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Computer Science

D-Index
43
Citations
7128
World Ranking
8034
National Ranking
3452

Overview

Jinjun Xiong is affiliated with the University at Buffalo, State University of New York in the United States. Their research primarily spans the field of Computer Science, with a focus on several specialized subfields.

The main subfields of study that encompass their work include:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Computer Networks and Communications
  • Hardware and Architecture

Within these domains, their research topics cover:

  • Advanced Neural Network Applications
  • Topic Modeling
  • Advanced Graph Neural Networks
  • Adversarial Robustness in Machine Learning
  • Natural Language Processing Techniques
  • Parallel Computing and Optimization Techniques
  • Advanced Image and Video Retrieval Techniques

The recent papers authored or coauthored by Jinjun Xiong include:

  • "On Interpretability of Artificial Neural Networks: A Survey," 2021, published in IEEE Transactions on Radiation and Plasma Medical Sciences
  • "Universal approximation with quadratic deep networks," 2020, published in Neural Networks
  • "On Interpretability of Artificial Neural Networks: A Survey," 2020, published on arXiv (Cornell University)
  • "Enabling Design Methodologies and Future Trends for Edge AI: Specialization and Codesign," 2021, published in IEEE Design and Test
  • "EMOGI," 2020, published in Proceedings of the VLDB Endowment

Some of the frequent coauthors collaborating with Jinjun Xiong are:

  • Wen-mei Hwu
  • Deming Chen
  • Dancheng Liu
  • Yiyu Shi
  • Chenhui Xu

Regarding publication venues, Jinjun Xiong has contributed to various outlets extensively, including:

  • arXiv (Cornell University)
  • IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
  • IEEE Design and Test
  • Proceedings of the VLDB Endowment
  • Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Best Publications

  • On Interpretability of Artificial Neural Networks: A Survey

    Feng-Lei Fan;Jinjun Xiong;Mengzhou Li;Ge Wang

  • Robust Extraction of Spatial Correlation

    Jinjun Xiong;V. Zolotov;Lei He

  • DNNBuilder: an automated tool for building high-performance DNN hardware accelerators for FPGAs

    Xiaofan Zhang;Junsong Wang;Chao Zhu;Yonghua Lin

  • Method, system, and program product for computing a yield gradient from statistical timing

    Chandramouli Visweswariah;JinJun Xiong;Vladimir Zolotov

  • Revisiting RCNN: On Awakening the Classification Power of Faster RCNN

    Bowen Cheng;Yunchao Wei;Honghui Shi;Rogério Schmidt Feris

  • Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation

    Zhonghao Wang;Mo Yu;Yunchao Wei;Rogerio Feris

  • FPGA/DNN Co-Design: An Efficient Design Methodology for 1oT Intelligence on the Edge

    Cong Hao;Xiaofan Zhang;Yuhong Li;Sitao Huang

  • TS2C: Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection

    Yunchao Wei;Zhiqiang Shen;Bowen Cheng;Honghui Shi

  • SPGNet: Semantic Prediction Guidance for Scene Parsing

    Bowen Cheng;Uiuc Uiuc;Liang-Chieh Chen;Yunchao Wei

  • Statistical Path Selection for At-Speed Test

    Vladimir Zolotov;Jinjun Xiong;Hanif Fatemi;Chandu Visweswariah

  • Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases

    Ren Wang;Gaoyuan Zhang;Sijia Liu;Pin-Yu Chen

  • A co-design framework of neural networks and quantum circuits towards quantum advantage.

    Weiwen Jiang;Jinjun Xiong;Yiyu Shi

  • Enabling real-time multi-messenger astrophysics discoveries with deep learning

    E. A. Huerta;Gabrielle Allen;Igor Andreoni;Javier Mauricio Antelis

  • Reinforcement learning based text style transfer without parallel training corpus

    Hongyu Gong;Suma Bhat;Suma Bhat;Lingfei Wu;Jinjun Xiong

  • Universal approximation with quadratic deep networks

    Fenglei Fan;Jinjun Xiong;Ge Wang

  • FPGA Performance Optimization Via Chipwise Placement Considering Process Variations

    Lerong Cheng;Jinjun Xiong;Lei He;Mike Hutton

  • Non-linear statistical static timing analysis for non-Gaussian variation sources

    Lerong Cheng;Jinjun Xiong;Lei He

  • Criticality computation in parameterized statistical timing

    Jinjun Xiong;Vladimir Zolotov;Natesan Venkateswaran;Chandu Visweswariah

  • Accelerating reduction and scan using tensor core units

    Abdul Dakkak;Cheng Li;Jinjun Xiong;Isaac Gelado

  • Model-guided derivation of lumbar vertebral kinematics in vivo reveals the difference between external marker-defined and internal segmental rotations.

    Xudong Zhang;Jinjun Xiong

  • Accelerating Reduction and Scan Using Tensor Core Units

    Abdul Dakkak;Cheng Li;Isaac Gelado;Jinjun Xiong

  • Enabling real-time multi-messenger astrophysics discoveries with deep learning

    E. A. Huerta;Gabrielle Allen;Igor Andreoni;Javier M. Antelis

Frequent Co-Authors

Wen-mei W. Hwu
Wen-mei W. Hwu University of Illinois at Urbana-Champaign
Yiyu Shi
Yiyu Shi University of Notre Dame
Vladimir Zolotov
Vladimir Zolotov IBM (United States)
Lei He
Lei He University of California, Los Angeles
Deming Chen
Deming Chen University of Illinois at Urbana-Champaign
Yunchao Wei
Yunchao Wei Beijing Jiaotong University
Nam Sung Kim
Nam Sung Kim University of Illinois at Urbana-Champaign
Rogerio Feris
Rogerio Feris IBM (United States)
Rakesh Nagi
Rakesh Nagi University of Illinois at Urbana-Champaign
Sijia Liu
Sijia Liu Michigan State University

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