Ish Rishabh Email & Phone Number

California, United States

Oakland, California, Us

Beverly Hills, California, Us

Most of my efforts have been devoted to the development and enhancements of personalized and non-personalized recommendation services at TicketMaster. The work has involved a vast array of technologies in both software engineering as well as data science. Some of the projects I have been involved with (starting with the earliest):* Batched personalized recommendations: Hadoop-based implementation of collaborative filtering recommendations based on users’ historical purchase and interaction data for over 100 million users.* Improving personalized recommendations by modeling fatigue: We modeled fatigue in personalized recommendations and fan’s past interaction with recommendations to improve the recommendations further. Fan interaction with past recommendations were used as features, along with demographic features of the fans to build a classifier that predicted the probability of the fan clicking a recommended artist. Sorting the recommendations based on this probability provided ~10% improvement in CTR.* Scalable personalized recommendation service: led the development and deployment of the first restful service at TicketMaster serving personalized artists recommendations. Heavily leveraged AWS technologies - beanstalk, EC2, DynamoDB, Lambda. The service became the foundation of the next generation of recommendation services at TicketMaster.* Unified Recommendation Service Architecture (URSA): The current generation of recommendation services at TicketMaster brings under one umbrella all siloed recommendation services and serves as a framework for rapid development and evaluation of multiple recommendation strategies. Uses contextual bandits to optimize the CTR. Multiple methods of personalized recommendations are baked under the hood including item-based collaborative filtering as well as latent factors analysis. URSA now powers all artist recommendations at TicketMaster across multiple channels - desktop, mobile web and mobile apps.

Irvine, Ca, Us

* Situation Estimation and Prediction in Spatio-Temporal Data StreamsPhD Thesis: Developing a framework for estimation and prediction of situations. Data are viewed as spatio-temporal streams over which spatial and temporal operators are defined. Context-based regression and classification models are used to define situation evolution process. Use of context-based models improves the accuracy of prediction. Applications include traffic prediction while taking into consideration the impact of accidents and public events. This prediction engine will eventually become part of EventShop - a framework for determining situations.* Tele-presence: Developed Environment to Environment (E2E) Communication System in collaboration with other colleagues, which brings the emphasis back to the message rather than the medium of communication. Events from sensors like cameras and microphones deployed in the environment are used to determine user presence, location and pose, which in turn are used to select the most appropriate sensors for communication.* Teaching: Have been a teaching assistant on multiple occasions for the following courses: discrete mathematics, Java programming, Python programming.

Worked on indoor localization using controlled ambient sounds. We developed a non-obtrusive audio-based receiver localization technology which leverages existing hardware (speakers) often deployed in shopping malls and consumer stores. Our method can localize a user carrying a smartphone in indoor environment to within 1m. The sever implementation was in Python and client was an Android app. A patent has been filed based on this work (pending).

Worked on enhancing the existing video conferencing system by enabling a remote person to participate in an ongoing video conference call, through Skype.

I worked as Research Scientist at CAIR (DRDO), Bangalore in the Computer Vision Group headed by Dr. Subrata Rakshit. Main area of research were image segmentation, classification and change detection.

Boston, Ma, Us

Worked as a Java/J2EE software engineer.

Bangalore, Karnataka, In

Did my summer internship at Mindtree Consulting, Bangalore. Worked on the implementation of a DHCP server.

Ph.D., Multimedia, Computer Vision

M.S. In Information And Computer Science, Multimedia, Computer Vision

B. Tech, Electronics, Communication Engineering