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- MASC students are required to attend 8 seminars for degree completion
- MEng students are required to attend 4 seminars for degree completion
- PhD students - Doctor of Philosophy in Mechanical and Mechatronics Engineering starting Winter 2025 and later are required to attend 8 Mechanical and Mechatronics Engineering research seminars
Note: To receive credit, students can ONLY attend MME Department Research Seminars.
Human-Robot Integration: Designing Interfaces for Augmenting Human Capabilities
Speaker: Dr. Tomoya Sasaki
Tokyo University of Science, Japan
Theme: Robotics
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Time: 2025-Jan-24th, 3:00 pm – 4:00 pm EST
In person in E5-2004
Abstract: This talk introduces an overview of my current research and past projects aiming to augment human
capabilities using robotics, virtual reality, and human-computer interaction approaches.
Dr. Tomoya Sasaki has been an assistant professor at Tokyo University of Science since 2023. He completed
his Ph.D. degree from the Graduate School of Engineering, the University of Tokyo, Japan in 2023. His
research interests include Robotics, Haptics, Wearable Technologies, and Virtual Reality.
Please contact the host, Prof. Yue Hu (yue.hu@uwaterloo.ca), if any questions.
ACES MODEL –
Supporting Atlantic Canada’s Pathway to Net-Zero by 2050
Speaker: Dr. Mohammed Alkatheri
Net Zero Atlantic
Theme: Energy
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Time: 2024-December-2nd, 4:00-5:00 pm
Location: E5-2004 (In-person only)
Refreshments will be provided
Abstract: This presentation will provide an overview of the ACES Model and explore a scenario analysis assessing Atlantic Canada’s commitment to achieving net-zero emissions by 2050, highlighting both opportunities and challenges.
Why ACES?
To fulfill our mission, Net Zero Atlantic created the Atlantic Canada Energy System (ACES) Model—a comprehensive, bottom-up, capacity expansion and linear optimization tool. By identifying least-cost pathways for energy development within specific policy and technology constraints, ACES provides insights into areas that need further study and helps shape our research priorities.
At Net Zero Atlantic, we lead research and projects that support Atlantic Canada’s transition to a carbon-neutral future. Our mandate centres on objectively assessing the impacts of various energy technologies on both the natural and social environment, helping to guide decision-making.
Dr. Mohammed Alkatheri is an Energy System Modeler at Net Zero Atlantic, where he leads the technical development and application of the ACES model. He holds a PhD in Chemical Engineering from the University of Waterloo, where he specialized in optimizing energy systems using advanced data tools such as AI and machine learning. He also holds an MSc from Khalifa University and a BSc from United Arab Emirates University in Chemical Engineering.
At Net Zero Atlantic, Mohammed has been closely involved in enhancing the ACES model, making it a credible, user-friendly tool for Atlantic Canadians, providing insights into "what if" scenarios. His work supports the region’s transition to a sustainable, low-carbon future by identifying strategic pathways and essential research areas to meet ambitious climate targets.
Please contact the host, Prof. XiaoYu Wu (xiaoyu.wu@uwaterloo.ca), if any questions
Enhancing Image-Guided Surgery through Robotic Surgeon-Support Systems
Speaker: Prof. Mahdi Tavakoli
University of Alberta, Canada
Theme: Robotics
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Time: 2024-Nov-29th , 1:00-2:00 pm EST
Online, Zoom meeting: (link)
Abstract: Surgical, therapeutic, and diagnostic interventions can be significantly enhanced using computerintegrated robotic systems with real-time decision-making capabilities that work under the direct, shared, or supervisory control of surgeons and therapists. Incorporating appropriate levels of autonomy in systems for healthcare delivery can lower the mental and physical loads on clinicians while improving the reliability, precision, and safety of the interventions for patients. In this seminar, Dr. Mahdi Tavakoli, Professor and Senior University of Alberta Engineering Research Chair in Healthcare Robotics, discusses several applications of medical robotics and their related challenges and offers solutions based on combining the capabilities of humans with the precision, accuracy, and fast decision-making capabilities of machines.
Prof. Mahdi Tavakoli is a Professor in the Electrical and Computer Engineering Department and the Biomedical Engineering Department and a Senior University of Alberta Engineering Research Chair in Healthcare Robotics. He is also Scientific Vice-Director for the Institute for Smart Augmentative and Restorative Technologies (iSMART) at the University of Alberta. He received his PhD degree in Electrical and Computer Engineering from the University of Western Ontario, Canada, in 2005. From 2006 to 2008, he was a post-doctoral researcher at Canadian Surgical Technologies and Advanced Robotics (CSTAR), Canada, and an NSERC Post-Doctoral Fellow at Harvard University, USA. Dr. Tavakoli’s research interests involve medical robotics, image-guided surgery, and rehabilitation robotics. Dr. Tavakoli is the lead author of Haptics for Teleoperated Surgical Robotic Systems (World Scientific, 2008) and the Specialty Chief Editor for Frontiers in Robotics and AI (Robot Design Section). He is a Senior Member of IEEE and an Associate Editor for the International Journal of Robotics Research, IEEE Transactions on Medical Robotics and Bionics, IEEE/ASME Transactions on Mechatronics’ Focused Section with Advanced Intelligent Mechatronics, and Journal of Medical Robotics Research.
