I support the Business Recommendations Engineering team. We are responsible for ML, algorithms, systems, and product experiences, around our Ads, Shopping, and Monetization products at Instagram. We work on wide-variety of problems across ads ranking, ads supply, signals, organic shopping ranking, business content distribution, business growth ML, revenue sentiment trade-offs, business integrity, privacy, and transparency & control.

I support the Business Recommendations team of Engineers, working end to end, on the recommendation system and UX that helps Instagram users connect with businesses they trust and love through ads and ad-like content. We work on problems across delivering advertiser value, user value, user and business safety, and building transparency around our business and businesses on our platform. We work across the stack on ranking, supply optimization, integrity, trust, infra, privacy, signals, and feedback experience with a diverse team of Eng with backgrounds in ML, front end and backend systems, and product.

Ads & Commerce QualityI support a team of Engineers across 3 areas (Quality, Supply, and Trust) working on "people value" for Ads and Commercial content on Instagram. The team spans machine learning, systems, and product engineers. We work on e2e problems for recommendation systems from building front end for user feedback and surveys to backends for ads supply and ranking to machine learning and value function for ads and organic ranking systems. We are growing quickly and we are hiring!

I. Machine Learning @ Google Play Monetization & Platform (2017 - 2018)-- Area Lead for Machine Learning across Commerce, Growth, Analytics, Core Serving and Eng ProductivityII. Store & Vertical Analytics @ Google Play (2015 - 2017)-- Tech Lead Manager of team of 12 (2016 - 2017): User Modeling & Segmentation, Metrics, Data Infrastructure & Quality for Play Store (Apps & Digital Content) & Consumption Apps (Music, Movies, Books)-- Tech Lead Manager of a team of 5 engineers (2016): User Modeling & Segmentation, Metrics, Data Infrastructure & Quality for Play Apps & Games.-- Tech Lead: Metrics (2015-2016) III. Search & Discovery @ Google Research & YouTube (2011 - 2015):-- Content based Comprehensive Video Annotation (2014 - 2015)-- Video Structure Understanding (2014)-- Machine Learning for Large Scale Video Annotation (2012 - 2015)-- YouTube Vibes (http://edition.cnn.com/2012/08/31/tech/web/youtube-moodwall/index.html) (2012)-- YouTube Slam (http://youtube-global.blogspot.com/2011/12/introducing-youtube-slam.html) (2011 - 2012)

Developed visual recognition and machine learning algorithms for object categorization. Developed an algorithm for unsupervised data clustering.

Co-founder of an intelligent apparel search startup in Champaign, IL. Responsible for computer vision and machine learning aspects of the product.

Developed clustering algorithms for object similarity and object categorization applications. Developed algorithms for image ranking and image search using bag of regions as descriptors.

Graded assignments and projects for an introductory course in embedded system design. Set up laboratory sessions. Proctored exams and evaluted students during laboratory sessions.

Developed software in C to implement a new paradigm for Shape Recognition. Extended the algorithm to develop a robust and invariant representation of shapes.

Graded class projects and homeworks. Interacted with graduate students and helped them with homework questions and software development for projects. Maintained class website and compiled final grades.

Developed Speaker Independent Hidden Markov Models for Speech Recognition for the proprietary Nilgiri OCMP at HP Labs.