Aditya Ponnada
Staff Quantitative User Researcher
Boston, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolAditya Ponnada is a Staff Quantitative User Researcher with a decade of experience at the intersection of HCI and AI, currently leading measurement and modeling of developer experiences and responsible agentic workflows at MongoDB. He builds large-scale quantitative research practices—having launched experience metrics and MaxDiff choice-modeling that drove double- to triple-digit engagement gains—and previously advanced personalization and human-in-the-AI systems at Spotify. His background spans intensive longitudinal wearable studies, practical ML for behavior prediction, and hands-on product experimentation, with open-source tools (MixWILD) and research that have been widely adopted in academia and industry. Known for turning complex interaction data into actionable product strategies, he blends rigorous causal analysis with pragmatic product launches and a talent for scaling research infrastructure.
10 years of coding experience
10 years of employment as a software developer
B.Des (Design), Interaction Design, B.Des (Design), Interaction Design at Indian Institute of Technology, GuwahatiDoctor of Philosophy (PhD), Human Computer Interaction, Doctor of Philosophy (PhD), Human Computer Interaction at Northeastern University
English, Hindi, Telugu
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (44)
prediction-model10
modeling-tool10
sampling10
multilevel10
modeling10
python9
zip4j7
zip5
commons4
storage4
java4
gcp4
cloud-storage4
aws4
google-cloud4
Programming languages (5)
Github contributions (5)
reach-lab/MixWildGUI
Nov 2016 - Jul 2020
Mix-WILD is statistical software designed to perform multilevel modeling on intensive longitudinal experience sampling data.
Contributions:6 releases, 739 commits, 45 PRs in 3 years 8 months
pythonstatisticalwilddata-samplingexperience-sampling
adityaponnada/microEMA-Preprocessing
Apr 2018 - Oct 2018
This repository contains the helper R and Python scripts to preprocess and prepare microEMA data for ecological validity studies
Contributions:51 PRs, 116 pushes, 2 branches in 6 months
pythonr-and-pythonvaliditypreparepreprocess
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