Tichakorn (Nok) Wongpiromsarn

Tichakorn (Nok) Wongpiromsarn

Assistant Professor

Department of Computer Science

Iowa State University

I am an Assistant Professor in the Department of Computer Science at Iowa State University. I received a Ph.D. in Mechanical Engineering from the California Institute of Technology in 2010 under the supervision of Prof. Richard Murray.

My research interests lie in the broad area of computer science, control, and optimization, with a particular focus on formal methods, motion planning, situational reasoning, hybrid systems, and distributed control systems. Most of my work involves applying mathematical and computational rigor to solve concrete, real-world problems, especially in autonomy, robotics, and transportation.

A significant portion of my career has been devoted to the development of autonomous vehicles, both in academia and industry settings. In particular, I was a principal research scientist and led the planning team at nuTonomy (now Hyundai-Aptiv Autonomous Driving Joint Venture). As one of the earliest employees, I was heavily involved in the whole software development and release process, from design (interfaces and modules) to implementation (C++ and python), testing, evaluation, and deployment. My work focused on planning, decision making, control, behavior specification, and validation of autonomous vehicles. I also led the Systems Team for Team Caltech in the 2007 DARPA Urban Challenge during my Ph.D.


  • Specification, design, and analysis of cyber-physical systems
  • Situational reasoning and decision making in complex, dynamic and uncertain environments
  • Modeling, analysis, and optimization of large-scale multi-agent systems


  • Ph.D. in Mechanical Engineering, 2010

    California Institute of Technology

  • Master of Science in Mechanical Engineering, 2006

    California Institute of Technology

  • Bachelor of Science in Mechanical Engineering (Summa Cum Laude), 2005

    Cornell University



Assistant Professor

Department of Computer Science, Iowa State University

Aug 2020 – Present Ames, IA

Research Fellow

Autonomous Systems Group, University of Texas at Austin

Jan 2020 – Aug 2020 Austin, TX

Affiliate Assistant Professor

Department of Computer Science, Iowa State University

Nov 2019 – Aug 2020 Ames, IA

Principal Research Scientist

Autonomous Mobility, Aptiv

Oct 2018 – Dec 2019 Singapore

Principal Research Scientist, Planning Team Lead


Oct 2015 – Oct 2018 Singapore

Project Manager

Thailand Center of Excellence for Life Sciences

Feb 2014 – Sep 2015 Bangkok, Thailand

Postdoctoral Associate

Future Urban Mobility, Singapore-MIT Alliance for Research and Technology

Oct 2010 – Dec 2012 Singapore

Recent News

I’m looking for Ph.D. students with strong analytical skills and eager to initiate and explore new ideas that will have real-world impact. Please check the current projects below. If you’re interested, the first step is to apply to the Department of Computer Science. For ISU students, please send me a short email and include the project(s) you are interested in.

May 27: I’m giving a talk on Establishing Correctness of Learning-Enabled Autonomous Systems at Workshop on Safe and Reliable Robot Autonomy under Uncertainty, ICRA 2022.

May 11: Hamad Ullah successfully defended his Master’s thesis!.

May 5: Opening ceremony of the Autonomous Systems Laboratory at 1110 Communications Building.

Oct 30: I’m giving talk on Formal Methods for Control Synthesis of Autonomous Systems at the GALCIT Colloquium at Caltech.

Oct 23: I’m giving talk on Formal Methods for Control Synthesis of Autonomous Systems at the Robotics Engineering Colloquium Series at WPI.



Most of my work draws inspiration from practical applications, especially in autonomy, robotics, and transportation. As these systems become more complex, they cannot be built based on human intuition alone anymore. My research focuses on providing theoretical and computational foundations to enable systematic modeling, design, optimization, and analysis for such complex systems.

During my Ph.D., I led the Systems team and implemented the finite state machine logic that accounted for traffic rules and governed the overall functioning of the planner of Alice, Team Caltech’s entry in the 2007 DARPA Urban Challenge. The difficulties in the design and analysis of this finite state machine motivated my research on applying formal methods to control systems as part of the MURI project on Specification, Design and Verification of Distributed Embedded Systems. During my postdoc at SMART, I worked on building low-cost autonomous vehicles for mobility-on-demand systems, developing distributed algorithms for controlling traffic lights, and designing transportation pricing strategies to reduce traffic congestion.

