Amey Porobo Dharwadker
I'm a Machine Learning Engineering Manager at Meta, leading Facebook's Video Recommendations Quality Ranking team. My team's work improves video recommendations for over 2 billion daily users, focusing on content quality enhancements and engagement optimization.
My contributions extend to Facebook News Feed Recommendations and Ads Ranking systems, where my work drove significant improvements in user engagement and revenue across Meta's platforms.
I graduated from Columbia University with MS in Electrical Engineering specializing in Computer Vision. I worked with Prof. Shih-Fu Chang on Video Action Recognition in the Wild.
Before that, I worked on computer vision based Advanced Driver Assistance System (ADAS) algorithms at Analog Devices. I obtained my undergraduate degree from NIT Tiruchirappalli.
I'm passionate about pushing the boundaries of AI to create personalized, meaningful digital experiences at global scale. My interests lie in Recommender Systems, Information Retrieval and Deep Learning. I thrive on tackling problems where optimization metrics are complex and good user experience is hard to formalize.
News
Appeared on the Recommender Systems Experts (Recsperts) podcast to discuss my work on Facebook's billion-scale video recommendations products.
Nominated as AI/ML industry expert judge for the prestigious CES 2025 Innovation Awards.
Invited as a Program Committee Member for the International Conference on Learning Representations (ICLR) 2025.
Invited as a Program Committee Member for the AAAI Conference on Artificial Intelligence 2025.
Gave a talk on "Supercharging Recommendation Systems with Large Language Models" at Machine Learning Prague 2024.
Served as Program Committee Member for ACM RecSys 2024, KDD 2024 and CIKM 2024 conferences.
Featured on Analytics India Magazine discussing my work on video recommendations at Meta.
Discussed my work on large-scale recommendations in an interview with AI Mazagine.
Talked about Building Next-Gen Recommender Systems with Large Language Models at Data Science Salon Conference in San Francisco, USA.
Talked about Decoding Popularity Bias in Large-Scale Recommender Systems at Open Data Science Conference in San Francisco, USA.
Gave a talk on "The Large Language Model Revolution in Recommender Systems Personalization" at Packt's Put Generative AI To Work Conference.
Served as Program Committee Member for the ACM Web Conference 2024.
Gave a talk on Unlocking Personalization in Large-Scale Recommendations at SMU. Thanks for the invitation, Prof. Hady W. Lauw and ACM SIGKDD Singapore.
Organized the VideoRecSys Workshop at RecSys 2023 conference in Singapore (Recording).
Nominated as AI/ML industry expert judge for the prestigious CES 2024 Innovation Awards.
Served as Program Committee Member for UMAP 2023 Conference.
Served as Program Committee Member for AAAI Conference on Artificial Intelligence 2024.
Served as Program Committee Member for ACM RecSys 2023 and CIKM 2023 conferences.
Invited guest on The AI Podcast with Jay Shah, discussing my work leveraging AI and ML to build and improve large-scale recommendations ranking products at Facebook.
Talked about Mastering the Art of Recommender System Evaluation at Data Innovation Summit 2023 in Stockholm, Sweden.
Served as Program Committee Member for the International Workshop on Mining Actionable Insights from Social Networks (MAISoN) at IJCAI 2023.
Chaired an E-commerce research session at ACM Web Conference 2023 in Austin, USA.
Invited as a Program Committee Member for ECAI Prestigious Applications of Intelligent Systems 2023 Conference.
Talked about Navigating the Landscape of Bias in Recommender Systems at MLconf 2023 in New York, USA.
Invited to judge the Globee Information Technology Awards, a premier global recognition that celebrates excellence and innovation in the ever-evolving world of technology.
Talked about Trends in Personalized Video Recommendations at the RE•WORK Enterprise AI Summit 2023 in San Francisco, USA.
Invited reviewer for the IEEE Transactions on Pattern Analysis and Machine Intelligence journal.
Expert commentary on how AI helps people with disabilities featured in this Lifewire article.
Invited to judge the prestigious Edison Awards, honoring excellence in innovation, new product development, marketing and design.
Served as Program Committee Member for UMAP 2023 conference.
Expert commentary on impact of AI generative art on kids featured in this Lifewire article.
Served as Program Committee Member for the IEEE ISCAS 2023 conference.
Served as Program Committee Member for ACM Web Conference 2023 and ECIR 2023.
Invited reviewer for the AISTATS 2023 conference.
Patent Issued - Embeddings for Feed and Pages (filed in March 2017).