معرفی
Matthew Eichhorn is a Lecturer in the Department of Computer Science at Cornell University, specializing in teaching large undergraduate courses on discrete mathematics and programming. He holds a PhD in Applied Mathematics from Cornell University and a BS in Computer Science and Mathematics from the University at Buffalo.
His research focuses on developing algorithms for societal decision-making, including online team formation, fair resource allocation, and causal inference in networks. He emphasizes leveraging combinatorial structures to design efficient algorithms and estimators. His work spans theoretical foundations and practical applications in public health, education, and social networks.
Recent publications explore causal inference under interference, allocation algorithms with complex constraints, and efficient representations for linear transforms. He actively contributes to academic initiatives like the Active Learning Initiative and Engineering Academic Excellence Workshops.
Eichhorn has taught multiple courses including CS 2110 (Object-Oriented Programming), CS 2800 (Discrete Structures), and engineering operations research. He has also served as a teaching assistant across computer science, mathematics, and engineering disciplines.