Please contact the host, Prof. Yue Hu (yue.hu@uwaterloo.ca), if any questions.
The Life of an Educator and Entrepreneur
Speaker: Prof. Clovis Maliska
Federal University of Santa Catarina (UFSC), Brazil
Theme: entrepreneurship in mechanical engineering
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Time: 2024-Nov-28th, 3:00 pm-4:00 pm EST
In person only in E5-2004
Clovis R. Maliska is a Full Professor in the Department of Mechanical Engineering at the Federal University of Santa Catarina (UFSC), Brazil. He received his PhD in Mechanical Engineering from the University of Waterloo, Canada, under the supervision of Professor George D. Raithby. He teaches fluid mechanics, heat transfer and computational fluid dynamics at the graduate level in mechanical engineering at UFSC. In 1995, he launched a pioneering book in Brazil on Computational Fluid Dynamics, with the second edition, published in 2004, which is used as a textbook in both under and graduate engineering programs. Professor Maliska is a member of the National Academy of
Engineering (ANE), Chair 71, and has also received the citation (medal) of the National Order of Scientific Merit from the Ministry of Science and Technology.
About this talk: Dr. Maliska completed his PhD in 1981 and launched a successful research and teaching career that resulted in the widespread application of Computational Fluid Dynamics (CFD) across all South America. He was the driving force behind the incorporation of ESSS (Engineering Simulation and Scientific Software Ltd.) that now has offices in Brazil, Argentina, Chile, Peru, Mexico, Columbia, USA (Texas), Portugal, Spain and most recently Italy. His most recent book, Fundamentals of Computational Fluid Dynamics, has had more than 16,000 downloads. Dr. Maliska has received many awards for his work, including honoring him, by the President of Brazil, with the title “Commander of the National Order”. This will be a non-technical lecture in which Dr. Maliska describes the evolution of his life as Professor, Researcher and Businessman. It will be of interest to undergraduate and graduate students who might see entrepreneurship in their future.
Please contact the host, Prof. Yue Hu (yue.hu@uwaterloo.ca), if any questions.
Theoretical Performance Bound and its Experimental Validation
of Battery Capacity Estimates in Rechargeable Batteries
Speaker: Professor Balakumar Balasingam
University of Windsor
Theme: Energy
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Time: 2024-November-22nd, 4:00-5:00 pm
Location: E5-2004 (In-person only)
Refreshment will be provided
Abstract: Capacity of a battery is a salient indicator of aging. Accurate estimation of capacity will help in evaluating the state of health (SOH), predicting its remaining useful life (RUL), and in determining a suitable second use application for the retired battery. The existing methods in the literature employ slow discharge, standard C-rate discharge, or curve-based approaches to estimate the battery capacity. A major drawback of these methods is that the quality of the estimate is not known. The Cramer–Rao lower bound (CRLB) defines the theoretical minimum error variance of an unbiased estimator. This talk discusses several real-world uncertainties that influence the capacity estimation in batteries. Such uncertainties are taken into consideration in deriving the CRLB for the estimated capacity. The derived performance limits help one to choose the method that best fits the quality of capacity estimation in a given application. Experimental data obtained from cylindrical Li-ion battery cells are used to validate the theoretical derivations of capacity estimation uncertainties.
Dr. Balakumar Balasingam (Ph.D., P.Eng. Ontario) received his B.Sc.Eng. degree specializing in Electronics and Telecommunication Engineering with first class honors from the University of Moratuwa, Sri Lanka, in 2002. He received his M.A.Sc. and Ph.D. degrees, both in Electrical Engineering, from McMaster University, Canada, in 2004 and 2008, respectively. He held postdoctoral position at the University of Ottawa from 2008 to 2010, and then a University Postdoctoral position at the University of Connecticut from 2010 to 2012. From 2012 to 2017, he was an Assistant Research Professor in the Department of Electrical and Computer Engineering at the University of Connecticut. From 2017, he has been with the University of Windsor where he is now an Associate Professor. Dr. Balasingam’s research interests are in signal processing, machine learning, information fusion, and their applications in autonomous systems; particularly, his close interests are in battery management systems, human-machine systems, and surveillance & tracking systems. In these areas, Dr. Balasingam has contributed to over 100 peer reviewed research papers, a US patent grant on battery
management systems, and a book, titled “Robust Battery Management Systems with MATLAB” published by Artech House in 2023. Dr. Balasingam is a senior member of IEEE.
