World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
7669
World Ranking
12425
National Ranking
5038

Electronics and Electrical Engineering

D-Index
33
Citations
7653
World Ranking
5929
National Ranking
1991

Overview

Yih-Fang Huang is affiliated with the University of Notre Dame in the United States and has contributed to the field of Computer Science with a notable emphasis on Artificial Intelligence and Computer Networks and Communications. Their research spans topics related to privacy-preserving technologies, age of information optimization, and stochastic gradient optimization techniques, among others.

Their work covers several specialized areas including:

  • Privacy-Preserving Technologies in Data
  • Age of Information Optimization
  • Stochastic Gradient Optimization Techniques
  • Mobile Crowdsensing and Crowdsourcing
  • Distributed Sensor Networks and Detection Algorithms
  • Privacy, Security, and Data Protection
  • Advanced MIMO Systems Optimization

Yih-Fang Huang has coauthored multiple papers with frequent collaborators such as Stefan Werner, Anthony Kuh, Vinay Chakravarthi Gogineni, François Gauthier, and Francois Gauthier. They have published extensively in various venues, most notably in arXiv (Cornell University), the IEEE Internet of Things Journal, IEEE Transactions on Signal Processing, ICASSP 2022, and IEEE Internet of Things Magazine.

Recent papers include:

  • Nonlinear Adaptive Filtering With Kernel Set-Membership Approach, 2020, IEEE Transactions on Signal Processing
  • Communication-Efficient Online Federated Learning Framework for Nonlinear Regression, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Communication-Efficient Online Federated Learning Strategies for Kernel Regression, 2022, IEEE Internet of Things Journal
  • Personalized Online Federated Learning for IoT/CPS: Challenges and Future Directions, 2022, IEEE Internet of Things Magazine
  • Personalized Graph Federated Learning With Differential Privacy, 2023, IEEE Transactions on Signal and Information Processing over Networks

Their publication record reflects a focus on developing algorithms and frameworks that improve online learning, federated learning, and privacy in interconnected systems such as IoT and CPS. This body of work often addresses the challenges of communication efficiency, personalization, and differential privacy in distributed environments.

Yih-Fang Huang's primary area of expertise is Computer Science, supported by numerous contributions also involving Electrical and Electronic Engineering and Sociology and Political Science. The research distribution highlights a multidisciplinary approach within technology and its societal implications.

Best Publications

  • On the value of information in system identification-Bounded noise case

    Eli Fogel;Y. F. Huang

  • Indeterminacy and identifiability of blind identification

    L. Tong;R.-w. Liu;V.C. Soon;Y.-F. Huang

  • State Estimation in Electric Power Grids: Meeting New Challenges Presented by the Requirements of the Future Grid

    Yih-Fang Huang;S. Werner;Jing Huang;N. Kashyap

  • Set-membership filtering and a set-membership normalized LMS algorithm with an adaptive step size

    S. Gollamudi;S. Nagaraj;S. Kapoor;Yih-Fang Huang

  • Bounds on the number of hidden neurons in multilayer perceptrons

    S.-C. Huang;Y.-F. Huang

  • Asymptotically convergent modified recursive least-squares with data-dependent updating and forgetting factor for systems with bounded noise

    S. Dasgupta;Yih-Fang Huang

  • Stochastic Dynamic Pricing for EV Charging Stations With Renewable Integration and Energy Storage

    Chao Luo;Yih-Fang Huang;Vijay Gupta

  • Stochastic Dynamic Pricing for EV Charging Stations with Renewables Integration and Energy Storage

    Chao Luo;Yih-Fang Huang;Vijay Gupta

  • Placement of EV Charging Stations --- Balancing Benefits among Multiple Entities

    Chao Luo;Yih-Fang Huang;Vijay Gupta

  • Distributed Least Mean-Square Estimation With Partial Diffusion

    Reza Arablouei;Stefan Werner;Yih-Fang Huang;Kutluyil Dogancay

  • BEACON: an adaptive set-membership filtering technique with sparse updates

    S. Nagaraj;S. Gollamudi;S. Kapoor;Yih-Fang Huang

  • Adaptive Distributed Estimation Based on Recursive Least-Squares and Partial Diffusion

    Reza Arablouei;Kutluyil Dogancay;Stefan Werner;Yih-Fang Huang

  • Adaptive interference suppression in multiuser wireless OFDM systems using antenna arrays

    S. Kapoor;D.J. Marchok;Yih-Fang Huang

  • Set-membership adaptive equalization and an updator-shared implementation for multiple channel communications systems

    S. Gollamudi;S. Kapoor;S. Nagaraj;Yih-Fang Huang

  • Source Localization and Tracking Using Distributed Asynchronous Sensors

    Teng Li;A. Ekpenyong;Yih-Fang Huang

  • A subspace method for estimating sensor gains and phases

    V.C. Soon;L. Tong;Y.F. Huang;R. Liu

  • Turbo codes for image transmission-a joint channel and source decoding approach

    Z. Peng;Y.-F. Huang;D.J. Costello

  • Pilot assisted synchronization for wireless OFDM systems over fast time varying fading channels

    S. Kapoor;D.J. Marchok;Y.-F. Huang

  • A recursive estimation algorithm using selective updating for spectral analysis and adaptive signal processing

    Y. Huang

  • Opportunistic transmission scheduling for multiuser MIMO systems

    Liang Dong;Teng Li;Yih-Fang Huang

  • Statistical Signal Processing

    Unknown

Frequent Co-Authors

Vijay Gupta
Vijay Gupta Purdue University West Lafayette
Josef A. Nossek
Josef A. Nossek Technical University of Munich
Daniel J. Costello
Daniel J. Costello University of Notre Dame
Kutluyil Dogancay
Kutluyil Dogancay University of South Australia
Soura Dasgupta
Soura Dasgupta University of Iowa
Taneli Riihonen
Taneli Riihonen Tampere University
Lang Tong
Lang Tong Cornell University
Visa Koivunen
Visa Koivunen Aalto University
Er-Wei Bai
Er-Wei Bai University of Iowa
Danilo P. Mandic
Danilo P. Mandic Imperial College London

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