Zhao Research Group

Machine learning (ML) is transforming sensor innovation and material design by enabling data-driven discovery, optimization, and cross-platform standardization. Through the integration of ML and spectroscopy, complex spectral data can now be decoded to reveal hidden chemical, structural, and biological information with unprecedented precision. In our group, ML is seamlessly woven into both experimental and theoretical frameworks to address grand challenges in sensing, material development, and environmental monitoring. By coupling artificial intelligence with advanced nanostructures and spectroscopic techniques such as surface-enhanced Raman spectroscopy (SERS), we are redefining the boundaries of analytical science.

     In collaboration with Profs. Xianyan Chen, Ping Ma, Wenxuan Zhong, Wenzhan Song, Bin Ai, and colleagues from Qatar University and China,  our team has developed deep learning models for virus and bacterial detection, baseline correction, and cross-device spectrum transformation. Recent works include the multiplex detection and quantification of viral co-infections using deep learning–enhanced SERS, functional regression for inter-instrument SERS calibration, and parameter-optimized baseline removal strategies for reliable data interpretation. We have also advanced SERS-based PFAS detection through combined DFT and ML analyses and pioneered methods for extracting true viral spectra and augmenting datasets to improve classification robustness. In parallel, our collaboration with Prof. Bin Ai’s group applies inverse design and convolutional neural networks to engineer plasmonic nanostructures with tailored optical properties and predictive hydrogen-sensing behavior. Beyond research, we are building SpectraGuru, an open-source spectroscopy and AI platform that democratizes access to powerful spectral analytics. Together, these efforts exemplify the transformative role of ML in accelerating discovery and application in health, environmental sustainability, and intelligent material design.

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Publication List

• Sakib Mahmud, Faizul Rakib Sayem, Manal Hassan, Yanjun Yang, Muhammad E. H. Chowdhury, Susu Zughaier, Faycal Bensaali, Yiping Zhao, “Deep learning-based cross-device standardization of surface-enhanced Raman spectroscopy for enhanced bacterial recognition,” Spectrochimica Acta A 347, 126931 (2025).

• Jiaheng Cui, Xianyan Chen, and Yiping Zhao. "Beyond Traditional airPLS: Improved Baseline Removal in SERS with Parameter-Focused Optimization and Prediction," Anal. Chem. 97, 16211 – 16218 (2025).

• Amit Kumar, Joshua C. Rothstein, Yangxiu Chen, Hong Zhang,and Yiping Zhao, “Experimental Raman spectra analysis of selected PFAS compounds: Comparison with DFT predictions,” Journal of Hazardous Materials 494, 138704 (2025).

• 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 10, 3941 – 3952 (2025).

• Samir Belhaouari, Abdelhamid Talbi, Mahmoud Elgamal, Khadija Elmagarmid, Shaimaa Ghannoum, Yanjun Yang, Yiping Zhao, Susu M. Zughaier, Halima Bensmail, "DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins," Heliyon 11, e42550 (2025).

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

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

• Joshua C. 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 3, 1272 - 1284 (2024).  

• Amit Kumar, Md Redwan Islam, Susu M. Zughaier, Xianyan Chen and Yiping Zhao, “Precision Classification and Quantitative Analysis of Multiple Bacteria Biomarkers via Surface-Enhanced Raman Spectroscopy and Machine Learning,” Spectrochimica Acta A 320, 124627 (2024).

• 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 9, 3158 – 3169 (2024).

• Xiangxin Lin, Mingyu Cheng, Xinyi Chen, Jinglan Zhang, Yiping Zhao, and Bin Ai, “Unlocking Predictive Capability and Enhancing Sensing Performances of Plasmonic Hydrogen Sensors via Phase Space Reconstruction and Convolutional Neural Networks,” ACS Sensors 9, 3877 - 3888 (2024).  

• Yanjun Yang, Hao Li, Les Jones, Jackelyn Murray, Hemant Naikare, Yung-Yi C. Mosley, Teddy Spikes, Sebastian Hülck, Ralph A. Tripp, Bin Ai, and Yiping Zhao, “Advancing SERS Diagnostics in COVID-19 with Rapid, Accurate, and Label-Free Viral Load Monitoring in Clinical Specimens via SFNet Enhancement,” Advanced Materials Interfaces, DOI 10.1002/admi.202400013. 

• Yangxiu Chen, Yanjun Yang, Jiaheng Cui, Hong Zhang, and Yiping Zhao, “Decoding PFAS contamination via Raman spectroscopy: A combined DFT and machine learning investigation,” J. Harz. Mater. 465, 133260 (2024). 

• Yilong Ju, ​Oara Neumann, ​Mary Bajomo, ​Yiping Zhao, ​Peter Nordlander, ​Naomi J. Halas, and ​Ankit Patel, “Identifying Surface-Enhanced Raman Spectra with a Raman Library Using Machine Learning,” ACS Nano  17, 21251–21261 (2023).

• ​Chun Liu, Jinglan Zhang, Yiping Zhao, and Bin Ai, “Inverse Design of Plasmonic Nanohole Arrays by Combing Spectra and Structural Color in Deep Learning,” Advanced Intelligent Systems, 2300121 (2023).

• Yanjun Yang, Hao Li, Les Jones, Jackelyn Murray, James Haverstick, Hemant K. Naikare, Yung-Yi C. Mosley, Ralph A Tripp, Bin Ai, Yiping Zhao, “Rapid detection of SARS-CoV-2 RNA in human nasopharyngeal specimens using surface-enhanced Raman spectroscopy and deep learning algorithms,” ACS Sensors 8, 297 - 307 (2023). 

• Zaid Farooq Pitafi, WenZhan Song, Zion Tse, Yanjun Yang, Yiping Zhao, Jackelyn Murray and Ralph Tripp, “Intelligent surface-enhanced Raman scattering sensor system for virus identification,” 2022 IEEE Global Communications Conference, eCF Paper Id: 1570804672.

• Mary M. Bajomo, Yilong Ju, Jingyi Zhou, Simina Elefterescu, Corbin Farr, Yiping Zhao, Oara Neumann, Peter Nordlander, Ankit Patel, and Naomi J. Halas, “Computational chromatography: a machine learning strategy for demixing individual chemical components in complex mixtures,” Proc. Natl. Acad. Sci. U.S.A. 119, e2211406119 (2022).

• Yanjun Yang, Beibei Xu, Jackelyn Murray, James Haverstick, Xianyan Chen, Ralph A. Tripp, and Yiping Zhao, “Rapid and quantitative detection of respiratory viruses using surface-enhanced Raman spectroscopy and machine learning,” Biosensors and Bioelectronics 217, 114721 (2022). 

• Yanjun Yang, Beibei Xu, James Haverstick, Nabil Ibtehaz, Artur Muszyński, Xianyan Chen, Muhammad E. H. Chowdhury, Susu M. Zughaier, and Yiping Zhao, “Differentiation and classification of bacterial endotoxins based on surface enhanced Raman scattering and advanced machine learning,” Nanoscale 14, 8806-8817 (2022). 

• Qun Zhao, Jason Langley, Joonsang Lee, Justin Abell, and Yiping Zhao, “Bioimaging and biospectra analysis by means of independent component analysis: experimental results,” Proc. SPIE Volume 8058, DOI: 10.1117/12.887064 (2011).