Please contact the host, Prof. XiaoYu Wu (xiaoyu.wu@uwaterloo.ca), if any questions.
Use of Remote Sensing Techniques in the Finance and Insurance
Sector
Speakers: Dr. Xi Zhu and Sebastian Paolini van Helfteren
Wholesale & Rural Innovation, Rabobank (Netherlands)
Theme: Interdisciplinary
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Time: 2024-November-13th, 9:30 - 10:30 am (Eastern Time)
Remote: Zoom Link *
Meeting ID: 989 5052 0533 Passcode: MME
Abstract: In this talk, the speakers will be talking about the use of Remote Sensing techniques in the finance and insurance sector, with a focus on the Acorn project. Acorn stands for Agroforestry CRUs for the Organic Restoration of Nature. Acorn is an agroforestry program that unlocks the international voluntary carbon market for smallholder farmers who are realizing agroforestry projects for carbon sequestration through biomass growth, predominantly through trees. Acorn supports the initiation and development of these agroforestry projects and facilitates the subsequent trade of the so-called carbon removal units (CRUs) that are generated from the sequestered carbon. Acorn is currently operating in 28 worldwide projects.
Sebastian Paolini van Helfteren will present in detail the Acorn project and how remote sensing is used in the finance and insurance sector in general, and Dr. Xi Zhu will present the methodology that Acorn used to estimate CRUs for each onboarded plot.
Dr. Xi Zhu and Sebastian Paolini van Helfteren are from Remote Sensing team of Wholesale &
Rural (W&R) Innovation from Rabobank (Netherlands).
* Students who need seminar attendance credit must log in with their UWaterloo accounts or write their name + student ID clearly before joining the meeting. Only attendance > 45 min will count. Otherwise, no attendance credit would be issued.
Please contact the host, Prof. XiaoYu Wu (xiaoyu.wu@uwaterloo.ca), if any questions
Structured Representations for Human-Centered
Embodied AI
Speaker: Prof. Jiajun Wu
Standford University, USA
Theme: Robotics, Reinforcement Learning
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Time: 2024-Oct-25th, 1:00-2:00 pm EDT
Online, Zoom meeting: (link)
Abstract: For embodied AI systems to assist humans in the real world, we must consider
human factors in all aspects. In this talk, I'll introduce our recent work on developing humancentered
embodied AI, including assets, environments, tasks, and learning algorithms. What
is shared across all these works is our choice of structured representations inspired by human
sensory observations, skills, and behaviors. I will discuss how we design the representations,
and how we use them to collect assets, build environments, design tasks, and finally
develop algorithms to solve embodied AI problems.
Jiajun Wu is an Assistant Professor of Computer Science and, by courtesy, of Psychology at Stanford
University, working on computer vision, machine learning, and computational cognitive science. Before
joining Stanford, he was a Visiting Faculty Researcher at Google Research. He received his PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology. Wu's research has been recognized through the Young Investigator Programs (YIP) by ONR and by AFOSR, the NSF CAREER award, paper awards and finalists at ICCV, CVPR, SIGGRAPH Asia, CoRL, and IROS, dissertation awards from ACM, AAAI, and MIT, the 2020 Samsung AI Researcher of the Year, and faculty research awards from J.P. Morgan, Samsung, Amazon, and Meta.
Please contact the host, Prof. Yue Hu (yue.hu@uwaterloo.ca), if any questions.
Challenges of Economic Research in Energy Systems
Speaker: Dr. Patrick Jochem
German Aerospace Centre (DLR)
Theme: Interdisciplinary
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Time: 2024-October-10th, 9:30 - 10:30 am (Eastern Time)
Remote: Zoom Link *
Meeting ID: 919 6700 2966 Passcode: MME
Abstract: The presentation focuses on challenges in decarbonized energy systems and their current transition phase for achieving greenhouse gas emission targets. The consequential conversion of these energy systems correlates with several challenges with regard to technical applicability, economic concerns or social acceptance (among others). The talk will highlight three research areas: (1) Analysis of potential resource scarcities in future energy systems and during their transition including associated threads due to political tensions and dependencies. (2) The technical transition is in most countries well defined, and several suitable scenarios show potential pathways. However, their implementation and the resulting impact on macroeconomic indicators are highly uncertain. Agent based macroeconomic modelling might help to understand these hurdles and develop suitable policy instruments for realizing these transition pathways. Finally, (3) the research on synergetic integration of electric vehicles in national electricity systems is illustrated by presenting current modelling approaches and results, such as resulting greenhouse gas emissions, flexibility provision due to controlled charging etc. For (2) and (3) open-source tools are available, i.e. AMIRIS, sfc tools, REMix, and venco.py.
