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DESCRIPTION:In this talk\, Gaurav will share his journey from conducting cognitive science and computer vision research at Brown University to building applied machine learning systems in industry. He will talk about how cognitive science and AI complement each other\, and how he balanced core AI research with applied projects\, and what he learned along the way. He will also highlight why applied AI projects are important\, the value they bring in bridging theory and real-world impact. Finally\, he’ll share some insights on navigating ML careers\, including his experience as a Machine Learning Engineer\, where research thinking helps him ask the right questions before solving a problem. He’ll reflect on lessons learned from both successes and failures across academia and industry.\n\nGaurav Gaonkar is a Machine Learning Engineer with experience building large-scale personalization and recommendation systems in AdTech. He holds a Master’s degree in Computer Science from Brown University\, where his research focused on computer vision and cognitive science\, exploring how human visual perception can help us improve AI models. At Brown\, he also served as a Teaching Assistant for courses in Deep Learning\, Computer Vision. Gaurav’s work bridges research and engineering\, with a strong focus on building reproducible\, well-structured ML systems. He’s passionate about building systems that connect cutting-edge research to meaningful\, real-world impact.\n\n------\n\nCreate your own Add to Calendar links with addevent.com/r/a \n
X-ALT-DESC;FMTTYPE=text/html:In this talk, Gaurav will share his journey from conducting cognitive science and computer vision research at Brown University to building applied machine learning systems in industry. He will talk about how cognitive science and AI complement each other, and how he balanced core AI research with applied projects, and what he learned along the way. He will also highlight why applied AI projects are important, the value they bring in bridging theory and real-world impact. Finally, he’ll share some insights on navigating ML careers, including his experience as a Machine Learning Engineer, where research thinking helps him ask the right questions before solving a problem. He’ll reflect on lessons learned from both successes and failures across academia and industry.<br><br>Gaurav Gaonkar is a Machine Learning Engineer with experience building large-scale personalization and recommendation systems in AdTech. He holds a Master’s degree in Computer Science from Brown University, where his research focused on computer vision and cognitive science, exploring how human visual perception can help us improve AI models. At Brown, he also served as a Teaching Assistant for courses in Deep Learning, Computer Vision. Gaurav’s work bridges research and engineering, with a strong focus on building reproducible, well-structured ML systems. He’s passionate about building systems that connect cutting-edge research to meaningful, real-world impact.<br /><br />------<br /><br />Create your own Add to Calendar links with addevent.com/r/a <br>
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SUMMARY:Gaurav Gaonkar - From Academia Research to Applied Machine Learning: Lessons from Academia and Industry (ML Industry)
DTSTART;TZID=America/Los_Angeles:20251203T090000
DTEND;TZID=America/Los_Angeles:20251203T100000
DTSTAMP:20261004T151017Z
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STATUS:CONFIRMED
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LOCATION:https://meet.google.com/hwt-bvpb-uqh?hs=122&authuser=0
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