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Schedule Interview NowMy name is Rishabh J. and I have over 0 years of experience in the tech industry. I specialize in the following technologies: Machine Learning, Artificial Intelligence, Data Analysis, ETL Pipeline, ETL, etc.. I hold a degree in Doctor of Philosophy (PhD), Master of Computer Science (MSCS), Bachelor of Science in Information Technology. Some of the notable projects I've worked on include: LLM-Driven Visual Speech Recognition for Lip Reading, DAVID - An Edge-AI Platform for Smart-Toys, Adaptation of Whisper models to child speech recognition, Synthetic Speaking Children – Why We Need Them and How to Make Them, LLM Optimization and Deployment for Speech and Language Understanding, etc.. I am based in Dublin, Ireland. I've successfully completed 8 projects while developing at Softaims.
My passion is building solutions that are not only technically sound but also deliver an exceptional user experience (UX). I constantly advocate for user-centered design principles, ensuring that the final product is intuitive, accessible, and solves real user problems effectively. I bridge the gap between technical possibilities and the overall product vision.
Working within the Softaims team, I contribute by bringing a perspective that integrates business goals with technical constraints, resulting in solutions that are both practical and innovative. I have a strong track record of rapidly prototyping and iterating based on feedback to drive optimal solution fit.
I'm committed to contributing to a positive and collaborative team environment, sharing knowledge, and helping colleagues grow their skills, all while pushing the boundaries of what's possible in solution development.
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Trinity College Dublin
I’m developing a Visual Speech Recognition (VSR) system that integrates LLMs with visual encoders to improve lip reading, particularly in resolving homophenes. Using datasets like LRS2, LRS3, and Wild
I contributed to the development of the DAVID Smart-Toy platform, an Edge-AI system integrating low-power neural inference with audio and vision sensors. I worked on two embodiments—a smart Teddy bear
Conducted comparative research on fine-tuning state-of-the-art ASR models—Whisper and Wav2Vec2—on child speech datasets. Demonstrated that Whisper offers strong generalization across age groups, while
I contributed to a project addressing data scarcity in child-centric HCI by developing synthetic, privacy-compliant training data. We used StyleGAN2 to generate diverse child faces and combined them w
I specialize in developing and deploying Speech-to-Text (STT) and Large Language Models (LLMs) for low-resource languages, with a focus on real-world applications. My work spans fine-tuning and optimi
Doctor of Philosophy (PhD) in
2021-01-01-2024-01-01
Master of Computer Science (MSCS) in
2019-01-01-2020-01-01
Bachelor of Science in Information Technology in
2015-01-01-2019-01-01