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Aditya Ponnada
Mobile health - Personal health informatics - HCI
Aditya Ponnada is a researcher with a background in computer science, design, and behavior science.4 He completed his PhD in Human Computer Interaction at Northeastern University's Khoury College of Computer Sciences, where he was advised by Professor Stephen Intille.14 His research focused on personal health informatics, human-computer interactions, and mobile/wearable interaction design.1
Career Progression
After completing his PhD in 2021, Aditya has held the following positions:
During his time at Spotify, Aditya led foundational studies on generative AI experiences, including AI Playlisting, which was released in April 2024.4
Education
- PhD in Computer Science and Behavior Science from Northeastern University (2015-2021)4
- B.Des in Industrial Design from Indian Institute of Technology, Guwahati, India (2009-2013)14
Research Interests
Aditya's research interests include:
- Human-computer interaction
- Mobile/ubiquitous computing
- Behavioral assessments
- Personal health informatics
- Data science and causal analysis methods146
His work aims to use mobile and wearable devices to measure behaviors that sensors cannot directly measure, using techniques such as ecological momentary assessment.5
Recent Activities
As of May 1, 2024, Aditya gave a presentation at Northeastern University on recommender systems and user behavior analysis, which was well-received by students.3
Highlights
Happy to share our latest Spotify R&D blog post on our WebSci'24 paper, "A Genre-Based Analysis of New Music Streaming at Scale." If you are attending WebSci'24, don't miss the amazing talk by Sam Way on Thu, May 23 😃 .
This paper addresses a fundamental question: How do people stream newly released music? We used data from ~300K newly released songs and the streaming behavior of ~1M Spotify users, to predict the success of new releases across genres and user segments 😮 .
If you enjoy data science/computational behavior science, closely follow pop culture, are interested in recommender systems, or love a lot of music, this blog is for you 🤘 !
https://lnkd.in/efuGWVak (Also links to the open-access full paper). Congratulations to all the co-authors: Julie Jiang, Ang Li, Ph.D., Ben Lacker, and Sam Way 🙌
#music #spotify #newreleases #datascience #behaviorscience #recsys #websci
