 |
Distinguished University Professor Dinesh Manocha received a 2022 Verisk AI Faculty Research Award. The award funding will support the generation and use of synthetic datasets to improve the accuracy of machine learning methods. These synthetic datasets can be combined with real-world datasets for training the neural networks.
Manocha is the Paul Chrisman Iribe Professor of Computer Science and Professor of Electrical and Computer Engineering (ECE) and is affiliated with both the Institute for Systems Research and the Maryland Robotics Center and co-leads the University of Maryland’s (GAMMA) research group.
With the GAMMA research group—which includes more than 30 Ph.D. students from across ECE and Computer Science—Manocha is tackling a number of artificial intelligence (AI) challenges related to robotics, autonomous driving, affective computing, activity recognition and document processing.
In addition to the Verisk Award, Manocha’s work is funded through support from various government grants, including the National Science Foundation, Army Research Office (ARO), the Defense Advanced Research Projects Agency (DARPA), Semiconductor Research Corporation (SRC) and the Army Research Laboratory (ARL).
“I have also been fortunate to receive strong support from industry for our research,” said Dinesh. “That includes Intel, Google, Facebook (now Meta), Adobe, ShareChat and now Verisk.”
The Verisk Faculty Research Awards Program supports academic research in artificial intelligence, machine learning and allied areas of computer science, mathematics, and the engineering sciences. The awards are aimed to promote research excellence at top universities and institutions of academic and research excellence, providing support for research, public service, instruction, fellowship, traineeships, or other research-related activities and foster interactions between Verisk and the academic/research community.
Related Articles:
'OysterNet' + underwater robots will aid in accurate oyster count
ISR faculty leading, playing key roles in ARL cooperative agreement
A learning algorithm for training robots' deep neural networks to grasp novel objects
Advancing Healthcare through Robotics and Machine Learning
Helping robots remember
Machine Learning's Translational Medicine
Realistic simulator improves safety of self-driving vehicles before road testing
New affiliate faculty Mark Fuge is expert in machine learning and artificial intelligence
Tuna-Inspired Mechanical Fin Could Boost Underwater Drone Power
Developing Efficient Systems for Deep Sea Exploration
February 9, 2022
|
