Papers

4

Total Citations

59

H-Index

3

About

Yaser P. Fallah is a leading researcher at the intersection of autonomous vehicles, robotics, and intelligent transportation systems. His work primarily focuses on environment representation for automated driving, with a landmark contribution being his 2022 study on "High-Definition Map Representation Techniques for Automated Vehicles" (32 citations), which systematically explores how topological and geometrical abstractions can summarize spatial information to enhance vehicle perception and reliability. Fallah also made significant early contributions to cooperative unmanned aerial vehicle (UAV) systems, demonstrated in his 2011 work on autonomous UAV teams for sensing and tracking (16 citations), where he developed a component-based software and hardware platform enabling single-user control of UAV fleets for surveillance missions. More recently, he has advanced the field of generalizable driving policies, investigating how restricted latent representations can enable autonomous agents to navigate diverse urban and highway scenarios. His research bridges theoretical map representation with practical autonomous systems, addressing fundamental challenges in how vehicles understand and interact with complex environments. With over 60 total citations across his most influential works, Fallah continues to shape the future of automated mobility.

Research Focus

Key Achievements

3
H-Index
4
Papers
59
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
High-Definition Map Representation Techniques for Automated Vehicles
32 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: University of Central Florida, University of California, Berkeley

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago