Ashfaq Farooqui

Ashfaq Farooqui


Research Institute of Sweden


Ashfaq Farooqui is a researcher within the Dependable transport systems group at the Research Institite of Sweden, Sweden. He obtained the Ph.d in Electrical Engineering and the MSc degree in Systems, Control, and Mechatronics from Chalmers University of Technology, Sweden in 2021 and 2015, respectively. His Bachelor degree in Electronics and Communication Engineering degree was obtained from BMS Institute of Technology, India in 2012. Ashfaq Farooqui was born in Bangalore, India.

My research focuses on model-driven development, supervisory control, and formal analysis. I develop tools and techniques to support verifiably safe control of automated systems.


  • Model Inference
  • Supervisory Control
  • Formal Verification


  • PhD in Electrical Engineering, 2021

    Chalmers University of Technology

  • MSc in Systems, Control, and Mechatronics, 2015

    Chalmers University of Technology

  • BSc in Electronics and Communication, 2012

    BMS Institute of Technology


2022-10 Our contribution On Active Learning for Supervisor Synthesis is accepted and will be published in IEEE Transactions of Automation Science and Engineering (TASE) and can be accessed here.

2022-02 Our contribution Automatically Learning Formal Models from Autonomous Driving Software is now published in the Special Issue “Feasible, Robust and Reliable Automation and Control for Autonomous Systems” by MDPI-Electronics and is avaliable here.

2021-10 I start as a researcher at RISE working within the Dependable Transport Systems group.

2021-06 I will defend my thesis titled On supervisor learning via active automata learning on the 11th of June, you are welcome to join

2021-06 Our contribution MIDES: A Tool for Supervisory Synthesis via Model Inference is accepted and will be presented at CASE 2021, Lyon, France.

2021-02 MIDES A tool for active learning of supervisors is now open-source and available on Girhub.

2020-08 Our contribution Automatically Learning Formal Models: An Industrial Case from Autonomous Driving Development is accepted at MASE 2020, Montreal, Canada Online.

2020-03: Both our contributions, Active Learning of Modular Plant Models and Modular Supervisory Synthesis for UnknownPlant Models Using Active Learning are accepted and will be presented atWODES 2020,Rio, Brazil Online.

2019-12: Our contribution Towards data-driven approaches in manufacturing: an architecture to collect sequences of operations has been published in International Journal of Production Research (IJPR) and can be accessed here.

2019-05: Our contribution Synthesis of Supervisors for Unknown Plant Models Using Active Learning has been accepted for CASE 2019, Vancouver, Canada.

**2018-12:** Our contribution From Factory Floor to Process Models: A Data Gathering Approach to Generate, Transform, and Visualize Manufacturing Processes has been accepted for publication in CIRP-JMST can be accessed here.

**2018-5:** Our work Towards Automatic Learning of Discrete-Event Models from Simulations has been accepted for CASE 2018, Munich, Germany.

**2018-5:** I shall discuss my licentiate thesis titled Towards Automatic Generation of Formal Models for Highly Automated Manufacturing Systems in EDIT EB at 13:15 on August 27th.

**2018-2:** Our work Real-time Visualization of Robot Operation Sequences was accepted for INCOM 2018, Bergamo, Italy.

**2016-6:** Our work-in-progress paper Error handling within highly automated automotive industry: current practice and research Needs, has been accepted for ETFA 2016, Berlin, Germany.

**2015-8-20:** I present my master thesis on – Interfacing a collaborative robot and truck held at lunnerummet, EDIT on 20 August 11:00-12:00.