Ayush Maheshwari

Ayush Maheshwari

Senior Solutions Architect at NVIDIA
Foundation Models, NLP, and AI for Science

Biography

🎉 Update: PhD completed in July 2024 • Currently at NVIDIA • Delivered lectures on Systems View of AI at IIT Kharagpur (Spring 2026)


I am Ayush Maheshwari (आयुष माहेश्वरी), a Senior Solutions Architect at NVIDIA, where I work with the NVAITC India team.

My work focuses on multilingual and domain-specific foundation models, AI for Science, and research collaborations with academic and scientific institutions.

At NVIDIA, I focus on:

  • Foundation Models for Indian languages and scientific domains
  • AI for Science, including geospatial foundation models and air-pollution modeling
  • Research Collaborations with academic institutions and research organizations to advance impactful AI applications

My work spans AI solution architecture, applied research, and community enablement through technical workshops, teaching, and collaborations.

I also served as Adjunct Faculty at IIT Kharagpur, where I delivered lectures in the Deep Learning course during the Spring 2026 semester to a class of 150+ students. These lectures focused on the systems perspective of large-scale AI development, including training, inference, and deployment of modern deep learning systems.

Previously, I completed my PhD at CSE, IIT Bombay under the guidance of Prof. Ganesh Ramakrishnan. I was fortunate to be supported by the Ekal Fellowship during my PhD.

My research interests include natural language processing, machine learning, graph-based learning, and multilingual AI. I have worked on constrained neural machine translation, semi-supervised and unsupervised learning, and data programming.

During my PhD, I was a key member of the neural machine translation project UDAAN, which helps publishers translate technical content into Indian languages at scale. The project is open source and has been used by several Indian government technical education agencies and official language departments.

In my spare time, I enjoy playing table tennis and cricket, and reading about Indian culture, the Ramayana, and the Mahabharata.

Download my resumé
(Last updated: April 2026)

Interests
  • Foundation Models
  • Large Language Models
  • Natural Language Processing
  • AI for Science
  • Human-in-the-loop AI
  • Neural Machine Translation
  • Machine Learning
  • Information Retrieval
Education
  • PhD in Computer Science, Jan 2019 - Aug 2023 (Defended July 2024)

    Indian Institute of Technology Bombay

Updates

  • [Dec 25] Paper on benchmarking LLMs on extremely-low resource Indic languages ! [IndicParam: Benchmark to evaluate LLMs on low-resource Indic langauges]

  • [May 25] Our paper on domain aware lexicon generation is accepted at ACL Main Conference 2025 ❤️ 😊 [LexGen: Domain aware multilingual lexicon generation]

  • [Jan 25] Our paper on synthetic data generation, ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification is accepted at NAACL 2025 🎆🎇 [Paper]

  • [Nov 24] Delighted to announce that my PhD work is awarded with Impactful Research Award 2023 by IIT Bombay ❤️ 🎇!

  • [Oct 24] Joined NVIDIA 😌! Excited to be a part of the future of AI 😇

  • [Sep 24] Our paper on Dictionary Constrained Disambiguation for Improved NMT is accepted at EMNLP 2024 [Paper] ❤️ 😌

Click here for updates archive

Experience

 
 
 
 
 
NVIDIA
Senior Solutions Architect
Oct 2024 – Present Gurugram

Part of NVIDIA AI Technology Center (NVAITC) India, driving research engagements and strategic collaborations.

Responsibilities include:

  • Leading enterprise AI solution architecture and deployment strategies
  • Collaborating with academic and research institutions on cutting-edge AI projects
  • Providing technical expertise on NVIDIA GPU acceleration, large language models, and AI infrastructure
  • Architecting scalable AI solutions for diverse industry verticals
  • Mentoring teams on best practices for AI/ML model development and deployment
  • Led “LLM Development from Scratch” workshop series attended by 1,000+ participants from IITs, CDAC, and AI startups
  • Industry keynote on Mamba/SSM architectures at PREMI 2025, IIT Delhi (100+ attendees)
  • 3-hour hands-on LLM workshop at Conference on Scientific ML, IISc Bangalore (150+ attendees)
  • 10+ sessions at CDAC, IITs, SAIL, and Thapar University on NVIDIA AI stack
 
 
 
 
 
Adjunct Faculty
Jan 2026 – May 2026 Kharagpur
Delivered lectures in the Deep Learning course (Spring 2026) to a class of 150+ students, focusing on the systems perspective of large-scale AI development — covering training infrastructure, inference optimization, and deployment of deep learning models at scale. (Slides)
 
 
 
 
 
Research Scientist
Sep 2023 – Sep 2024 Bengaluru
  1. Led a team of 5 people to build Indic-large language models from scratch.
  2. Developing data collection & processing pipelines for training and evaluation.
  3. Training of tokenizer and designing model training architecture.
  4. Training the model on large Intel Gaudi-2 cluster.
  5. Instruction tuning and preference training of the pre-trained models.
 
 
 
 
 
Adobe Research
Research Intern
May 2021 – Aug 2021 Bengaluru

Worked on prototyping new service for Adobe PDF in the legal domain Responsibilities include:

  • Modeling of the problem
  • Designing, developing and prototyping using ML
  • Deployment and Demonstration
 
 
 
 
 
IIT Bombay
Project Engineer
Jan 2016 – Dec 2018 Mumbai
Develop software solutions for security agencies
 
 
 
 
 
Tata Consultancy Services
System Engineer
Oct 2011 – Jul 2013 Mumbai

Projects

UDAAN - An NMT pipeline + Post-editing tool to translate document (Best Paper Award at CODS-COMAD 2023)
An end-to-end Machine Translation and post-editing platform that has translated >50 books across 10 Indian languages. 100+ professional translators actively use UDAAN to upload documents, obtain MT output, and edit translations. Received Presidential recognition and Best Paper Award at CODS-COMAD 2023. Includes >100 digitized dictionaries freely available from CSTT.
SPEAR - Programmatically label and quickly build training data
A widely-adopted open-source Python library for programmatic data labeling with 100+ GitHub stars. SPEAR reduces data labeling efforts by implementing cutting-edge data programming approaches (Snorkel, ImplyLoss, Learning to Reweight). Integrates semi-supervised learning for efficient training and inference. Featured at EMNLP 2021.
Temples of India
Temples of India is a not-for-profit knowledge platform to document and store possibly all details of temples across Indian subcontinent. We aim to present each detail related to the temple such as its location, images of the temple, videos, open and close timings, etc.

Awards & Honors

Impactful Research Award 2023
Awarded for impactful research contributions during PhD at IIT Bombay
Best Paper Award
Our paper on translation post-editing tool (UDAAN) won the best paper award at CODS-COMAD 2023
Ekal Fellowship for PhD Research
Funded by Ekal Fellowship throughout PhD research at IIT Bombay

1:1 Mentoring & Consultations

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🎓 PhD Applications & Research 🤖 NLP & Machine Learning 💼 Career Guidance 📝 Paper Reviews & Feedback
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