The Analysis and Design of Data Algorithms, Processes, and Theories (ADDAPT) lab at Georgia Tech studies machine learning from the data side: how data gets collected, which data matters most, and how it gets modeled.
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People
People
Current PhD Students
Kangping Hu: PhD in CS (2025 - )
Hangyu Zhou: PhD in ML (2025 - )
Anisha Pal: PhD in CS (2026 - )
Current BS & MS Students
Archit Shinde: BS in CS
Diya Kaimal: BS in CS
Kabir Kang: MS in CS
Naman Talreja: BS in CS
Nash Moore: BS in CS
Neel Bhattacharyya: BS in CS
Suman Krishna: BS in CS
Tanmay Chavan: MS in CS
Tony Qin: BS in CS
Yu-An Chen: BS/MS in CS
Yukai Ma: MS in CS
Yuxuan (Leon) Liang: BS in CS
Alumni
Kalp Vyas: MS in CS
Sai Gokhale: MS in CS
Saloni Bedi: BS/MS in CS
Wei-Liang (Edison) Liao: BS in CS
Papers
Papers
Preprints
Kangping Hu & Stephen Mussmann. Myopic Bayesian Decision Theory for Batch Active Learning with Partial Batch Label Sampling. Arxiv link
Stephen Mussmann. The Approximation Ratio for the Risk of Myopic Bayesian Active Learning for Linear Regression. Arxiv link
Published
Kabir Kang & Stephen Mussmann. Instance-Level Costs for Nuanced Classifier Evaluation. ICML 2026. Arxiv link
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