Automation and controls

Professor Information: 



Arash Arami is an assistant professor at the Department of Mechanical and Mechatronics Engineering at University of Waterloo since December 2017. He is the director of Neuromechanics and Assistive Robotics Laboratory. Dr. Arami is cross appointed in System Design Engineering department and an active member of Waterloo Robohub, Centre for Bioengineering and Biotechnology and Waterloo AI institute. He is also an affiliated Scientist at KITE, Toronto Rehab Institute (University Health Network). 

Before, he was a Research Associate at Human Robotics Group at Imperial College London, from August 2015 to December 2017, working mainly on modelling human neuromechanics and design of collaborative controllers for exoskeletons. He was also a Postdoctoral Researcher at Ecole Polytechnique Fédéral de Lausanne (EPFL) from March 2014 to August 2015 in the Laboratory of Movement Analysis and Measurement, when his research was more focused on wearable systems, signal processing and application of machine learning in human movement analysis. He obtained his PhD from EPFL on 2014 on design and evaluation of smart prostheses, and kinematics estimation and loosening detection of endoprostheses. 


 

  • Assistive Robotics 

  • Human-Robot Interaction 

  • Rehabilitation Engineering 

  • Neuromechanics and Sensorimotor Modelling 

  • Neural Control of Movements 

  • Intelligent Systems 

  • Wearable Systems 

  • System Identification 

  • Applied AI 



Sanjeev Bedi is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo. He is the founder of the Engineering IDEAs Clinic and the NSERC Chair in Immersive Design Engineering Activities (IDEAs). Professor Bedi leads the 5-Axis Surface Machining Lab and was a former Director of Mechatronics Engineering (06-12). 

Professor Bedi’s research interests are in flank milling, the development of tool path strategies, the design of NC controllers, 5-axis numerically controlled machining, the modeling of the machining process and the design of NC machines. His research expertise lies in automated polishing, complex curve machining methods, efficient tool path planning, gouge detection and avoidance mechanisms, machined surface evaluation, and surface finish estimation. 

The 5-axis machine lab is designed to conduct research into 5-axis machining. 5-axis machines are becoming increasingly popular in the industry, however the techniques required to take advantage of the additional flexibility of these machines are still in their infancy. 


 

  • Flank milling 

  • Development of Tool Path Strategies  

  • Design of NC Controllers 

  • 5-Axis Numerically Controlled Machining 

  • Modeling of the Machining Process (PAM and MPM) 

  • Design of NC Machines 

  • Ornamental Wood Working 

  • Gouge detection and Avoidance Mechanisms 

  • Machined Surface Evaluation 

  • Surface Finish Estimation 

  • Mechatronics 

  • Automotive 

  • Gouge detection and Avoidance Mechanisms 

  • Automated Polishing 

  • Complex Curve Machining Methods: Principle Axis Method (PAM) and Multi-Point Method (MPM) 

  • Design of Numerical Control (NC) Machines and Controllers 

  • Machined Surface Evaluation 

  • Surface Finish Estimation

Russell Buchanan is an Assistant Professor of Intelligent Systems in the Department of Mechanical and Mechatronics Engineering since 2024 and is the principal investigator of the Robotic Interaction, Perception and Learning Lab. Previously, he was a postdoctoral research associate at the University of Edinburgh, UK and affiliated with the Alan Turing Institute. He received his Doctor of Philosophy (DPhil) from the University of Oxford in 2024 for his work on perception for legged robots in challenging, vision-denied environments. He received his master's degree from ETH Zurich, Switzerland in 2018, which included an 8-month research stay at CSIRO in Brisbane, Australia.

His research interests are in SLAM, state estimation and mapping for mobile robots in challenging, real-world conditions. Learn more about his research in his: Robotic Interaction, Perception and Learning Lab.

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  • Robot Perception
  • State Estimation
  • Legged Robots
  • Deep Learning
  • Field Robotics
  • Computer Vision



Kaan Erkorkmaz is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo. He is a Fellow of the International Academy for Production Engineering (CIRP) and also a Registered Professional Engineer in the Province of Ontario. 
 
