CV

My CV in PDF: Click Here

Education

• University of Georgia, Jun. 2023 - 2027(expected)
  • Ph.D in Engineering, Emphasis in Electrical and Computer Engineering
• Northeastern University, Sept. 2021 – May. 2023
  • Master in Artificial Intelligence, Khoury College of Computer Sciences
• Nankai University, Sept. 2017 - Jun. 2021
  • Bachelor of Science in Statistics, College of Mathematical Sciences
  • Awarded “Best Paper Award” for my bachelor thesis
• University of California, Berkeley, Aug. 2019 - Dec. 2019
  • Berkeley International Study Program
  • Awarded “Global Nankai” Abroad Study Scholarship

Skills

• Programming Languages: Python, JAVA, C++, JavaScript
• Others: OpenCV, R, MATLAB, Latex, Markdown, Android Development, Spark, MySQL, Azure

Publications

Extracting True Virus SERS Spectra and Augmenting Data for Improved Virus Classification and Quantification

Yufang Liu, Yanjun Yang, Haoran Lu, Jiaheng Cui, Xianyan Chen, Ping Ma, Wenxuan Zhong, and Yiping Zhao "Extracting True Virus SERS Spectra and Augmenting Data for Improved Virus Classification and Quantification", ACS Sensors Article ASAP DOI: 10.1021/acssensors.4c03397

Label-free detection of respiratory virus co-infections: integrating surface-enhanced Raman scattering with deep learning

Yanjun Yang, Jiaheng Cui, Amit Kumar, Dan Luo, Jackelyn Murray, Les Jones, Xianyan Chen, Sebastian Hülck, Ralph A. Tripp, and Yiping Zhao "Label-free detection of respiratory virus co-infections: integrating surface-enhanced Raman scattering with deep learning", Proc. SPIE 13298, Photonic Diagnosis, Monitoring, Prevention, and Treatment of Infections and Inflammatory Diseases 2025, 1329802 (19 March 2025)

Multiplex Detection and Quantification of Virus Co-Infections Using Label-free Surface-Enhanced Raman Spectroscopy and Deep Learning Algorithms

Yanjun Yang, Jiaheng Cui, Amit Kumar, Dan Luo, Jackelyn Murray, Les Jones, Xianyan Chen, Sebastian Hülck, Ralph A. Tripp, and Yiping Zhao*, "Multiplex Detection and Quantification of Virus Co-Infections Using Label-free Surface-Enhanced Raman Spectroscopy and Deep Learning Algorithms", ACS Sensors, 2025 10 (2), 1298-1311

Functional Regression for SERS Spectrum Transformation Across Diverse Instruments

Wang, Tao and Yang, Yanjun and Lu, Haoran and Cui, Jiaheng and Chen, Xianyan and Ma, Ping* and Zhong, Wenxuan* and Zhao, Yiping*, "Functional Regression for SERS Spectrum Transformation Across Diverse Instruments", Analyst, 2025, 150, 460-469

Ultra-Sensitive Detection of PFASs using Surface Enhanced Raman Scattering and Machine Learning: A Promising Approach for Environmental Analysis

Joshua Curtis Rothstein, Jiaheng Cui*, Yanjun Yang, Xianyan Chen and Yiping Zhao*, "Ultra-Sensitive Detection of PFASs using Surface Enhanced Raman Scattering and Machine Learning: A Promising Approach for Environmental Analysis", Sensors & Diagnostics 2024 3(8): 1272-1284.

Detection of SARS-CoV-2 in patient specimens by surface enhanced Raman spectroscopy and deep learning

Yanjun Yang, Hao Li, Dan Luo, Jiaheng Cui, Amit Kumar, Leslie Jones, Jackelyn Crabtree, Hemant Naikare, Yung-Yi C. Mosley, Teddy Spikes, Sebastian Hülck, Xianyan Chen, Ralph A. Tripp, Bin Ai, Yiping Zhao*, "Detection of SARS-CoV-2 in patient specimens by surface enhanced Raman spectroscopy and deep learning," Optical Sensing and Detection VIII. Vol. 12999. SPIE, 2024.

Rapid Detection of SARS-CoV-2 Variants Using ACE2-Based SERS Sensor Enhanced by CoVari Deep Learning Algorithms

Yanjun Yang, Jiaheng Cui, Dan Luo, Jackelyn Murray, Xianyan Chen, Sebastian Hülck, Ralph Tripp, and Yiping Zhao*, "Rapid Detection of SARS-CoV-2 Variants Using ACE2-Based SERS Sensor Enhanced by CoVari Deep Learning Algorithms", ACS Sensors 2024 9 (6), 3158-3169

Decoding PFAS Contamination via Raman Spectroscopy: A Combined DFT and Machine Learning Investigation

Yangxiu Chen, Yanjun Yang, Jiaheng Cui, Hong Zhang*, Yiping Zhao*, "Decoding PFAS contamination via Raman spectroscopy: A combined DFT and machine learning investigation.", Journal of Hazardous Materials, Volume 465, 2024, 133260, ISSN 0304-3894.