معرفی
Qihang Lin is a Professor and the Gary C. Fethke Research Professor in Business Analytics at the Tippie College of Business, University of Iowa, where he also serves as Faculty Director of the part-time Master of Science in Business Analytics (MSBA-PT) program. His academic leadership and research excellence position him at the forefront of optimization and data science.
Dr. Lin holds a PhD in Algorithms, Combinatorics, and Optimization from Carnegie Mellon University and a BS in Mathematical Science from Tsinghua University. His research spans continuous optimization, machine learning, and fairness in AI, with a focus on developing efficient and provable algorithms for complex decision-making problems.
- Continuous Optimization
- First-Order Methods
- Distributed Optimization
- Error Bound Conditions
- Machine Learning and Predictive Analytics
- Fairness in AI
- Markov Decision Processes
His recent publications, appearing in venues like Mathematics of Operations Research, NeurIPS, and Management Science, emphasize theoretical advances in optimization under constraints, fairness-aware learning, and scalable methods for large-scale data. The work consistently bridges theory and application, particularly in healthcare and AI ethics.
Dr. Lin has been recognized with multiple awards, including:
- Best Paper Award - INFORMS Workshop on Data Science (2017)
- Runner-up, Best Paper Award - INFORMS Workshop on Data Science (2019)
- Early Career Faculty Research Award, Tippie College of Business (2018)
- MBA Business Analytics Professor of the Year (2018–2019)
He has secured significant research funding from the National Science Foundation and the University of Iowa, focusing on fairness-aware machine learning and federated learning in healthcare. His grants demonstrate strong collaboration with interdisciplinary teams and a commitment to solving real-world problems through algorithmic innovation. He has also contributed to the academic community as a reviewer for top journals such as Mathematical Programming, SIAM Journal on Optimization, and IEEE Transactions on Signal Processing.
Dr. Lin has been involved in research initiatives related to federated learning for medical imaging (ImagiQ) and fairness in AI systems, often working within collaborative frameworks involving data science and healthcare equity. His role as Faculty Director and research fellow underscores his leadership in shaping analytics education and research at the University of Iowa.
