D. Paul Benjamin
Director of Ph.D. program in Computer Science
Seidenberg School of CSIS
Computer Science NY
- @New York City
163 William Street
New York City
Dr. Benjamin earned his doctorate in computer science from NYU. He worked for six years in industry before entering academia. Currently, he is professor of computer science and founder and director of the Robotics Lab at Pace University in New York City.
PhD, New York University, 1985
MS, New York University, 1982
BFA, Carnegie Mellon University, 1976
MS, Carnegie Mellon University, 1975
BS, Carnegie Mellon University, 1973
Awards and Honors
- U.S. Patent 60/654,415 - System for Intrusion Detection and Vulnerability Assessment in a Computer Network using Simulation and Machine Learning
Pace University - CS NY, January 1, 2006 - Spring 2006 Course Release to write grant proposals
Reengineering LLC, February 1, 2004 - U.S. Patent 6,691,132 - Semantic Encoding and Compression of Database Tables
New York University, September 1, 1983 - Graduate Research Assistant
Liang, Y., Shan, J., Benjamin, D. & Almajalid, R. (2019, May 19). Convolutional Neural Networks for Breast Ultrasound Image Segmentation.
Benjamin, D. P., Yue, H. & Lyons, D. Classification and Prediction of Human Behaviors by a Mobile Robot.
, D. P., Lyons, D. & Yue, H. Progress in Building a Cognitive Vision System.
Benjamin, D. (2019, December 6). MID2019. Spatial Understanding as a Common Basis for Human-Robot Collaboration. Pace University, 163 William Street, New York.
Benjamin, D. (2019, February 15). Rise of the Machines: Artificial Intelligence, Robotics, and the Reprogramming of Law. Ethics and the Design and Engineering of Autonomous Robots. Fordham Law School, Fordham University.
Benjamin, D. P. (2018, October 17). Predictive Vision for Human-Robot Collaboration. Fordham University, Bronx, NY.
Benjamin, D. P. (2018, July). Fourth International Conference on Human Factors and Unmanned Systems. Using a Virtual World to Implement a Mental Model. Orlando, Florida.
Benjamin, D. P. & , . (2017, July). Third International Conference on Human Factors and Unmanned Systems. Spatial Understanding as a Common Cognitive Basis for Human-Robot Collaboration. Los Angeles, CA.
Benjamin, D. P. & , . (2016, July). Second International Conference on Human Factors and Unmanned Systems. Classification and Prediction of Human Behaviors By a Mobile Robot. Orlando, FL.
Benjamin, D., Lyons, D. & Yue, H. (2016, April). SPIE Conference on Multisensor, Multisource Information Fusion: Architectures, Algorithms and Applications. Progress in Building a Cognitive Vision System for a Mobile Robot. Baltimore, MD.
Robotics; Artificial Intelligence (Application of Artificial Intelligence to Networks); Cybersecurity; Data Mining; Application of semigroup theory to theory formulation.
Grants, Sponsored Research and Contracts
A Humanoid Robot for Investigating Spatial Understanding in Human-Robot Collaboration
Benjamin, D. September 2019 - August 2020. Office of Naval Research , Federal , $187,444.00. Funded. The Pace University Robotics Lab is developing a robotic architecture based on cognitive principles for autonomous robots that can safely interact and collaborate with people on a wide range of physical tasks. Central to our architecture is its mental model, which is a 3D virtual world that the architecture synchronizes with the environment in real time. This mental model represents changes in causation in the world and generates expectations about physical change in the world. A main scientific focus of this project is the development of the 3D virtual world and its use in planning, learning and communication in Human-Robot interaction.
This proposal is for funding to support the purchase of a humanoid robot platform. Currently, our robots are Pioneer 2 and 3 robots, which are sufficient for investigating basic issues in navigation, path planning, and perception. However, we are investigating how people and robots can collaborate on tasks that involve interacting with and manipulating the environment. This includes assembly tasks, as well as tasks involving robots and people moving together. Small Pioneer robots are inadequate for performing such tasks, due to their limited sensory capabilities, small size, and almost nonexistent ability to manipulate their environment.
The platform we have selected is the Pioneer Manipulator Research Platform. It's size and humanoid configuration make possible much more natural interaction with people, and its two Kinova Jaco2 manipulators enable it to perform physical tasks involving gripping and carrying. The sensory capabilities of the platform are superior to that of the basic Pioneer robots, and include laser range finding, gyroscope, sonar, and range cameras. In addition, the platform has speakers and a speech synthesizer.
The budget for this proposal also includes supporting computers, including a powerful workstation to serve as the base for the project and a laptop. This workstation has 56 cores and 256GB memory, plus a high-end graphics card with 1536 CUDAs. The laptop will add computing power to the robot's onboard computers.
The software used in our architecture includes a lot of open source code, including OpenCV, PhysX and Soar. All of the software produced by our project is open source; however, much of our analytical code is Mathematica and Matlab code, and the proposal budget includes upgrades to the licenses, especially obtaining a gridMathematica license to fully utilize the cores in the workstation.
The project will produce many large vision datasets, and will utilize a large library of recognized objects and their 3D mesh models. This requires significant storage space, which will be provided by a 40TB external drive.
Patent: System for Intrusion Detection and Vulnerability Assessment in a Computer Network using Simulation and Machine Learning
Patent: Semantic Encoding and Compression of Database Tables
American Association for Artificial Intelligence
Association for Computing Machinery
Computer Science Ph.D. Supervisory Committee [Committee Chair]
Desc: Scheduling courses, meeting with prospective students, admissions decisions, designing policies and procedures, reporting to Dean, enforcing policies
Committee's Key Accomplishments: The committee has grown the Ph.D. program and strengthened its quality.
Faculty Search Committee [Committee Member]
Desc: help write position advertisements, review resumes, interview candidates
Committee's Key Accomplishments: advertisements done and out, resumes coming in
Learning Sciences Program Development Committee
Desc: Contribute to developing the curriculum for a new interdisciplinary program in Learning Sciences.
Committee's Key Accomplishments: Developed a good curriculum, but the program is on hold due to the university's financial state.