Maryam Fatemi
Papers
1
Total Citations
13
H-Index
1
About
Maryam Fatemi is a leading researcher at the intersection of computer vision, graphics, and autonomous systems, with a primary focus on neural rendering for self-driving technologies. Her most impactful work, "SplatAD: Real-Time Lidar and Camera Rendering with 3D Gaussian Splatting for Autonomous Driving" (2025), has already garnered 13 citations, signaling its rapid influence in the field. Fatemi’s major contribution lies in pioneering real-time, photorealistic simulation environments that integrate both lidar and camera data using 3D Gaussian splatting—a breakthrough that enables cost-effective, scalable safety testing for autonomous robots and vehicles. By bridging the gap between synthetic and real-world sensor data, her research addresses a critical bottleneck in autonomous driving validation, allowing engineers to simulate diverse, edge-case driving scenarios without physical risk. This work stands out for its practical impact, offering a high-fidelity, computationally efficient alternative to traditional rendering pipelines. Fatemi’s achievements position her at the forefront of neural rendering for robotics, where her innovations are helping to accelerate the safe deployment of self-driving systems. Her research continues to inspire new directions in real-time simulation, making her a rising star in autonomous vehicle technology.
Research Focus
Key Achievements
Top Papers
- 1