Jie He

Jie He is a PreDoc Researcher at the Department of Cyber-Physical Systems, Technische Universität Wien. His research spans computational social choice, algorithmic game theory, and formal methods in robotics and IoT systems. He works on multidisciplinary problems involving complexity analysis, fair division, and preference modeling.

• Current projects: EdgeAI (2022–2025), TAIGER (2023–2027), ADEX (2020–2024)
• Key collaborations: Research with R. Grosu, E. Bartocci, D. Nickovic

Research interests focus on computational aspects of collective decision-making, including fair division, matching problems, and preference modeling. He works on both theoretical foundations (e.g., parameterized complexity) and practical applications (e.g., robotic-IoT systems).

His publication history reveals deep expertise in computational complexity of social choice problems, with recent work on 3D stable roommates, fair division in graph-structured settings, and preference modeling through Euclidean and Manhattan geometries.

As an advisor, he supervised diploma theses on:

• Optimization strategies for 5G transceivers
• Dynamic object detection in multi-agent systems

His work appears in top conferences like ACM/IEEE DAC, ICSE, and various computational social choice venues.