Dimitris Stripelis

36 papers A* 1B 1Journal 25Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Supercharging Federated Intelligence Retrieval. CoRR Dimitris Stripelis, Patrick Foley, Mohammad Naseri, William Lindskog-Münzing, Chong Shen Ng, Daniel J. Beutel, Nicholas D. Lane
2025	J	`jnl`	A Technical Policy Blueprint for Trustworthy Decentralized AI. CoRR Hasan Kassem, Sergen Cansiz, Brandon Edwards, Patrick Foley, Inken Hagestedt, Taeho Jung, Prakash Narayana Moorthy, Michael O'Connor, Bruno Rodrigues, Holger Roth, Micah J. Sheller, Dimitris Stripelis, Marc Vesin, Renato Umeton, Mic Bowman, Alexandros Karargyris
2025	J	`jnl`	Beyond DNS: Unlocking the Internet of AI Agents via the NANDA Index and Verified AgentFacts. CoRR 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, Abhishek Singh, Ayush Chopra, Dimitris Stripelis, Bhuwan B, Sumit Kumar, Maria Gorskikh
2025	J	`jnl`	FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models. CoRR Yan Gao, 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, Inseo Song, KangYoon Lee, Hong Jia, Ting Dang, Junyan Wang, Zheyuan Liu, Daniel J. Beutel, Lingjuan Lyu, Nicholas D. Lane
2025	J	`jnl`	Upgrade or Switch: Do We Need a New Registry Architecture for the Internet of AI Agents? CoRR Ramesh Raskar, Pradyumna Chari, Jared James Grogan, Mahesh Lambe, Robert Lincourt, Raghu Bala, Abhishek Singh, Ayush Chopra, Rajesh Ranjan, Shailja Gupta, Dimitris Stripelis, Maria Gorskikh, Sichao Wang
2025	—	`conf`	Upgrade or Switch: Do We Need a Next-Gen Trusted Architecture for the Internet of AI Agents? TPS-ISA Ramesh Raskar, Pradyumna Chari, Mahesh Lambe, Robert Lincourt, Raghu Bala, Aditi Joshi, Jared James Grogan, Abhishek Singh, Ayush Chopra, Rajesh Ranjan, Shailja Gupta, Dimitris Stripelis, Maria Gorskikh, Sichao Wang
2024	J	`jnl`	A federated learning architecture for secure and private neuroimaging analysis. Patterns Dimitris Stripelis, Umang Gupta, Hamza Saleem, Nikhil J. Dhinagar, Tanmay Ghai, Chrysovalantis Anastasiou, Rafael Sanchez, Greg Ver Steeg, Srivatsan Ravi, Muhammad Naveed, Paul M. Thompson, José Luis Ambite
2024	—	`conf`	Adaptive Federated Learning for Automatic Modulation Classification Under Class and Noise Imbalance. AAAI Spring Symposia Jose Sanchez-Viloria, Dimitris Stripelis, Panos P. Markopoulos, George Sklivanitis, Dimitris A. Pados
2024	J	`jnl`	Alopex: A Computational Framework for Enabling On-Device Function Calls with LLMs. CoRR Yide Ran, Zhaozhuo Xu, Yuhang Yao, Zijian Hu, Shanshan Han, Han Jin, Alay Dilipbhai Shah, Jipeng Zhang, Dimitris Stripelis, Tong Zhang, Salman Avestimehr, Chaoyang He
2024	J	`jnl`	Digital Privacy in Healthcare: State-of-the-Art and Future Vision. IEEE Access Shalaka S. Mahadik, Pranav M. Pawar, Raja Muthalagu, Neeli Rashmi Prasad, Sin-Kuen Hawkins, Dimitris Stripelis, Sreedhar Rao, Peter Ejim, Bruce Hecht
2024	J	`jnl`	Fox-1 Technical Report. CoRR Zijian Hu, Jipeng Zhang, Rui Pan, Zhaozhuo Xu, Shanshan Han, Han Jin, Alay Dilipbhai Shah, Dimitris Stripelis, Yuhang Yao, Salman Avestimehr, Chaoyang He, Tong Zhang
2024	J	`jnl`	PolyRouter: A Multi-LLM Querying System. CoRR Dimitris Stripelis, Zijian Hu, Jipeng Zhang, Zhaozhuo Xu, Alay Dilipbhai Shah, Han Jin, Yuhang Yao, Salman Avestimehr, Chaoyang He
2024	—	`conf`	ScaleLLM: A Resource-Frugal LLM Serving Framework by Optimizing End-to-End Efficiency. EMNLP (Industry Track) Yuhang Yao, Han Jin, Alay Dilipbhai Shah, Shanshan Han, Zijian Hu, Dimitris Stripelis, Yide Ran, Zhaozhuo Xu, Salman Avestimehr, Chaoyang He
2024	J	`jnl`	ScaleLLM: A Resource-Frugal LLM Serving Framework by Optimizing End-to-End Efficiency. CoRR Yuhang Yao, Han Jin, Alay Dilipbhai Shah, Shanshan Han, Zijian Hu, Yide Ran, Dimitris Stripelis, Zhaozhuo Xu, Salman Avestimehr, Chaoyang He