Professor Erkorkmaz’s research interests are in the areas of precision manufacturing, machining, and dynamics; controls, and optimal trajectory planning for machine tools; with the objective of increasing the productivity, part quality, and resource efficiency in manufacturing operations. 


 

  • Precision Engineering 

  • Dynamics 

  • Controls 

  • Manufacturing 

  • Mechatronics 

  • Automotive 

  • Advanced Robotics 

  • Controls and Precision Tooling 

  • Digital Factories 

  • Digital Design and Fabrication Technologies 

  • Embedded Systems 

  • Sensors and Devices 

  • Machining Automation 

  • Additive Manufacturing 

  • Advanced Manufacturing



Baris Fidan is a Professor in Mechanical & Mechatronics Engineering, with cross appointment in System Design Engineering and Electrical & Computer Engineering at the University of Waterloo. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE) and the American Institute of Aeronautics and Astronautics (AIAA). 

His research interests include cooperative and adaptive control, system identification, nonlinear system theory, multi-agent systems and sensor networks, robotics and intelligent systems, and various control applications including vehicular controls and control of mechatronic and biomedical systems. 

Professor Fidan has been the principal investigator for the NSERC discovery programs `Cooperative and Adaptive Mechatronic Systems: Identification, Control, and Optimization' and 

‘Distributed Geometric Coordination of Autonomous Vehicle Networks Moving in Three Dimensions’ and the CFI-ORF Research Infrastructure ‘Cooperative Autonomous Vehicle Network Test-Bed’. He has also been the principal investigator or co-investigator of a number of industrial research projects, including the Mitacs Project `Localization, Monitoring, and Motion Coordination of Autonomous Indoor Service Robots', NSERC/ORF CRD projects `Autonomous Driving Strategies for Urban and Highway Environments', `Development of New Technologies for Design and Popularization of Urban Vehicles', `Holistic Vehicle Control', `Hard Shaping and Accelerated Dressing Technologies for High-Productivity / High-Quality Gear Manufacture'. 


 

  • Adaptive control 

  • Nonlinear control 

  • System identification 

  • Sensor networks  

  • Multi-agent systems 

  • Robotics 

  • Operational Artificial Intelligence 

  • High performance flight control 

  • Autonomous and Connected Car 

  • Automotive 

  • Operational Artificial Intelligence 

  • Robotics 

Yue Hu 

Yue Hu



Yue Hu is an Assistant Professor at the Department of Mechanical and Mechatronics Engineering at the University of Waterloo since September 2021, head of the Active & Interactive Robotics Lab. Prior to joining The University of Waterlooo, Yue had lived and worked in many different places and countries. She obtained her master's degree in Advanced Robotics from the University of Genova, Italy, and Ecole Centrale de Nantes, France, in 2013. She then carried out her PhD in robotics at Heidelberg University, Germany, receiving her degree in 2017. She was postdoc first at Heidelberg University, then at the Italian Institute of Technology (IIT), in Italy. Between 2018 and 2021 she was first a JSPS (Japan Society for the Promotion of Science) fellow at the National Institute of Advanced Industrial Science and Technologies (AIST) in Japan, and then an Assistant Professor at the Department of Mechanical Systems Engineering, Tokyo University of Agriculture and Technology. Yue is one of the co-chairs of the IEEE-RAS Technical Committee on Model-based Optimization for Robotics. Her research interests include physical human-robot interaction, collaborative robots, humanoid robots, and optimal control.


 

  • Robotics 

  • Collaborative robots 

  • Human-robot interaction 

  • Human Motion Analysis 

  • Humanoid Robots 

  • Optimal control 



Dr. Carol Hulls, P.Eng. is Associate Chair Teaching and a Continuing Lecturer in the Mechanical and Mechatronics Engineering Department. Her role involves supporting instructors in the department to improve teaching and learning in a wide range of areas including mentoring of new faculty, supporting the adoption of innovative teaching and learning approaches, and promoting reflective practice as a way to improve teaching. She has been teaching courses in programming, sensor fusion, and computer hardware since 1999, and has taught several thousand first year engineering students, primarily in mechanical and mechatronics engineering. In 2016 she received the Brightspace Innovation Award in Teaching and Learning for her work developing open-ended design activities for first year students in engineering. After having spent much of the pandemic live-streaming her lectures from home, she is happy to return to the classroom and the greater interaction it provides with students. 


