Tianqin Li is a Co-Founder and CMU PhD researcher with nine years of experience at the intersection of artificial and natural intelligence, specializing in robust, efficient computer vision for scene understanding. Based in Pittsburgh, she has led research across CMU labs and industry internships (Bosch Research) on vision representation learning, self-supervised pretraining, and domain adaptation for time-series and high-resolution data. Her work blends deep learning research with applied system concerns—fine-tuning models for downstream detection tasks and making vision models practical for real-world settings like autonomous driving. She also has a cross-disciplinary background in biotechnology and mathematics, and led an award-winning iGEM software team, reflecting unusual fluency bridging wet-lab challenges and computational methods.
9 years of coding experience
2 years of employment as a software developer
Mathematics and Computer Science, Mathematics and Computer Science at University of California, Berkeley
Bachelor of Science - BS Biotechnology, Bachelor of Science - BS Biotechnology at Sun Yat-sen University
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Carnegie Mellon University School of Computer Science
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