2024	—	`conf`	TensorOpera Router: A Multi-Model Router for Efficient LLM Inference. EMNLP (Industry Track) Dimitris Stripelis, Zhaozhuo Xu, Zijian Hu, Alay Dilipbhai Shah, Han Jin, Yuhang Yao, Jipeng Zhang, Tong Zhang, Salman Avestimehr, Chaoyang He
2024	J	`jnl`	TorchOpera: A Compound AI System for LLM Safety. CoRR Shanshan Han, Yuhang Yao, Zijian Hu, Dimitris Stripelis, Zhaozhuo Xu, Chaoyang He
2023	J	`jnl`	Federated Learning over Harmonized Data Silos. CoRR Dimitris Stripelis, José Luis Ambite
2023	—	`conf`	MetisFL: An Embarrassingly Parallelized Controller for Scalable & Efficient Federated Learning Workflows. DistributedML@CoNEXT Dimitris Stripelis, Chrysovalantis Anastasiou, Patrick Toral, Armaghan Asghar, José Luis Ambite
2023	J	`jnl`	MetisFL: An Embarrassingly Parallelized Controller for Scalable & Efficient Federated Learning Workflows. CoRR Dimitris Stripelis, Chrysovalantis Anastasiou, Patrick Toral, Armaghan Asghar, José Luis Ambite
2022	J	`jnl`	Federated Named Entity Recognition. CoRR Joel Mathew, Dimitris Stripelis, José Luis Ambite
2022	J	`jnl`	Federated Progressive Sparsification (Purge, Merge, Tune)+. CoRR Dimitris Stripelis, Umang Gupta, Greg Ver Steeg, José Luis Ambite
2022	J	`jnl`	Performance Weighting for Robust Federated Learning Against Corrupted Sources. CoRR Dimitris Stripelis, Marcin Abram, José Luis Ambite
2022	J	`jnl`	Secure Federated Learning for Neuroimaging. CoRR Dimitris Stripelis, Umang Gupta, Hamza Saleem, Nikhil J. Dhinagar, Tanmay Ghai, Rafael Sanchez, Chrysovalantis Anastasiou, Armaghan Asghar, Greg Ver Steeg, Srivatsan Ravi, Muhammad Naveed, Paul M. Thompson, José Luis Ambite
2022	J	`jnl`	Semi-Synchronous Federated Learning for Energy-Efficient Training and Accelerated Convergence in Cross-Silo Settings. ACM Trans. Intell. Syst. Technol. Dimitris Stripelis, Paul M. Thompson, José Luis Ambite
2022	—	`conf`	Towards Sparsified Federated Neuroimaging Models via Weight Pruning. DeCaF/FAIR@MICCAI Dimitris Stripelis, Umang Gupta, Nikhil J. Dhinagar, Greg Ver Steeg, Paul M. Thompson, José Luis Ambite
2022	J	`jnl`	Towards Sparsified Federated Neuroimaging Models via Weight Pruning. CoRR Dimitris Stripelis, Umang Gupta, Nikhil J. Dhinagar, Greg Ver Steeg, Paul M. Thompson, José Luis Ambite
2021	—	`conf`	Membership Inference Attacks on Deep Regression Models for Neuroimaging. MIDL Umang Gupta, Dimitris Stripelis, Pradeep K. Lam, Paul M. Thompson, José Luis Ambite, Greg Ver Steeg
2021	J	`jnl`	Membership Inference Attacks on Deep Regression Models for Neuroimaging. CoRR Umang Gupta, Dimitris Stripelis, Pradeep K. Lam, Paul M. Thompson, José Luis Ambite, Greg Ver Steeg
2021	—	`conf`	Scaling Neuroscience Research Using Federated Learning. ISBI Dimitris Stripelis, José Luis Ambite, Pradeep Lam, Paul M. Thompson
2021	J	`jnl`	Scaling Neuroscience Research using Federated Learning. CoRR Dimitris Stripelis, José Luis Ambite, Pradeep Lam, Paul Thompson
2021	J	`jnl`	Secure Neuroimaging Analysis using Federated Learning with Homomorphic Encryption. CoRR Dimitris Stripelis, Hamza Saleem, Tanmay Ghai, Nikhil J. Dhinagar, Umang Gupta, Chrysovalantis Anastasiou, Greg Ver Steeg, Srivatsan Ravi, Muhammad Naveed, Paul M. Thompson, José Luis Ambite
2021	J	`jnl`	Semi-Synchronous Federated Learning. CoRR Dimitris Stripelis, José Luis Ambite
2020	J	`jnl`	Accelerating Federated Learning in Heterogeneous Data and Computational Environments. CoRR Dimitris Stripelis, José Luis Ambite
2019	B	`conf`	MR-Cubes: On-the-Fly Computation of Location Popularity from Check-in Data Streams. MDM George Constantinou, Chrysovalantis Anastasiou, Dimitris Stripelis, Cyrus Shahabi
2018	—	`conf`	Extending Apache Spark with a Mediation Layer. SBD@SIGMOD Dimitris Stripelis, Chrysovalantis Anastasiou, José Luis Ambite
2017	A*	`conf`	A Scalable Data Integration and Analysis Architecture for Sensor Data of Pediatric Asthma. ICDE Dimitris Stripelis, José Luis Ambite, Yao-Yi Chiang, Sandrah P. Eckel, Rima Habre