 

  • Engineering education 

  • Experiential learning 

  • Use of technology for teaching 

  • Real-time sensor fusion 



Soo Jeon is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo. 

Professor Jeon’s expertise lies in the broad areas of mechatronics, dynamic systems, instrumentation and control. His research projects include Sensing-Rich Drive Trains, Multimodal Sensory Feedback for Dexterous Manipulation, Non-Linear Dynamics of Controlled Mechanical Systems, Autonomous and Self-Sustaining Systems. 

Professor Jeon is the recipient of the 2022 AKCSE/KOFST Engineer of the Year Award, the Rudolf Kalman Best Paper Award from ASME for the year 2010 and the Discovery Accelerator Supplement Award from the NSERC for the year 2015. 

He is a member of ASME, IEEE and CSME. He serves as an associate editor for ASME Journal of Dynamic Systems, Measurement and Control (2015 ~ 2021), IEEE Transactions on Automation Science and Engineering (2015 ~ 2018), IEEE/ASME Transactions on Mechatronics (2020 ~ ) and IEEE Robotics and Automation Letters (2022 ~ ). 


 

  • Automation 

  • Robotics 

  • Control 

  • Intelligent Systems 

  • Estimation 

  • Sensors and sensing systems  

  • Nonlinear mechanics 



Amir Khajepour is a professor of Mechanical and Mechatronics Engineering and the Director of Waterloo Center for Automotive Research (WatCAR) and the Mechatronic Vehicle Systems (MVS) Lab. He held the Tier 1 Canada Research Chair in Mechatronic Vehicle Systems from 2008 to 2022 and the Senior NSERC/General Motors Industrial Research Chair in Holistic Vehicle Control from 2017 to 2022. His work has resulted in training of over 160 PhD and MASc students, 30 patents, 600 research papers, many books, numerous technology transfers, and several start-up companies. He has been recognized with the Engineering Medal from Professional Engineering Ontario and is a fellow of the Engineering Institute of Canada, the American Society of Mechanical Engineering, and the Canadian Society of Mechanical Engineering. 

To add to his accolades, Amir recently became the Director of the Waterloo Centre for Automotive Research (WatCAR). 


 

  • Hybrid vehicles 

  • Suspension systems 

  • Vehicle noise vibration and harshness (NVH) 

  • Vibration analysis and control 

  • Modeling and control of laser cladding 

  • Automation and robotics 

  • Mechatronics 

  • Automotive  

  • Autonomous and connected car 

  • Vehicle dynamics and systems control 

  • Additive manufacturing  

  • Advanced manufacturing 

  • Robotics 

  • Cloud-based Fleet mobility 

  • Advanced Suspension Systems 

  • Automated Warehousing 

  • Mobile Robots 

  • Large-scale Cable Robotics 

  • Vehicle Control and Estimation Systems 



Behrad Khamesee is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo. He is also an integral member of the Waterloo Center for Automotive Research (WATCAR). 
 
Professor Khamesee’s research interests are in microrobotics and micromanipulation using magnetic levitation, magnetically driven medical microrobots for drug delivery and microsurgery, smart structures and actuators, and the development of a cost-effective prosthetic leg. 
 
He is also the Director of Maglev Microrobotics Laboratory, which studies the design and development of magnetically levitated (Maglev) robots. A magnetic Levitation setup enabling high precision 3D remote positioning was built. The lab is also working on the development and industrialization of various applications of magnetism such as electromagnetic energy harvesters for human locomotion and regenerative electromagnetic suspension system for vehicles, and non-destructive testing for detecting cracks and defects in live pipelines. 
 
Dr. Khamesee is a Co-PI in the development of RoboHub through a large CFI grant. His research team designed, fabricated, and installed a Magnetic Levitation Floor in the RoboHub for flexible manufacturing applications. 


