Gaoxiang Luo
“People will adopt a point of view more readily when they are allowed to arrive at it themselves, than when they are told.” - Benjamin Franklin
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May 2024 -
Our paper Enabling Visual Recognition at Radio Frequency will appear at MobiCom 2024!
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May 2024 -
I will be starting my Machine Learning Engineer Internship at Zscaler at San Jose office, hosted by James Zhu!
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May 2024 -
My wife and I release an open-access tool MetaMate to streamline the data extraction process for educational systematic reviews and meta-analyses!
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Mar 2024 -
Our paper An In-Depth Evaluation of Federated Learning on Biomedical Natural Language Processing for Information Extraction has been accepted to npj Digital Medicine (IF: 15.2)!
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August 2023 -
Our paper Rethinking Transfer Learning for Medical Image Classification has been accepted to BMVC 2023 (oral)!
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July 2023 -
Our paper Ability of Artificial Intelligence to Identify Self-Reported Race in Chest X-Ray Using Pixel Intensity Counts has been accepted to Journal of Medical Imaging (JMI)!
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September 2022 -
Our paper Evaluation of Federated Learning Variations for COVID-19 Diagnosis Using Chest Radiographs from 42 US and European Hospitals accepted to Journal of the American Medical Informatics Association (JAMIA)!
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August 2022 -
Here is a Cisco blog and my exit presentation for my internship at Cisco Research working on Federated Learning.
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May 2022 -
Our paper SAMCNet: Towards a Spatially Explainable AI Approach for Classifying MxIF Oncology Data accepted to ACM SIGKDD 2022!
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Apr 2022 -
I will be joining University of Pennsylvania to pursue a Ph.D. in Computer and Information Science!
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Dec 2021 -
Obtained my B.S. degree with high distinction from the University of Minnesota!
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Sep 2021 -
Accepted to CS Research Mentorship Program (CSRMP) at Google Research!
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Sep 2021 -
Our Federated Learning use case was highlighted in Nvidia Clara White Paper.
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Enabling Visual Recognition at Radio Frequency
H. Lai , G. Luo , Y. Liu , M. Zhao
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An In-Depth Evaluation of Federated Learning on Biomedical Natural Language Processing for Information Extraction
L. Peng , G. Luo , S. Zhou , J. Chen , Z. Xu , R. Zhang , J. Sun
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Rethink Transfer Learning for Medical Image Classification
L. Peng , H. Liang , G. Luo , T. Li , J. Sun
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Evaluation of Federated Learning Variations for COVID-19 Diagnosis Using Chest Radiographs from 42 US and European Hospitals
L. Peng , G. Luo , A. Walker , Z. Zaiman , E. Jones , et al.
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