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layout: about title: about permalink: / subtitle: ML Research @Qualcomm AI Research | MSc @McGill University
profile: align: right image: profile_pic.jpg image_circular: true # crops the image to make it circular # more_info: > # # <p>555 your office number</p> # # <p>123 your address street</p> # # <p>Your City, State 12345</p>
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Machine Learning Engineer | Generative AI Efficiency | Model Compression
Generative AI Efficiency (Qualcomm AI Research): My current work focuses on creating efficient solutions for Large and Small Language Models (LLMs/SLMs), multimodal foundation models, diffusion large language models (dLLMs) and other advanced LLM inference techniques like speculative decoding, accelerating on-device training.
Model Compression (Huawei Noah’s Ark Lab): At Noah’s Ark Lab, Montreal, my work entailed developing and implementing neural network model compression techniques to improve computational performance (quantization, pruning, NAS across conv and transformer based architectures).
Academic Research (McGill University): I obtained a thesis-based Master of Science in Machine Learning, where my research was advised by Prof. Mathieu Blanchette, focussing on applying Reinforcement Learning techniques in Bioinformatics.
Passion Project: My passion extends beyond inference to areas like LLM distributed training, reinforcement learning, kernel optimization and other low level op implementation.
Beyond my work, I spend my leisure time playing badminton, ping pong, and passionately following Formula-1 and Manchester United FC.
555 your office number
123 your address street
Your City, State 12345
layout: about title: about permalink: / subtitle: ML Research @Qualcomm AI Research | MSc @McGill University
profile: align: right image: profile_pic.jpg image_circular: true # crops the image to make it circular # more_info: > # # <p>555 your office number</p> # # <p>123 your address street</p> # # <p>Your City, State 12345</p>
selected_papers: true # includes a list of papers marked as “selected={true}” social: true # includes social icons at the bottom of the page
announcements: enabled: true # includes a list of news items scrollable: true # adds a vertical scroll bar if there are more than 3 news items limit: 12 # leave blank to include all the news in the _news folder
latest_posts: enabled: false scrollable: true # adds a vertical scroll bar if there are more than 3 new posts items limit: 3 # leave blank to include all the blog posts —
Machine Learning Engineer | Generative AI Efficiency | Model Compression
Generative AI Efficiency (Qualcomm AI Research): My current work focuses on creating efficient solutions for Large and Small Language Models (LLMs/SLMs), multimodal foundation models, diffusion large language models (dLLMs) and other advanced LLM inference techniques like speculative decoding, accelerating on-device training.
Model Compression (Huawei Noah’s Ark Lab): At Noah’s Ark Lab, Montreal, my work entailed developing and implementing neural network model compression techniques to improve computational performance (quantization, pruning, NAS across conv and transformer based architectures).
Academic Research (McGill University): I obtained a thesis-based Master of Science in Machine Learning, where my research was advised by Prof. Mathieu Blanchette, focussing on applying Reinforcement Learning techniques in Bioinformatics.
Passion Project: My passion extends beyond inference to areas like LLM distributed training, reinforcement learning, kernel optimization and other low level op implementation.
Beyond my work, I spend my leisure time playing badminton, ping pong, and passionately following Formula-1 and Manchester United FC.