 

  • Mechatronics 

  • Microrobotics 

  • Magnetic levitation 

  • Micromanipulation 

  • Automation and robotics 

  • Microactuator 

  • Biomechanics and Biotechnology 

  • Automotive  

  • MEMS 

  • Connectivity and Internet of Things 

  • Electromagnetic Actuators 

  • Additive Manufactring 

  • Robotics 

  • IoT 

  • Devices 

  • Energy Harvesting 

  • Advanced manufacturing 



William Melek is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo. He also serves as the Director of the Laboratory of Computational Intelligence and Automation, and the Director of RoboHub

The Laboratory of Computational and Intelligence Automation conducts research on modular robotics and Intelligent Systems Modeling and Control. The research efforts place emphasis on manufacturing and automotive applications which involves design of modeling and control algorithms for flexible automation, autonomous systems and vehicles stability systems. Bioinformatics is also an area of research undertaken by Professor Melek and his team. This research involves clinical decision-support systems and non-convex optimization methods for scheduling clinical resources. 


 

  • Artificial Intelligence 

  • Intelligent Control 

  • Mechatronics 

  • Automotive Design Model & Control of Advanced Mechatronics Systems 

  • Modular and Reconfigurable Robotics & Automation 

  • Autonomous Navigation and Mobile Manipulation 

  • Computational Intelligence 

  • Advanced robotics 

  • Autonomous vehicles 

  • Hybrid and electric vehicles 

  • Big data/analytics 

  • Sensors and devices 

  • Autonomous and connected car 

  • Advanced manufacturing 

  • Operational Artificial Intelligence 



Professor Katja Mombaur is the Canada Excellence Research Chair in Human-Centred Robotics and Machine Intelligence. She is an expert on human-robot interaction, wearable and humanoid robots, and human motion analysis. 
In the RoboHub, Professor Mombaur conducts research on developing robots with “motion intelligence,” a particular kind of AI that incorporates an understanding of human movement and anticipation of human actions. She also works with wearable and humanoid robots to determine how increasingly intelligent machines can operate safely and efficiently in a complex human world, and how they should behave in that world. She uses mathematical modelling to teach robots how to move and to design the best possible assisstive devices, such as exoskeletons and prosthetic limbs, for the elderly and disabled. 


 

  • Human-robot interaction 

  • Wearable robots 

  • Rehabilitation robots 

  • Intelligent assistive devices 

  • Humanoid robots 

  • Human movement analysis 

  • Optimal control 

  • Model-based control 

  • Multibody systems modeling 



Patricia Nieva is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo. 

She is an expert in micro- and nano- technologies and in particular, the development of microsensors, nanosensors and integrated sensor system solutions. She has established a multidisciplinary research program that aims to build novel sensing methodologies to enhance vehicle safety and performance, as well as point-of-care health monitoring and medical diagnosis. The focus of her work is on chemical and biological photonic sensing technologies involving fiber optics and nanostructured plasmonic devices, as well as high-temperature MEMS (Micro-Electro-Mechanical Systems) capacitive, infrared and interferometric sensing technologies. Her work also spans reliability studies of microsystems, in-situ characterization of material properties of thin films, and the manufacturing of metallic nanoparticles for sensing applications. Professor Nieva is also recently involved in a project to build a handheld cardiac monitor that will measure proteins in the blood commonly linked to a heart attack, alerting the patient’s doctor before symptoms appear. 

Her ongoing research work constitutes an important commitment to the identification of simple, cost-effective and reliable micro- and nano- technologies for advanced sensing. Professor Nieva’s research has led to 2 patents (one awarded and one provisional). She has authored and co-authored more than 90 journal and conference publications, and is also a member of the Institute of Electrical and Electronic Engineers (IEEE), the American Society of Mechanical Engineers (ASME) and the Phi Kappa Phi Honor Society. 


