Author

Kai Chang

Stanford University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Same name, identified by ORCID

Biology Disciplines

Click to filter author papers

Bioengineering· 1 Cancer Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:human· 2 Approach:machine learning (classical)· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Assay:imaging· 1

Frequent Co-Authors

Ariel StiberiD· 2 shared Jennifer A. DionneiD· 2 shared Amanda GonçalvesiD· 1 shared Amanda KiraneiD· 1 shared Antony Georgiadis· 1 shared Baba Ogunlade· 1 shared Babatunde Ogunlade· 1 shared Boi Bryant Quach· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioengineering

Ariel StiberORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Dynamic, single-cell monitoring of CAR T cell identity and activation with Raman spectroscopy

Ariel Stiber, Boi Bryant Quach, Babatunde Ogunlade, Antony Georgiadis, Kai Chang, Y. Li, Patrick J. Quinn, Haoqing Wang, Kristin CY Tsui, Charm Ang, Elena Sotillo, David Bernard Miklos, Crystal Lee Mackall, Zinaida Good, Jennifer A. Dionne

Gold-nanorod surface-enhanced Raman spectroscopy with LightGBM separates CAR T from untransduced T cells, tracks antigen-specific activation dynamics, and discriminates sorted CAR+ from CAR- patient T cells.

bioRxiv · Jul 18, 2026 · PreprintBioengineering✦ In-depth digest

Predicting targeted- and immunotherapeutic response outcomes in melanoma with single-cell Raman Spectroscopy and AI

Kai Chang, Mamatha Serasanambati, Baba Ogunlade, Hsiu-Ju Hsu, James Paul Agolia, Ariel Stiber, Jeffrey Gu, Jay Chadokiya, Grayson E. Rodriguez, Prabhjeet Singh, Saurabh Sharma, Amanda Gonçalves, Ojasvi Verma, Fareeha Safir, Nhat Vu, , Jennifer A. Dionne

This paper uses single-cell Raman spectroscopy and machine learning to predict therapeutic response in melanoma, achieving >96% accuracy in cell line classification and 91% accuracy in patient drug resistance inference.

bioRxiv · May 16, 2025 · PreprintCancer Biology