UAlbany Department of Biological Sciences Researcher Spotlight: Ruogu Wang and AI in Biological Imaging
Research Contributions in AI
The University at Albany Department of Biological Sciences is excited to highlight another outstanding researcher: Dr. Ruogu Wang, a postdoctoral fellow from Professor Alex Valm’s Lab. Dr. Wang's current work focuses on combining artificial intelligence (AI) with biological imaging.
Academic and Research Pathway
Dr. Wang possesses a Bachelor’s degree in Mathematics from Nankai University and he earned his Ph.D. in Mathematics from the University at Albany. His research is focused on statistical learning, spectral unmixing, and the use of machine learning to address complex problems in biological analysis. Dr. Wang is a postdoctoral researcher working with Professor Alex Valm at UAlbany's Department of Biological Sciences. His recent paper, as the primary author and developed in partnership with Professor Valm’s lab, was just accepted for publication in Briefings in Bioinformatics. In this peer-reviewed paper Dr. Wang describes state-of-the art methods that utilize AI to analyze biological systems by integrating machine learning with computational and imaging techniques.
Research Summary
Dr. Wang’s research focuses on biological spectral unmixing, an important technique used in fluorescence microscopy to analyze complex biological samples. With members of the Valm Lab, he developed and then tested the Multi-View Linear Mixture Model (MV-LMM), a machine learning framework that enhances the accuracy and flexibility of spectral unmixing. The MV-LMM uses both excitation and emission spectra to address the challenge of spectral overlap in biological samples, thereby improving data interpretation and analysis of fluorescence-based imaging.
For additional information on Dr. Wangs publication, please see: Wang, R., Feng, Y., & Valm, A. M. (2025). A framework of multi-view machine learning for biological spectral unmixing of fluorophores with overlapping excitation and emission spectra. Briefings in Bioinformatics, 26(1).
Motivation for Postdoctoral Studies
Dr. Wang joined the Valm Lab because of his interest in studying the human microbiome which includes the fields of microbiology, genomics, bioinformatics, molecular biology, ecology, evolution and systems biology. By applying the tools and methodologies typically used in these fields plus AI, the Valm Lab has gained a better understanding of the microbiome's role in human health and disease.
Contribution to the Field
The MV-LMM method addresses spectral overlap more effectively than traditional methods thereby allowing the use of additional fluorophores in biological analyses. Incorporating AI technology into their current research allowed Dr. Wang to explore microbial structures and functions with greater efficiency and accuracy resulting in a better understanding of the human microbiome.
Advice for Students
Dr. Wang encourages students to embrace an interdisciplinary education and remain curious. He stresses the importance of constantly learning new skills and techniques across various fields and disciplines.
Congratulations to Dr. Wang and members of the Valm lab for their commitment leading to their most recent publication. This research highlights the University's role as a Carnegie R1 institution in offering the essential resources and expertise that enable groundbreaking scientific discoveries. Their work not only provides a better understanding of the human microbiome through AI but also demonstrates the importance of a collaborative and supportive academic and research environment.
Links:
Information on the Department of Biological Sciences Undergraduate Research Program
Information on the Ph.D. in Biology Program
Information on the M.S. in Biology Program
Information on the M.S. in Forensic Science and Management Program
Information on Department of Biological Sciences Faculty Research and Publications
Information on the Capital District Postdoc Association