 

  • Micro- and Nano Electro Mechanical Systems (MEMS and NEMS) for harsh environments 

  • Physical sensors and devices 

  • Micro-Opto-Electro-Mechanical Systems (MOEMS) and adaptive Optics 

  • BioMEMS sensors 

  • MEMS packaging and reliability 

  • Integrated microsystems 

  • Micropower Generation (MPG) 



Dr. William (Bill) Owen is a Lecturer and our Associate Chair of Undergraduate Studies in the Department of Mechanical and Mechatronics Engineering.


 

  • Robotics 

  • Trajectory planning 

  • Motion planning 

  • Modeling 

  • Robotic machining 

  • Friction 

  • Mechatronics



Dr. Toyserkani holds the Canada Research Chair position in Additive Manufacturing (AM) and has over 20 years of experience in different aspects of AM research and development, from mechatronics AM system development to AM applications in medicine and engineering. He established the first AM laboratory at a Canadian university - the Multi-Scale Additive Manufacturing (MSAM) Laboratory – which focuses on the development of the next generation of AM processes and applications. 
 
His lab is now the most comprehensive AM academic facility in Canada and one of the top 5 academic AM facilities in the world. His extensive experience in AM and leadership have allowed him to devote his academic life to addressing AM challenges holistically and promoting this strategic research area at the national and international level. 
 
He is an active steward in the AM field. He is the director of a Pan-Canadian NSERC Strategic Network entitled “Holistic Innovation in Additive Manufacturing (HI-AM)”, that brings together leading AM experts from seven top Canadian universities including University of Waterloo, University of Toronto, University of British Columbia, McGill University, University of Alberta, Laval, and, Dalhousie. Several international universities and 14 industrial partners are involved in this network. Further information can be found in this website: HI-AM | NSERC Network for Holistic Innovation in Additive Manufacturing (nserc-hi-am.ca). 
 
He is a voting member of the American Society for Testing and Materials International (ASTM)-Committee F42, which is a leading committee in the development of standards for AM. He is also a member of the AM Advisory Committee of Advanced Manufacturing Supercluster (NGen) and was a member of the NSERC Selection Committee for Strategic Grant Applications (Advanced Manufacturing Target Area) from 2015 to 2018. He has been invited for >50 talks/panels in different countries. His research has been highlighted in many magazines and newspapers such as “The Globe and Mail”. 
 
He has 18 granted/pending patents on different aspects of AM. He has actively transferred his innovative technologies to industry. Two start-up companies have been established that stem from his R&D programs. 
 
His research is having a significant impact in the young AM field. He has published 135 AM-related journal articles (received >5800 citations as of October 2021). His research has been recognized through many awards/honours. 


 

  • Additive manufacturing 

  • Laser metal powder-fed and powder-bed additive manufacturing: Modeling, real-time control and process adoption 

  • Smart structures with embedded optical sensors developed by additive manufacturing 

  • Bio-additive manufacturing 

  • Additive Manufacturing of Smart Structures with Embedded Optical Sensors 

  • Advanced Manufacturing 



James is an Assistant Professor in the Department of Mechanical and Mechatronics Engineering. His research is focused on sensor technologies that improve diagnostic capabilities, prevent injuries, and optimizing treatment for individuals with chronic conditions.  

Some of his previous projects include developing devices and techniques to assess the risk of a disruptive event, and the development of assistive robots to help with safe mobilities for individuals with disabilities.


 

  • Assistive Technology 

  • Rehabilitation Engineering 

  • Connectivity and Internet of Things 

  • Robotics 

  • Neuromotor control 

  • IoT 

  • Devices 

  • Biomedical Engineering 

  • Bioengineering 



Additive manufacturing is rapidly changing the manufacturing landscape. Dr. Vlasea’s research focuses on innovative design, process optimization and adoption of new materials for powder bed fusion and binder jetting additive manufacturing processes. The research goals are to bridge the technological gaps necessary to improve part quality, process repeatability and reliability.


 

  • Additive manufacturing 

  • Advanced manufacturing 

  • Power bed fusion 

  • Binder jetting 

  • Process modeling 

  • Digital design optimization 

  • Process optimization 

  • Process modeling 

  • Data analytics 

  • Monitoring