Mining Public Datasets for Modeling Intra-City PM2.5 Concentrations at a Fine Spatial Resolution. - Yijun Lin 001; Yao-Yi Chiang; Fan Pan; Dimitrios Stripelis; José Luis Ambite; Sandrah P. Eckel; Rima Habre (SIGSPATIAL/GIS, 2017)

A Scalable Data Integration and Analysis Architecture for Sensor Data of Pediatric Asthma. - Dimitris Stripelis; José Luis Ambite; Yao-Yi Chiang; Sandrah P. Eckel; Rima Habre (ICDE, 2017)

Extending Apache Spark with a Mediation Layer. - Dimitris Stripelis; Chrysovalantis Anastasiou; José Luis Ambite (SBD@SIGMOD, 2018)

MR-Cubes: On-the-Fly Computation of Location Popularity from Check-in Data Streams. - George Constantinou; Chrysovalantis Anastasiou; Dimitris Stripelis; Cyrus Shahabi (MDM, 2019)

Accelerating Federated Learning in Heterogeneous Data and Computational Environments. - Dimitris Stripelis; José Luis Ambite (CoRR, 2020)

Scaling Neuroscience Research Using Federated Learning. - Dimitris Stripelis; José Luis Ambite; Pradeep Lam; Paul M. Thompson (ISBI, 2021)

Membership Inference Attacks on Deep Regression Models for Neuroimaging. - Umang Gupta; Dimitris Stripelis; Pradeep K. Lam; Paul M. Thompson; José Luis Ambite; Greg Ver Steeg (MIDL, 2021)

Semi-Synchronous Federated Learning. - Dimitris Stripelis; José Luis Ambite (CoRR, 2021)

Secure Neuroimaging Analysis using Federated Learning with Homomorphic Encryption. - Dimitris Stripelis; Hamza Saleem; Tanmay Ghai; Nikhil J. Dhinagar; Umang Gupta; Chrysovalantis Anastasiou; Greg Ver Steeg; Srivatsan Ravi; Muhammad Naveed 001; Paul M. Thompson; José Luis Ambite (CoRR, 2021)

Towards Sparsified Federated Neuroimaging Models via Weight Pruning. - Dimitris Stripelis; Umang Gupta; Nikhil J. Dhinagar; Greg Ver Steeg; Paul M. Thompson; José Luis Ambite (DeCaF/FAIR@MICCAI, 2022)

Federated Named Entity Recognition. - Joel Mathew; Dimitris Stripelis; José Luis Ambite (CoRR, 2022)

Federated Progressive Sparsification (Purge, Merge, Tune)+. - Dimitris Stripelis; Umang Gupta; Greg Ver Steeg; José Luis Ambite (CoRR, 2022)

Performance Weighting for Robust Federated Learning Against Corrupted Sources. - Dimitris Stripelis; Marcin Abram; José Luis Ambite (CoRR, 2022)

Secure Federated Learning for Neuroimaging. - Dimitris Stripelis; Umang Gupta; Hamza Saleem; Nikhil J. Dhinagar; Tanmay Ghai; Rafael Sanchez; Chrysovalantis Anastasiou; Armaghan Asghar; Greg Ver Steeg; Srivatsan Ravi; Muhammad Naveed 001; Paul M. Thompson; et al. (CoRR, 2022)

Semi-Synchronous Federated Learning for Energy-Efficient Training and Accelerated Convergence in Cross-Silo Settings. - Dimitris Stripelis; Paul M. Thompson; José Luis Ambite (ACM Trans. Intell. Syst. Technol., 2022)

MetisFL: An Embarrassingly Parallelized Controller for Scalable & Efficient Federated Learning Workflows. - Dimitris Stripelis; Chrysovalantis Anastasiou; Patrick Toral; Armaghan Asghar; José Luis Ambite (DistributedML@CoNEXT, 2023)

Federated Learning over Harmonized Data Silos. - Dimitris Stripelis; José Luis Ambite (CoRR, 2023)

Adaptive Federated Learning for Automatic Modulation Classification Under Class and Noise Imbalance. - Jose Sanchez-Viloria; Dimitris Stripelis; Panos P. Markopoulos; George Sklivanitis; Dimitris A. Pados (AAAI Spring Symposia, 2024)

