million children born annually. The vaccination doses are recorded by frontline health workers on standardized paper-based Mother and Child Protection (MCP) cards, which are manually digitized by data entry operators, resulting in poor data quality, delays, and significant time and resources. In our article, we focus on Optical Character Recognition– (OCR) based automated digitization of MCP card images captured through a smartphone application developed by us. By utilizing a standardized template for the MCP cards, which is available a priori, we register the card images and perform OCR on the extracted region of interest (ROIs). Since the cards with curvature or torn edges had poor ROIs, we built a global–local alignment technique that first approximates the ROI using global homography and then refines using a local homography resulting in improved accuracy. Our pipeline gives a character level accuracy of 98.73% on our dataset against 75.02% by Google Cloud Vision and 79.26% by Azure OCR. We also describe our field testing experience, where the digitized MCP card images were used to provide useful features on the smartphone application for health workers to conduct vaccination sessions.