جستجوی استاد راهنمای دانشگاهی

Robert Harperمشاهده پروفایل

استاد

• Programming Languages
• Type Theory
• Cost Semantics
• +۳ مورد دیگر

Robert Harper is a Professor in the Computer Science Department at Carnegie Mellon University, Pittsburgh, PA. His research focuses on the intersection of type theory and programming language design, with emphasis on formal verification, cost semantics, and concurrency models. University: Carnegie Mellon University Department: Computer Science Academic Rank: Professor Email: rwh@cs.cmu.edu Harper's research program integrates cost analysis with behavioral properties in type theory, including Synthetic Tait Computability for logical frameworks and Amortized Analysis via Coalgebraic Methods . He explores foundational issues in Higher-Order Recursion and resource-sensitive programming through Decalf , a directed effectful cost-aware framework. His work combines theoretical rigor with practical implementation in systems like Twelf and Red* . Recent publications demonstrate his contributions to Computational Adequacy , Session-Typed Concurrency , and Compiler Verification . Collaborations with institutions like the Max Planck Institute for Software Systems and researchers such as Stephanie Balzer and Jan Hoffmann extend his impact to concurrent systems and cost-sensitive programming. Scientific Distinctions ACM SIGPLAN Programming Languages Achievement Award (2021) ACM Fellow (2005) Allen Newell Award for Research Excellence (2001) He advises students on projects like Cost Verification in Calf and Parallel Scan Verification , while teaching advanced courses including 15-413: Advanced Topics in Principles of Programming Languages (Spring 2025) and 15-312: Principles of Programming Languages (Fall 2025). Research funded by AFOSR grants including MURI A210038S002.

Dave Andersenمشاهده پروفایل

دانشیار

• Computer Systems
• Distributed Systems
• Networked Environments
• +۱۲ مورد دیگر

Dave Andersen is an Associate Professor at the School of Computer Science, Carnegie Mellon University , with research focusing on memory and power-efficient computing, robust distributed systems, and networked environments. He also serves as CTO of Enriched Ag . Education: Ph.D. and M.S. in Computer Science from MIT (2001, 2004), B.S. in Computer Science and Biology from the University of Utah (1995). Research Trends: Explores systems design in the post-Moore's Law era, emphasizing concurrency, low-latency geo-replicated storage, and RDMA in datacenters. Key projects include MemC3, Eiger, Cuckoo Filter, and FAWN. Teaching: Courses in Advanced OS, Distributed Systems, Low-Power Computing, and Network Security. Professional Service: Program committee roles at SOSP, NSDI, SIGCOMM, and DARPA ISAT advisory group. Personal: Active in running, climbing, and outdoor activities with detailed route guides for Pittsburgh and Boston.

Weina Wangمشاهده پروفایل

استادیار

• Applied Probability
• Stochastic Systems
• Reinforcement Learning
• +۷ مورد دیگر

Weina Wang is an Assistant Professor in the Computer Science Department at Carnegie Mellon University, joining in Fall 2018. Her research lies at the intersection of applied probability , stochastic systems , and reinforcement learning , focusing on decision-making in large-scale systems with applications to computing resource orchestration, data privacy, and graph statistics. She has received prestigious awards including the NSF CAREER Award (2022) , ACM MobiHoc Best Paper (2022) , and ACM SIGMETRICS Rising Star Research Award (2023) . PhD in Electrical Engineering, Arizona State University (2016) Bachelor’s in Electronic Engineering, Tsinghua University (2009) Her recent publications span restless bandits , queueing theory , and attributed graph alignment , reflecting her dual focus on fundamental limits and algorithmic solutions. Notable collaborations include work on privacy-preserving data routing , phase-aware scheduling , and erasure-coded servers for heterogeneous traffic. She has advised PhD students Jalani Williams , Tuhinangshu Choudhury , and Yige Hong . Her research has been recognized with best paper awards and grants like the NSF CAREER . She also contributes to professional societies, recently joining the INFORMS Applied Probability Society council . Her teaching includes courses like Probability and Computing and Fundamentals of MDPs and Reinforcement Learning .