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Hi, I’m Nilay Gupta, a highly qualified AI researcher with 2+ years of direct experience in multimodal deep learning, advanced NLP techniques, and medical robotics. I’ve earned awards for AI research and medical innovation, and I’ve published in multidisciplinary venues. Currently based in London, I’m passionate about turning research into real-world impact—especially at the intersection of healthcare, robotics, and AI. I enjoy building end-to-end AI pipelines, optimizing models with PEFT/LoRA, and collaborating with interdisciplinary teams to deliver clinically meaningful solutions.…Hi, I’m Nilay Gupta, a highly qualified AI researcher with 2+ years of direct experience in multimodal deep learning, advanced NLP techniques, and medical robotics. I’ve earned awards for AI research and medical innovation, and I’ve published in multidisciplinary venues. Currently based in London, I’m passionate about turning research into real-world impact—especially at the intersection of healthcare, robotics, and AI. I enjoy building end-to-end AI pipelines, optimizing models with PEFT/LoRA, and collaborating with interdisciplinary teams to deliver clinically meaningful solutions.

Nilay Gupta

AI Engineer, Data Scientist, AI Developer, +2

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Hi, I’m Nilay Gupta, a highly qualified AI researcher with 2+ years of direct experience in multimodal deep learning, advanced NLP techniques, and medical robotics. I’ve earned awards for AI research and medical innovation, and I’ve published in multidisciplinary venues. Currently based in London, I’m passionate about turning research into real-world impact—especially at the intersection of healthcare, robotics, and AI. I enjoy building end-to-end AI pipelines, optimizing models with PEFT/LoRA, and collaborating with interdisciplinary teams to deliver clinically meaningful solutions.…Hi, I’m Nilay Gupta, a highly qualified AI researcher with 2+ years of direct experience in multimodal deep learning, advanced NLP techniques, and medical robotics. I’ve earned awards for AI research and medical innovation, and I’ve published in multidisciplinary venues. Currently based in London, I’m passionate about turning research into real-world impact—especially at the intersection of healthcare, robotics, and AI. I enjoy building end-to-end AI pipelines, optimizing models with PEFT/LoRA, and collaborating with interdisciplinary teams to deliver clinically meaningful solutions.

Available to hire

Hi, I’m Nilay Gupta, a highly qualified AI researcher with 2+ years of direct experience in multimodal deep learning, advanced NLP techniques, and medical robotics. I’ve earned awards for AI research and medical innovation, and I’ve published in multidisciplinary venues.

Currently based in London, I’m passionate about turning research into real-world impact—especially at the intersection of healthcare, robotics, and AI. I enjoy building end-to-end AI pipelines, optimizing models with PEFT/LoRA, and collaborating with interdisciplinary teams to deliver clinically meaningful solutions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

AI Data Expert at Amazon

October 1, 2025 - September 30, 2024

NLP Research Assistant at CAI Zurich University of Applied Sciences

March 1, 2023 - September 30, 2023

Extracted 10 million tweets via Twitter API to build temporal user data for radical event prediction. Annotated 200 users as radical/non-radical/turned radical using changepoint detection and a density-ratio estimation approach, applying K-Means clustering to group radical vs. non-radical tweets. Catalogued 4000 projects and 12000 publications into 10 topics and 80 subtopics using topic modeling.

Machine Learning Research Intern at Pennsylvania State University

June 1, 2021 - August 31, 2021

Enhanced inter-annual variability capture in monsoon onset predictions (India) by ~20% by comparing ELM, PCR, Random Forest, and XGBoost. Presented a KGML 2021 poster and published abstracts at INTROMET 2021 and 102nd AMS Education.

AI Scientist at Uniphore

October 1, 2023 - September 15, 2024

Deployed an end-to-end few-shot text classification pipeline, achieving 80% accuracy with 5 or fewer training samples, enabling rapid domain adaptation. Fine-tuned transformer models using PEFT/LoRA, reducing compute requirements by 98% while maintaining accuracy. Automated model evaluation and deployment workflows, cutting testing/release cycle times by 90%.