I also spent 4+ years at a self-driving car company, nuTonomy, where I initially led the planning team and was a primary developer of the planning and decision-making module. Unlike in Alice, nuTonomy’s planning system does not rely on complex finite state machines. Instead, we applied formal methods to automatically build the decision-making logic such that it is provably correct by construction. While I was excited to see the core part of my research in real-world practices, I realized that there is a fundamental problem that has been mostly overlooked by the formal methods community and lies in the lack of precise specifications of these autonomous systems, i.e., in defining what constitutes their correct behaviors, taking into account various factors, including safety, regulatory requirements, comfort, culture, etc, that may be conflicting. My recent work focuses on addressing this gap and developing theory, methods, and tools to derive, analyze, and refine specifications for autonomous systems.


Sharing the World with Autonomous Systems: What Goes Wrong and How to Fix It (NSF)

Develop efficient algorithms for autonomous systems to characterize and actively identify the inconsistencies (e.g., in perception and decision-making) among the interacting agents and to influence the behaviors of the other agents to improve the safety of the overall system.

CAREER: Establishing Correctness of Learning-Enabled Autonomous Systems with Conflicting Requirements (NSF)

Develop specification formalisms, control synthesis algorithms, and quantitative verification frameworks for autonomous systems that include learning-based components, operate in uncertain environments, and are subject to conflicting requirements with partially established priorities.

Developing a Low Visibility Navigation System (Iowa DOT)

Develop and retrofit an existing snowplow with a suite of sensors and mapping systems along with a driver assistance interface that will guide the operator when visibility

Resource-Aware Hierarchical Runtime Verification for Mixed-Abstraction-Level Systems of Systems (NSF)

Develop runtime verification techniques that incorporate mixed-abstraction-level granularity in specifications and enable on-deadline mitigation triggering

Planning with Conflicting Specifications

Develop planning and decision-making algorithms with multiple, potentially conflicting objectives.

Formal Specifications of Autonomous Systems

Derive, analyze, and refine specifications from regulatory requirements and demonstrations.

Autonomy in Mobility-on-Demand Systems

Assess and demonstrate the role of autonomy in mobility-on-demand systems through modeling, algorithm development and experimental demonstration.

Real-time Control and Learning for Sustainable Transportation

Mechanism design for dynamic pricing and real-time control of traffic signals based on control, communication, optimization and game theory

Temporal Logic Planning (TuLiP) Toolbox

A Python-based software toolbox for the synthesis of embedded control software that is provably correct with respect to an expressive subset of linear temporal logic (LTL) specifications.

Consensus Approaches to the Assignment Problem

Design a consensus protocol to solve the assignment problem in a distributed manner.

Formal Methods for Design and Verification of Embedded Control Systems

Develop mathematical and computational frameworks to facilitate the design and analysis of embedded control systems such as autonomous vehicles.

DARPA Urban Challenge 2007

A race of autonomous ground vehicles through an urban environment.

Abstraction-Based Multi-Vehicle Command and Control

A path planning system for multi-vehicle domains.

Recent Publications

TRELPy: Toolbox for Task-Relevant Evaluation of Perception
Multimodal Model Predictive Runtime Verification for Safety of Autonomous Cyber-Physical Systems
GENESIS-RL: GEnerating Natural Edge-cases with Systematic Integration of Safety considerations and Reinforcement Learning
Locally Homotopic Paths: Ensuring Consistent Paths in Hierarchical Path Planning

Recent & Upcoming Talks

Establishing Correctness of Learning-Enabled Autonomous Systems
Formal Methods for Control Synthesis of Autonomous Systems
Formal Methods for Control Synthesis of Autonomous Systems
RuleBooks for Autonomous Vehicles
Behavior Specifications of Autonomous Vehicles



  • Com S 476/576: Motion Strategy Algorithms and Applications, Spring 2021, Spring 2022, Iowa State University
  • DS 301: Applied Data Modeling and Predictive Analysis, Fall 2020, Fall 2022, Iowa State University
  • EECI 2020: Specification, Design, and Verification for Self-Driving Cars, 9–13 March 2020, Istanbul, Turkey
  • EECI 2012: Specification, Design, and Verification of Networked Control Systems, 14–18 May 2012, L’Aquila, Italy
  • EECI 2011: Specification, Design, and Verification of Distributed Embedded Systems, 21–25 March 2011, Supelec, France
  • FRA 638: Mobile robots, Fall 2015, Institute of Field Robotics (FIBO), King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

Guest Lectures

  • F1TENTH 2020: Minimum Violation Planning, 22 April 2020, University of Pennsylvania
  • F1TENTH 2020: Behavior Specification using Rulebooks, 27 April 2020, University of Pennsylvania

Recent Posts

The Journey of Autonomous Vehicles

A summary of technological progress and challenges over the past 10+ years.


  • nok@iastate.edu
  • Department of Computer Science, 226 Atanasoff Hall, 2434 Osborn Dr, Ames, IA 50011