I’m an applied AI researcher/engineer, currently at AI71 in Abu Dhabi. My work here centers on LLM agent systems for enterprise: agent orchestration, making them production-ready, and evaluation frameworks. Recently I’ve also started working on voice-based use cases.

Before this, I spent nearly four years at Wadhwani AI in Delhi, building AI for public health. The work I’m proudest of: a chatbot for frontline healthcare workers, automated TB diagnostics (AAAI 2024), and a clinical decision support system used in over 122 million patient consultations. I studied at IIIT Delhi, an interdisciplinary program across Computer Science, Economics, and Sociology.

Born and raised in Delhi, now learning to live on my own in Abu Dhabi. Outside work, I follow cricket, climb mountains, travel whenever I can, and chase good food.

Experience

Where I've worked, in reverse chronological order.

  1. Senior ML Engineer Mar 2025 to present

    AI71

    Building AI agents for enterprise. Architected the transition from static RAG to ReAct-based LLM agents using LangGraph. Designed evaluation frameworks, optimized inference costs by 3x, and benchmarked frontier models for reasoning.

  2. Associate ML Scientist II Aug 2021 to Mar 2025

    Wadhwani AI

    Built AI systems for public health at scale, including an LLM chatbot for frontline healthcare workers, automated TB diagnostics (AAAI 2024), and a clinical decision support system serving 122M+ consultations. Partnered with the Indian government, USAID, and the Gates Foundation.

  3. Teaching Assistant, Econometrics Jan to May 2021

    IIIT Delhi

    Assisted Dr Gaurav Arora with the Econometrics II course. Created data assignments in R and evaluated quizzes and exams.

  4. Research Intern 2020

    Wadhwani AI

    Helped build AI and data science solutions to predict non-adherence in TB patients. Wrote about the internship experience.

  5. Research Intern 2019

    Trivedi Centre for Political Data

    Helped create datasets on legislators and election-related judgments.

  6. B.Tech in CS, Economics & Sociology 2017 to 2021

    IIIT Delhi

    Pursued an interdisciplinary program at the intersection of Computer Science, Economics, and Sociology. Where I first got interested in applying ML to real-world problems.

Projects

Selected things I've built.

  • Ask: AI Assistant for Enterprise

    ReAct-based LLM agent system at AI71 with structured reasoning, dynamic tool orchestration, prompt and KV caching (18-35% TTFT reduction), and a full evaluation framework with MLflow tracking and CI/CD integration.

    ASK71

  • AI Chatbot for Frontline Healthcare Workers

    LLM-based assistant helping frontline health workers in India with clinical queries. 83% acceptance rate from domain experts. Reduced per-query cost 5-6x with synthetic data and caching. Built with the Ministry of Health, supported by USAID and the Gates Foundation.

    HealthVaani

  • Automated TB Diagnostics (Line Probe Assay)

    Object detection system using DETR to read Line Probe Assay strips for Drug-Resistant TB, achieving >96% band accuracy. Designed a ground truth study with 9 expert microbiologists. Paper at AAAI 2024.

    Paper

  • Clinical Decision Support System (CDSS)

    ML system for India's national telemedicine platform, helping doctors identify the right diagnosis across 31 diseases. Served 122M+ consultations. Semi-finalist at MIT Solve Challenge 2023.

    MIT Solve

  • Corneal Transplant Outcome Prediction

    AI suite predicting future visual scores and patient drop-off to improve cornea management and surgery outcomes. Led the project end-to-end, including product, stakeholder management, fundraising, and ML.

Publications

  1. Evaluating Robustness in LLM-based Medical Chatbots

    Mukul Kumar, Alugubelli Dinesh Reddy, Sai Nikhilesh Reddy. 2nd HEAL Workshop at CHI Conference on Human Factors in Computing Systems, 2025. [pdf]

  2. Artificial Intelligence for Advancing Eye Care in Resource-Poor Settings: Assessing the Predictive Accuracy of an AI-Model for Diabetic Retinopathy Screening in India

    Rohan Chawla, Prachi Karkhanis, Malay Shah, Aritra Das, Rishabh Sharma, Dhwani Almaula, Pradeep Venkatesh, Harsh Vardhan Singh, Mukul Kumar, Ramanuj Samanta, Vinod Kumar, Amar Shah, Bhavin Vadera, Nakul Jain, Akanksha Sen, Shyamsundar Shreedhar, Vipin Garg, Soma Dhavala, Kowshik Ganesh, Srinivas Rana, Radhika Tandon. Global Epidemiology, 2025. [paper]

  3. Automatic Interpretation of Line Probe Assay Test for Tuberculosis

    Jatin Agrawal, Mukul Kumar, Avtansh Tiwari, Sachin Danisetty, Soma Dhavala, Nakul Jain, Prasaanth Balraj, Niket Singh, Siddhant Shingi, Jayakrishna Kurada, Raghuram Rao, S Anand, Nishant Kumar. Proceedings of the AAAI Conference on Artificial Intelligence, 2024. [paper]

Beyond the desk

A few things I've done outside of my core work.

  1. Speaking & Training 2021 to present

    Talks, Panels & Workshops

    Spoken at ACM COMPASS 2024 on AI for healthcare delivery in India, been part of panel discussions, and facilitated 8 AI training workshops for medical professionals, senior government officials, and partner agencies.

  2. Field Visits 2021 to 2025

    Travelling Across India for Fieldwork

    While at Wadhwani AI, travelled to remote areas across multiple Indian states to talk to users, patients, doctors, and frontline health workers, collecting data, understanding ground realities, and shaping the AI products around real needs. One of the experiences I cherish the most.

Contact

Email is the best way to reach me at muk137kumar@gmail.com, though LinkedIn works too. I read everything and reply to most.