TensorOpera Router: A Multi-Model Router for Efficient LLM Inference. - Dimitris Stripelis; Zhaozhuo Xu; Zijian Hu 001; Alay Dilipbhai Shah; Han Jin; Yuhang Yao; Jipeng Zhang; Tong Zhang 001; Salman Avestimehr; Chaoyang He 001 (EMNLP (Industry Track), 2024)

ScaleLLM: A Resource-Frugal LLM Serving Framework by Optimizing End-to-End Efficiency. - Yuhang Yao; Han Jin; Alay Dilipbhai Shah; Shanshan Han; Zijian Hu 001; Dimitris Stripelis; Yide Ran; Zhaozhuo Xu; Salman Avestimehr; Chaoyang He 001 (EMNLP (Industry Track), 2024)

Digital Privacy in Healthcare: State-of-the-Art and Future Vision. - Shalaka S. Mahadik; Pranav M. Pawar; Raja Muthalagu; Neeli Rashmi Prasad; Sin-Kuen Hawkins; Dimitris Stripelis; Sreedhar Rao; Peter Ejim; Bruce Hecht (IEEE Access, 2024)

TorchOpera: A Compound AI System for LLM Safety. - Shanshan Han; Yuhang Yao; Zijian Hu 001; Dimitris Stripelis; Zhaozhuo Xu; Chaoyang He 001 (CoRR, 2024)

PolyRouter: A Multi-LLM Querying System. - Dimitris Stripelis; Zijian Hu 001; Jipeng Zhang; Zhaozhuo Xu; Alay Dilipbhai Shah; Han Jin; Yuhang Yao; Salman Avestimehr; Chaoyang He 001 (CoRR, 2024)

Alopex: A Computational Framework for Enabling On-Device Function Calls with LLMs. - Yide Ran; Zhaozhuo Xu; Yuhang Yao; Zijian Hu 001; Shanshan Han; Han Jin; Alay Dilipbhai Shah; Jipeng Zhang; Dimitris Stripelis; Tong Zhang 001; Salman Avestimehr; Chaoyang He 001 (CoRR, 2024)

Fox-1 Technical Report. - Zijian Hu 001; Jipeng Zhang; Rui Pan 002; Zhaozhuo Xu; Shanshan Han; Han Jin; Alay Dilipbhai Shah; Dimitris Stripelis; Yuhang Yao; Salman Avestimehr; Chaoyang He 001; Tong Zhang 001 (CoRR, 2024)

A federated learning architecture for secure and private neuroimaging analysis. - Dimitris Stripelis; Umang Gupta; Hamza Saleem; Nikhil J. Dhinagar; Tanmay Ghai; Chrysovalantis Anastasiou; Rafael Sanchez; Greg Ver Steeg; Srivatsan Ravi; Muhammad Naveed 001; Paul M. Thompson; José Luis Ambite (Patterns, 2024)

FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models. - Yan Gao 016; Massimo Roberto Scamarcia; Javier Fernández-Marqués; Mohammad Naseri; Chong Shen Ng; Dimitris Stripelis; Zexi Li; Tao Shen; Jiamu Bai; Daoyuan Chen; Zikai Zhang; Rui Hu; et al. (CoRR, 2025)

Upgrade or Switch: Do We Need a New Registry Architecture for the Internet of AI Agents? - Ramesh Raskar; Pradyumna Chari; Jared James Grogan; Mahesh Lambe; Robert Lincourt; Raghu Bala; Abhishek Singh 005; Ayush Chopra; Rajesh Ranjan; Shailja Gupta; Dimitris Stripelis; Maria Gorskikh; et al. (CoRR, 2025)

Beyond DNS: Unlocking the Internet of AI Agents via the NANDA Index and Verified AgentFacts. - Ramesh Raskar; Pradyumna Chari; John Zinky; Mahesh Lambe; Jared James Grogan; Sichao Wang; Rajesh Ranjan; Rekha Singhal; Shailja Gupta; Robert Lincourt; Raghu Bala; Aditi Joshi; et al. (CoRR, 2025)