Suvash Sharma
Papers
1
Total Citations
12
H-Index
1
About
Suvash Sharma is a leading researcher in autonomous systems and machine learning, with a focus on bridging the gap between simulation and real-world perception. His most-cited work, "Training of Neural Networks with Automated Labeling of Simulated Sensor Data" (2019), addresses a critical bottleneck in autonomous vehicle development: the costly and time-intensive process of manually labeling training data for convolutional neural networks. By introducing a method for automated labeling of simulated sensor data, Sharma enables the generation of large, high-quality training datasets without human intervention, significantly accelerating the development cycle for perception algorithms. This contribution has garnered 12 citations and is foundational for researchers seeking scalable, cost-effective approaches to neural network training. His work directly impacts the efficiency of ground-vehicle autonomy, reducing reliance on expensive real-world data collection. Sharma’s innovative synthesis of simulation and deep learning continues to influence the field, offering a practical pathway toward robust, data-driven autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Training of Neural Networks with Automated Labeling of Simulated Sensor Data12 citations · 2019