Qingfang Liu

Background

About Qingfang Liu

I’m drawn to technology for its power to reshape the future, unbound by bureaucracy or the status quo. I’m drawn to psychology for its ability to uncover what lies beneath, beyond the superficial. At their intersection, I’ve spent nearly a decade using computational and experimental methods to understand the human mind. I received interdisciplinary training through the following path- PhD in Psychology, with a computational focus on building cognitive models to explain, simulate, and predict human behavior and brain data in a Bayesian framework - MS in Statistics, with a strong foundation in statistical principles and state-of-the-art ML/DL methods - Postdoctoral researcher leading experimental work in human cognitive neuroscience (fMRI/TMS), including clinical trials - Currently a research fellow at NIH, leveraging computational approaches to deepen our understanding of cognition and contribute to mental health research Core strengths- End-to-end data science: from experimental design and large-scale data collection to modeling, visualization, and deployment - Advanced ML/DL applied to large, high-dimensional data in life sciences and healthcare - Statistical rigor (Bayesian and frequentist), with an operations-research mindset - Fast self-learning and cross-disciplinary knowledge transfer - Clear, concise communication: 20+ talks, peer-reviewed papers, and mentorship of students and cross-functional teams I’m now exploring data science and ML roles in health tech, pharma, and biotech where I can combine scientific depth with industry speed—and eventually build products of my own. If you’re working at the intersection of AI, life sciences, and impact, I’d love to connect.