Shengxi Huang

Shengxi Huang is an assistant professor in the Department of Electrical Engineering, Department of Biomedical Engineering, and Materials Research Institute at Penn State. Huang earned her Ph.D. degree in electrical engineering and computer science at MIT in 2017. Following that, she did postdoctoral research at Stanford University. She obtained her bachelor’s degree with the highest honors at Tsinghua University, China.

Huang is the recipient of multiple awards, including NSF CAREER Award, Johnson & Johnson STEM2D Scholar’s Award (6 awardees worldwide in 6 disciplines), Kavli Fellowship for Nanoscience, Jin Au Kong Award for Best PhD Thesis at MIT, and Ginzton Fellowship at Stanford. Her research interests involve light-matter interactions of quantum materials and nanostructures, the development of new quantum optical platforms and biochemical sensing technologies, and using machine learning to accelerate the characterization and analysis of quantum materials and biosamples.

AI-related Expertise Topics

  • Machine learning analysis for optical data of nanomaterials, quantum materials, biomolecules, and biosamples
  • Machine learning classification and interpretation of Alzheimer’s disease
  • Smart biochemical sensors

Externally Funded AI Projects

  • Johnson & Johnson, Ubiquitous Sensing with High Sensitivity and High Specificity
  • NSF, Understanding Virus Evolution Through Deep Raman Spectroscopy


Related Publications

  • Ziyang Wang, Jiarong Ye, Li Ding, Tomotaroh Granzier-Nakajima, Shubhang Sharma, Isabelle Biase, Mauricio Terrones, Se Hoon Choi, Chongzhao Ran, Rudolph E. Tanzi, Sharon X. Huang, Can Zhang, Shengxi Huang. Rapid Biomarker Screening of Alzheimer’s Disease by Machine Learning and Graphene-Assisted Raman Spectroscopy. bioRxiv 2021.06.03.446929

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Shengxi Huang
Assistant Professor of Electrical Engineering and Biomedical Engineering



The Center for Artificial Intelligence Foundations and Engineered Systems (CAFE), pronounced café, brings together expertise from 75 researchers representing 24 academic units across Penn State with the goal of developing cross-disciplinary interactions. The center’s focus is on accelerating advances by synergistically advancing AI foundations and the techniques to deploy them efficiently toward applications focused on engineered and defense systems. CAFE provides opportunities for research partnerships, faculty/student recruitment, and technology transition to practice.

Center for Artificial Intelligence Foundations and Engineered Systems

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