Scientific Research

Research Field

Cyberphysical Systems (CPS) encapsulate very large networks of “smart” devices (possessing sensing, communication, and computation capabilities) that control physical entities. Notable examples enlist Smart Cities, Smart Grids, Intelligent Transportation, Sensor Networks, and Swarm Robotics. The ever-emerging paradigm of Artificial Intelligence of Things (AIoT) targets solutions that capitalize the computational power of Internet-of-Things (IoT) devices to enable Artificial Intelligence (AI) in system operations.

Our group conducts interdisciplinary research across a broad range of topics and applications pertaining to AIoT / CPS / IoT such as:


– Machine Learning: Federated Learning, Deep Learning, Reinforcement Learning, Online Learning, and Data Mining
– Edge Computing
– Distributed Optimization
– Wireless Networks
– System Theory: Optimization, Estimation, and Control
– Signal Processing: Sparse sampling and Online algorithms

as well as applications in robotics, power systems, transportation, data privacy, and cyber security.

Paper Publications

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• Journal Articles.
• 1. N. Freris, A. Ajalloeian, and M. Vlachos, “Interpretable Embedding and Visualization of Compressed Data.” Accepted at ACM Transactions on Knowledge Discovery from Data, 2022..
• 2. M. Li, J. Qin, N. Freris, and D. Ho, “Multi-Player Stackelberg-Nash Game for Nonlinear System via Value Iteration-Based Integral Reinforcement Learning.” IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 4, pp. 1429-1440, 2022..
• 3. T. Huang, N. Freris, P. R. Kumar, and L. Xie, “A Synchrophasor Data-driven Method for Forced Oscillation Localization under Resonance Conditions.” IEEE Transactions on Power Systems, vol. 35, no. 5, pp. 3927-3939, 2020..
• 4. S. Jabari, N. Freris, and D. Dilip, “Sparse travel time estimation from streaming data.” Transportation Science, vol. 54, no 1, pp. 1-20, 2020..
• 5. P. Latafat, N. Freris, and P. Patrinos, “A new randomized block-coordinate primal-dual algorithm for distributed optimization.” IEEE Transactions on Automatic Control, vol. 64, no. 10, pp. 4050-4065, 2019..

Patents

• 1. N. Freris, O. Öçal, and M. Vetterli, “Method for compressed sensing of streaming data and apparatus for performing the same.” CN105531934B, 2019 / JP6495292B2, 2019 / ES2782830T3, 2020 / HUE047132T2, 2020 / EP3044881B1, 2020 / US10728298B2, 2020,
• 2. N. Freris, F. Fusco, and M. Vlachos, “Method and device for data mining on compressed data vectors.” CN104335176B, 2017 / US10528578B2, 2020,
• 3. C. Hsu, N. Freris, J. Singh, and X. Zhu, “Distortion-aware multihomed scalable video streaming to multiple clients.” US8793391B2, 2014,

Published Books

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Research Projects

• 强化学习融合合约多目标优化研究,进行,
• 绿色高精度感知与终端集成技术,进行,