Shigang Chen

About

Shigang Chen is a Professor in the Department of Computer & Information Science & Engineering at the University of Florida. His research focuses on artificial intelligence, machine learning, and related interdisciplinary applications, aiming to design and develop accurate, scalable, and robust AI and machine learning algorithms inspired by fields such as earth sciences, agriculture, smart cities, biomedicine, and public health. His work involves creating innovative algorithms and tools to address complex real-world problems through interdisciplinary approaches.

Research topics

• Materials science
• Chemical engineering
• Chemistry
• Nanotechnology
• Organic chemistry
• Engineering
• Physical chemistry
• Engineering physics
• Physics
• Optoelectronics

Selected publications

• Demeter: Reliable Cross-soil LPWAN with Low-cost Signal Polarization Alignment

  2024-05-29 · 24 citations

  articleOpen access

  Soil monitoring plays an essential role in agricultural systems. Rather than deploying sensors' antennas above the ground, burying them in the soil is an attractive way to retain a non-intrusive aboveground space. Low Power Wide-Area Network (LPWAN) has shown its long-distance and low-power features for aboveground Internet-of-Things (IoT) communication, presenting a potential of extending to underground cross-soil communication over a wide area, which however has not been investigated before. T…

  PublisherOA PDFDOI

• SateRIoT: High-performance Ground-Space Networking for Rural IoT

  2024-12-04 · 17 citations

  articleOpen access

  Rural Internet of Things (IoT) systems connect sensors and actuators in remote areas, serving crucial roles in agriculture and environmental monitoring. Given the absence of networking infrastructure for backhaul in these regions, satellite IoT techniques offer a cost-effective solution for connectivity. However, current satellite IoT architectures often struggle to deliver high performance due to temporal and spatial link challenges. This paper presents SateRIoT, a new network architecture with…

  PublisherOA PDFDOI

• Single Update Sketch with Variable Counter Structure

  Proceedings of the VLDB Endowment · 2023-09-01 · 13 citations

  article

  Per-flow size measurement is key to many streaming applications and management systems, particularly in high-speed networks. Performing such measurement on the data plane of a network device at the line rate requires on-chip memory and computing resources that are shared by other key network functions. It leads to the need for very compact and fast data structures, called sketches, which trade off space for accuracy. Such a need also arises in other application context for extremely large data s…

  PublisherDOI

• Scout Sketch+: Finding Both Promising and Damping Items Simultaneously in Data Streams

  IEEE/ACM Transactions on Networking · 2024-10-04 · 6 citations

  articleSenior author

  Data stream processing holds great potential value in lots of practical application scenarios. This paper studies two new but important patterns for items in data streams, called promising and damping items. The promising items mean that the frequencies of an item in multiple continuous time windows show an upward trend overall, while a slight decrease in some of these windows is allowed. In contrast to promising items exhibiting an increasing trend, the definition of damping items indicates a d…

  PublisherDOI

• XTSFormer: Cross-Temporal-Scale Transformer for Irregular-Time Event Prediction in Clinical Applications

  Proceedings of the AAAI Conference on Artificial Intelligence · 2025-04-11 · 4 citations

  articleOpen access

  Adverse clinical events related to unsafe care are among the top ten causes of death in the U.S. Accurate modeling and prediction of clinical events from electronic health records (EHRs) play a crucial role in patient safety enhancement. An example is modeling de facto care pathways that characterize common step-by-step plans for treatment or care. However, clinical event data pose several unique challenges, including the irregularity of time intervals between consecutive events, the existence o…

  PublisherOA PDFDOI

Recent grants

• SCH: Enabling Data Outsourcing and Sharing for AI-powered Parkinson's Research

  NIH · $1.5M · 2021–2026

• NeTS: Small: Sketching Big Network Data

  NSF · $500k · 2017–2021

• CAREER: Traffic Differentiation in Multihop Wireless Networks

  NSF · $416k · 2007–2012

Frequent coauthors

• Shanwen Tao

  Lanzhou University

  37 shared

• Min Chen

  33 shared

• Yian Zhou

  32 shared

• Qingjun Xiao

  Southeast University

  32 shared

• You Zhou

  Qilu University of Technology

  28 shared

• Chaoyi Ma

  25 shared

• Qiao Yan

  Beijing Automotive Group (China)

  23 shared

• Kui Xie

  Shanghai Jiao Tong University

  23 shared

Labs

• Adaptive Learning & Optimization LabPI

Education

• Ph.D., Computer and Information Science and Engineering

  University of Florida

  2007

• M.S., Computer and Information Science and Engineering

  University of Florida

  2003

• B.S., Computer Science

  University of Science and Technology of China

  1998

Awards & honors

• UF Term Professorship, 2021
• NSF CAREER Award
• UF Research Foundation Professor, 2017
• IEEE Fellow
• ACM Distinguished Scientist, 2016

Similar researchers at University of Florida

• Yuanyuan Leih-61
• Sanjay Rankah-50
• Anand Rangarajanh-44