Bio: Patrick Jochem studied economics at the universities of Bayreuth, Mannheim and Heidelberg, Germany. In 2009, he completed his award-winning doctorate in the field of transport economics at the University of Karlsruhe (TH), funded by the German Federal Environmental Foundation (DBU). In 2009, he founded the "Transport and Energy" research group at the Karlsruhe Institute of Technology (KIT), which he headed until 2019. Between 2014 and 2019, he was a fellow of the Heidelberg Academy of Sciences and Humanities. In summer 2015, he was a visiting professor at the University of Waterloo, Ontario, and completed his habilitation in 2016 with the topic "Electric Mobility and Energy Systems - A techno-economic impact analysis of electric vehicles on the energy system" in the field of business administration at KIT. Since 2016, he has been a member of the editorial board of the journal "Transportation Research Part D: Transport and Environment" and since 2020 he has been Head of Department of Energy System Analysis at the Institute of Networked Energy Systems of the German Aerospace Centre (DLR-VE). Patrick Jochem has published over 100 scientific papers and has an excellent international network in the interdisciplinary field of transport and energy.
* Students who need seminar attendance credit must log in with their UWaterloo accounts or write their name + student ID clearly before joining the meeting. Only attendance > 45 min will count. Otherwise, no attendance credit would be issued.
Please contact the host, Prof. XiaoYu Wu (xiaoyu.wu@uwaterloo.ca), if any questions
Innovating at Interfaces: Enhancing Performance and Longevity of Sustainable Energy Systems
Speaker: Dr. Sami Khan
Simon Fraser University
Theme: Thermal, Fluids
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Time: 2024-September-30th, 3:00-4:00 pm
Location: E5-2004 (In-person only)
Refreshment will be provided
Abstract: Interfaces are ubiquitous, and bottlenecks to performance and longevity in sustainable energy systems often occur due to interfacial interactions. Deciphering and controlling mechanisms underlying these interactions is critical to designing improved and long-lasting sustainable energy and chemical generation systems. My group has developed a novel approach to reduce soot accumulation on biomass combustor surfaces using microtextures, reporting that randomly microtextured surfaces obtained by sandblasting shows a 71% reduction in the time taken to oxidize 90% of surface soot coverage when compared to smooth surfaces at 530°C. We also study grooved microtextures fabricated via laser ablation and find that grooves with widths between 15 and 50 µm enhance soot oxidation, while the expedited advantage is lost when the groove width is 85 µm, indicating that there is an optimal length-scale of surface roughness for this self-cleaning effect to take place. Microtextured surfaces that facilitate soot oxidation upon contact could significantly improve performance and longevity in various combustion applications.
Bio: Dr. Sami Khan is an Assistant Professor in the School of Sustainable Energy Engineering at Simon Fraser University. He obtained his Ph.D. in Mechanical Engineering from MIT in 2020. At SFU, Dr. Khan leads the Engineered Interfaces for Sustainable Energy (EISEn) group, which aims to improve the performance and longevity of sustainable energy systems by fundamentally understanding and tuning electro-chemo-physical interactions at interfaces, with a particular focus on enhancing CO2 capture and conversion processes. He has previously worked in the rare-earth mining industry in Canada and was a Science and Technology Advisor to the Chief Scientist of Natural Resources Canada. He is the recipient of many awards including the Action Canada Fellowship (2021) and the Marcel Pourbaix Award for Best Poster in Corrosion Science (received at the NACE International CORROSION conference in 2019).
Please contact the host, Prof. XiaoYu Wu (xiaoyu.wu@uwaterloo.ca), if any questions.
Leveraging Structure and Abstractions for OOD Generalization
Speaker: Prof. Amy Zhang
UT Austin, Texas, USA
Theme: Robotics, Reinforcement Learning
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Time: 2024-Sept-13th , 2:00-3:00 pm EDT
Online, Zoom meeting: (link)
Abstract: Out-of-distribution generalization relies on leveraging structure inherent to our problem domain. We explore how different structural assumptions common to robotics can be incorporated into reinforcement learning and planning algorithms for improved sample efficiency and generalization. Specifically, we explore object-oriented representations and using them to decompose object rearrangement tasks and quasimetric structure and richer learning signals in goal-conditioned problems.
Prof. Amy Zhang: I am an assistant professor at UT Austin in the Chandra Family Department of Electrical and Computer Engineering. My work focuses on improving generalization in reinforcement learning through bridging theory and practice in learning and utilizing structure in real world problems. Previously I was a research scientist at Meta AI - FAIR and a postdoctoral fellow at UC Berkeley. I obtained my PhD from McGill University and the Mila Institute, and also previously obtained an M.Eng. in EECS and dual B.Sci. degrees in Mathematics and EECS from MIT
Please contact the host, Prof. Yue Hu (yue.hu@uwaterloo.ca), if any questions.
Supervisor: Dr. Roydon Fraser