About Me
Hi there! I'm Aditya, a PhD student in the Data Mining Research Laboratory at The Ohio State University, advised by Prof. Srinivasan Parthasarathy. My research broadly focuses on graph machine learning and conformal prediction. I am increasingly interested in how conformal ideas can enable more reliable and principled machine learning beyond standard supervised settings.
Before my PhD, I earned both my Bachelor's and Master's degrees in Computer Science & Engineering and Mathematics at The Ohio State University. Basically, I've been a Buckeye for a while, and I wouldn't have it any other way. Go Bucks!
Another passion of mine is teaching and education. I've had the pleasure of working with the Fundamentals of Engineering for Honors program as a teaching associate throughout my time at Ohio State.
News
- 09/2025 | Our work on using Bag of Little Bootstraps for training Heterogeneous GNNs has been accepted at ICDM 2025.
- 07/2025 | Conformal Fairness was accepted to Responsible AI Day at KDD 2025.
- 05/2025 | Starting my internship at Google!
- 04/2025 | Our paper benchmarking conformal prediction for node classification is accepted to TMLR-25.
- 01/2025 | Our paper on fairness for conformal predictors is accepted to ICLR-25.
- 09/2023 | Our paper on graph pattern mining paradigms is accepted to HiPC-23.
- 08/2023 | Began my PhD @ Ohio State!
- 05/2023 | Starting my internship at Cruise!
Selected Publications
Conformal Prediction
FedCF: Fair Federated Conformal Prediction
A. Srinivasan*, A. T. Vadlamani*, A. Meghrazi, S. Parthasarathy
Under Review
Paper (Preprint) Code
Conformal Prediction: A Theoretical Note and Benchmarking Transductive Node Classification in Graphs
P. Maneriker*, A. T. Vadlamani*, A. Srinivasan, Y. He, A. Payani, S. Parthasarathy
Accepted at TMLR 2025. Transactions on Machine Learning Research
A Generic Framework for Conformal Fairness
A. T. Vadlamani*, A. Srinivasan*, P. Maneriker, A. Payani, S. Parthasarathy
ICLR 2025. The Thirteenth International Conference on Learning Representations
Graphs
BLB-HGNN: Bag of Little Bootstraps for Training Heterogeneous GNNs
A.T. Vadlamani, S. Salarian, S. Gurukar, S. Parthasarathy
ICDM 2025. IEEE International Conference on Data Mining (Acceptance confirmed, to appear)
Graph Pattern Mining Paradigms: Consolidation and Renewed Bearing
V. Dias, S. Ferraz, A. Vadlamani, M. Erfanian, C. H. C. Teixeira, D. Meira Jr, S. Parthasarathy
HiPC 2023. IEEE International Conference on High Performance Computing, Data, and Analytics
Education
GIFTS: Exploration Activities for Just-in-Time Learning in a First-Year Engineering Robotics Design-Build Project
A. T. Vadlamani, L. Rumreich, A. H. Phillips
ASEE 2023. 2023 ASEE Annual Conference & Exposition — First-Year Programs Division
* Equal Contribution
Education
The Ohio State University
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PhD in Computer Science & Engineering 08/2023 - Present
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MS in Computer Science & Engineering 01/2022 - 05/2023
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BS in Computer Science & Engineering and Mathematics 08/2018 - 05/2022
Work/Intern Experience
05/2025 - 08/2025
Google
PhD Software Engineer Intern
05/2023 - 08/2023
Cruise LLC
PhD Software Engineer Intern
05/2022 - 08/2022
Amazon.com
Software Development Engineer Intern
05/2021 - 08/2021
Amazon.com
Software Development Engineer Intern
05/2019 - 08/2019
CAS
Technology Intern
Teaching Experience
01/2022 - 05/2023,
08/2024-Present
Graduate Teaching Associate
Fundamentals of Engineering for Honors
08/2019 - 12/2021
Undergraduate Teaching Assistant
Fundamentals of Engineering for Honors
Service
- Program Committee/(External) Reviewer: ICLR, NeurIPS, KDD, PAKDD, SDM