Shiqi Zhang

      I am an assistant professor in computer science, at SUNY Binghamton.

      My research is on autonomous intelligent robotics. I am particularly interested in developing algorithms that integrate reasoning (with declarative knowledge), planning (to achieve long-term goals), and learning (from past experiences) formalisms for mobile service robots that work in human-inhabited, collaborative, everyday environments.

      I was an assistant professor in Cleveland State University. I was a Postdoc at UT Austin, where I worked on the Building Wide Intelligence project with Professor Peter Stone. Before that, I received my Ph.D. (2013) from Texas Tech University with Professor Mohan Sridharan (now at University of Birmingham, UK). Before that, I received my M.S. and B.S. from Harbin Institute of Technology . More info about me: CV (pdf, updated in Nov 2018), a short bio (txt), and my name in Chinese (png).

      Research group website is under construction:

Recent updates


    • Spring 2019 (CS 465/565) Introduction to Artificial Intelligence [web]
    • Earlier courses
    • Fall 2018 (CS 480/580) Intelligent Mobile Robotics [web]
    • Spring 2018: CIS 693, EEC 693, EEC 793 Autonomous Intelligent Robotics [web; project reports]
    • Fall 2017: CIS 490/590 Foundations of Computing
    • Spring 2017: CIS 493, EEC 492, EEC 592 Autonomous Intelligent Robotics [web; project reports]
    • Fall 2016: CIS 490/590 Foundations of Computing


Multi-Robot Planning with Conflicts and Synergies

Task planning for a team of robots requires modeling limited domain resources (e.g., corridors that allow at most one robot at a time) and the possibility of action synergy (e.g., multiple robots going through a door after a single door-opening action). We introduce the iterative inter-dependent planning (IIDP) algorithm for planning for a team of robots, while avoiding searching in joint state or action spaces. [Paper, 2017]

Robot Scavenger Hunt Game

The main goal of the Robot Scavenger Hunt is to provide a standardized framework that includes a set of standardized tasks for evaluating the AI and robotic capabilities of medium-sized intelligent mobile robots. [Paper, 2016]

Mixed Logical Inference and Probabilistic Planning

Deployment of robots in practical domains poses key knowledge representation and reasoning challenges. This paper presents an architecture that exploits the complementary strengths of declarative programming and probabilistic graphical models as a step toward addressing these challenges. [Paper, 2015]

Robot Language Learning through Dialog

Intelligent robots frequently need to understand requests from naive users through natural language. We introduce a dialog agent for mobile robots that understands human instructions through semantic parsing, actively resolves ambiguities using a dialog manager, and incrementally learns from human-robot conversations by inducing training data from user paraphrases. [Paper, 2015]


    Professional Services

      Available in CV.

    Robot Outreach

      • Students from Horizon Science Academy Cleveland Middle School (Cleveland OH) visited our lab in Jan 23, 2018.
        robot outreach robot outreach
        Left: James Doherty, an undergraduate research assistant, was explaining how our Segway-based mobile robot avoids people in navigation. Right: a visitor was using a ball to guide a drone to move in AIR lab.
      • More details to be added.


      Shiqi Zhang
      Assistant Professor
      SUNY Binghamton

      Office: Q07, Engineering Building
      Phone: 607-777-4355

      Research Lab: M11, Engineering Building


      Mailing address:

      Department of Computer Science
      Thomas J. Watson School of Engineering and Applied Science
      State University of New York at Binghamton
      4400 Vestal Parkway East
      Binghamton, NY 13902-6000