I am a researcher with a strong theoretical basis in artificial intelligence. Specifically, reinforcement learning, combinatorial search, multiagent route assignment, game theory, flow and convex optimization, and multiagent modeling and simulation. I gained vast knowledge and experience in utilizing my theoretical foundations towards traffic management and traffic optimization application. Nonetheless, I view myself as part of the AI community where my work is highly cited. I strive to further the impact of my applicable expertise for solving real-life problems while simultaneously continuing to make theoretical advances that justify the proposed solutions.
Autonomous Traffic Management
Network Flow Optimization
Autonomous driving capabilities are becoming increasingly common on vehicles. Such capabilities present opportunities for developing safer, cleaner and more efficient road networks. Looking towards a future where traffic is composed of vehicles with different levels of autonomousy, we are developing efficient reservation based intersection management protocols. By relying on the fine and accurate control of connected and autonomous vehicles along with communication capabilities, intersection managements protocols coordinate such vehicles simultaneously across intersections.
Road pricing as a tool for congestion management has a long history in the transportation world, being first suggested nearly a century ago. Recent advances in connected and automated vehicle technology offer unprecedented flexibility and scope for implementing these tolls. In principle, tolls can be charged on many or all network links, and changed frequently in response to real-time observations of traffic conditions. Toll values and traffic conditions can then be communicated to vehicles which instantly change routes in response, with minimal to no intervention needed on behalf of drivers, who might only indicate some measure of the trip urgency or other proxy for value of time before departing. Even before autonomous driving technology reaches full penetration, communication capabilities and automated route selection software (as can be found on modern cell phones) may be sufficient to implement such a scheme.
In the multiagent pathfinding problem we are given a graph and a set of agents, each agent must be assigned a path leading from its initial location to its destination such that it will not collide with obstacles or other moving agents. MAPF can model many real-world problems such as video games, traffic control, robotics, aviation, automated warehouses and more. See (Yu and LaValle 2016) for a comprehensive survey.
Guni Sharon is an assistant professor in the department of computer science and engineering (CSE) at Texas A&M University. He received his doctoral, master’s and bachelor’s degrees in information systems engineering from Ben-Gurion University. Sharon’s current work focuses on developing and applying artificial intelligence techniques for optimizing transportation networks. Prior to joining Texas A&M, he was a postdoc in the computer science department at University of Texas at Austin. He is the recipient of the Outstanding Paper Award from the Association for the Advancement of Artificial Intelligence (AAAI). Prof. Sharon's complete curriculum vitae is avilable in its Full version, as a One page, or as a One page + publications
Texas A&M University, Computer Science and Engineering. Develop and provide academic courses at the graduate and undergraduate levels. Guide, lead and mentor students during classes and research projects. Create, innovate and implement career-enhancement programs and activities. Serve and support functional activities of departmental committees.
University of Texas at Austin, Computer Science. Member in TxDOT 6838 Project titled “Bringing smart transport to Texans: ensuring the benefits of a connected and autonomous transport system in Texas”. Part of a research collaboration between UT-Austin and Toyota, InfoTechnology Center Co., Ltd. Coordinating and leading a bi-weekly project meeting on traffic management including 2 faculty members, 3 post-docs and 2 Ph.D. students.
Ben-Gurion University, Information Systems Engineering; Dean award for outstanding Ph.D student. Thesis title “Novel Search Techniques for Path Finding in Complex Environment”. Awarded the "Darom" Graduate Research Scholarship.
Ben-Gurion University. Led discussions in a class of up to 30 students. Prepared course material including laboratory experiments, lectures, exams, homework, and practice problems. TA for the following courses: Introduction to Operation Systems, Operations Research, Introduction to A.I., Automata and computability Theory.
Ben-Gurion University, Information Systems Engineering; graduation with Honors. Thesis title “Optimal Multiagent Pathfinding”. Awarded the Harbor Foundation Graduate Research Scholarship.
Ben-Gurion University, Information Systems Engineering; graduation with Honors. Winner of the South African Zionist Federation Scholarship.
Israeli Defense Force; Head of the operations department of an artillery brigade. supervised two soldiers.
Applying: Apply via the Texas A&M graduate admission system. In your statement of purpose refer to my lab and, if applicable, a specific project that you would like to work on. You can increase your chances of admission by reading one of my papers and suggesting your own ideas as to how to extend the underlying research (be creative). A good applicant is one that provides evidence of the following three traits:
* Don’t worry about sharing your thoughts. Assuming they are not trivial or previously published, I will not use, develop, or present your ideas without your consent.
Position description: As a PhD student you are expected to lead a research project. Leading a project requires you to develop and manage the affiliated codebase, guide interns and undergrads, perform ground-breaking research, and, ultimately, publish research papers. We will have weekly meetings where you will report progress during the past week, issues that you encountered, possible ways to address these issues, and objectives that you hope to accomplish in the following week. PhD students are expected to apply for fellowships that are relevant to their research.
Applying: MSc applications follow a similar process and requirements as a PhD application (see above). Currently enrolled MSc students are welcomed to join the lab meetings and participate in a research project. Given sufficient contribution, I will happily support a transfer application from a non-thesis track to a thesis track. Exceptional MSc students will be offered admission to the PhD track.
Position description: As a MSc student you are expected to support a research project (usually led by a PhD student). You will be in charge of a well-defined sub-project. You are not expected to come up with your own ideas but encouraged to do so.
Applying: Graduate students which are actively contributing to the lab may apply for a GAR. Such students are expected to work on a project that is likely to result in a publication. Please speak with me directly if you would like to apply. You are expected to apply for external funding sources prior to applying for lab funds.
Position description: Funded graduate student are expected to: (a) devote at least 20 hours/week to a research project and (b) produce substantial research contribution in the form of publications and undergrad mentoring.
Applying: Send me an email specifying: your background and credentials, internship dates, one or more research projects that you would like to get involved with, one letter of support (preferably from a faculty member), funding source. Please note that my lab is not be able provide financial support for internships. Consequently, an application should be made only after securing relevant funding. Possible funding resources include: Fulbright, TAMU research intern program
Position description: Interns are expected to: (a) devote at least 40 hours/week to a research project and (b) produce substantial research contribution in the form of publications, grants, codebase, and/or undergrad mentoring.
Applying: A visiting scholar/postdoc position is available for researchers with a proven research record. A proven record refers to publications in top-tier venues, being a former collaborator, or a students of a former collaborator. Applicants should send me an email stating their background and credentials, one or more research projects that they would like to lead, one letter of support (preferably from a former collaborator)
Position description: Visiting scholars are expected to: (a) manage a research project and (b) produce substantial research contribution in the form of publications, grants, codebase, and graduate student mentoring.
Department of Computer Science and Engineering, H. R. Bright Building, 3112 TAMU, 710 Ross St, College Station, TX 77843
guni (at) tamu (dot) edu
+(1) 979 845 5498
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