Mahsa Ghasemi
Computer Science · Purdue University West Lafayette
Publications
58
Citations
81
Est. group size
~1
Recurring co-author estimate
Active years
16
Publishing since 2011
Mahsa Ghasemi's research focuses on decision-making and safety for autonomous systems, particularly using reinforcement learning, formal verification methods, and multi-agent coordination for applications like unmanned aerial vehicles and human-robot collaboration. Recent work also explores fairness in online learning (bandit algorithms), causal inference methods, and security challenges for drone traffic management and advanced air mobility systems. The work blends theoretical methods (formal methods, reinforcement learning theory, causal discovery) with applied domains such as UAV safety and robotics.
Publication output has grown substantially over the last decade, with a notable surge in output in the most recent year after a period of moderate, fluctuating activity.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Separation Assurance between Heterogeneous Fleets of Small Unmanned Aerial Systems via Multi-Agent Reinforcement Learning
arXiv (Cornell University) · 2026
- Multi-User Dueling Bandits: A Fair Approach using Nash Social Welfare
arXiv (Cornell University) · 2026
- Separation Assurance between Heterogeneous Fleets of Small Unmanned Aerial Systems via Multi-Agent Reinforcement Learning
arXiv (Cornell University) · 2026
- Joint MDPs and Reinforcement Learning in Coupled-Dynamics Environments
arXiv (Cornell University) · 2026
- A Survey of Security Challenges and Solutions for UAS Traffic Management (UTM) and Small Unmanned Aerial Systems (sUAS)
2026
- A Survey of Security Challenges and Solutions for UAS Traffic Management (UTM) and small Unmanned Aerial Systems (sUAS)
arXiv (Cornell University) · 2026
- A Survey of Security Challenges and Solutions for Advanced Air Mobility and eVTOL Aircraft
arXiv (Cornell University) · 2026
- A Survey of Security Challenges and Solutions for Advanced Air Mobility and eVTOL Aircraft
arXiv (Cornell University) · 2026
- Joint MDPs and Reinforcement Learning in Coupled-Dynamics Environments
Open MIND · 2026
- Multi-User Dueling Bandits: A Fair Approach using Nash Social Welfare
arXiv (Cornell University) · 2026
- FRIH: A face recognition framework using image hashing
Multimedia Tools and Applications · 2024
- Adaptive Online Experimental Design for Causal Discovery
arXiv (Cornell University) · 2024
- Partial Structure Discovery is Sufficient for No-regret Learning in Causal Bandits
2024
- Identification of Average Causal Effects in Confounded Additive Noise Models
arXiv (Cornell University) · 2024
- Partial Structure Discovery is Sufficient for No-regret Learning in Causal Bandits
arXiv (Cornell University) · 2024
- arXiv (Cornell University)×27
- IEEE Transactions on Automatic Control×2
- Multimedia Tools and Applications×1
- Foundations and Trends® in Systems and Control×1
- World Academy of Science, Engineering and Technology, International Journal of Chemical and Molecular Engineering×1
- Qianchuan Ye
Computer Science · Purdue University West Lafayette
- Prasita Mukherjee
Computer Science · Purdue University West Lafayette
- Jingbo Wang
Computer Science · Purdue University West Lafayette
- Joe Eappen
Computer Science · Purdue University West Lafayette
- Yuantian Ding
Computer Science · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
Claim or correct this profile