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We are the Intelligent System (IntelliSys) Lab at the ECE Department of Stevens Institute of Technology. Our research bridges artificial intelligence (AI) and novel system architectures by designing efficient and robust AI algorithms and developing intelligent and high-performance computing systems. Check our roadmap.


News

12/09/2024 :pencil: Our paper “WHALE-FL: Wireless and Heterogeneity Aware Latency Efficient Federated Learning over Mobile Devices via Adaptive Subnetwork Scheduling” has been accepted by AAAI 2025!
11/21/2024 :trophy: Our paper Stellaris: Staleness-Aware Distributed Reinforcement Learning with Serverless Computing has received the ACM/IEEE SC’24 Best Student Paper Finalist!
11/20/2024 :trophy: Our paper Pre-Warming is Not Enough: Accelerating Serverless Inference with Opportunistic Pre-Loading has won the ACM SoCC’24 Best Paper Award!
10/26/2024 :video_camera: Please check all the cool labs and researchers at iCNS and ECE @ Stevens [YouTube]!
10/07/2024 :calendar: Dr. Wang gives a talk on Large-scale Distributed DRL with Serverless Computing at Politecnico di Torino in Turin, Italy, hosted by Prof. Carla Fabiana Chiasserini.
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Selected Publications

  1. KDD
    CriticalFL: A Critical Learning Periods Augmented Client Selection Framework for Efficient Federated Learning
    In Proceedings of the ACM Special Interest Group on Knowledge Discovery and Data Mining (KDD) 2023
  2. ASPLOS
    RainbowCake: Mitigating Cold-starts in Serverless with Layer-wise Container Caching and Sharing
    In Proceedings of the ACM Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) 2024
  3. ICLR
    Backdoor Federated Learning by Poisoning Backdoor-Critical Layers
    Accepted by the International Conference on Learning Representations (ICLR) 2024
  4. SC
    Stellaris: Staleness-Aware Distributed Reinforcement Learning with Serverless Computing (Best Student Paper Finalist)
    Accepted by the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC) 2024

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