جستجوی استاد راهنمای دانشگاهی

• High-speed data converters
• Wireless transceivers
• Digital phase-locked loops
• +۷ مورد دیگر

Shiyu Su is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. His research focuses on high-speed data converters, wireless transceivers, digital phase-locked loops (PLL), and AI-assisted analog/mixed-signal design automation. He holds a Ph.D. from the University of Southern California (2019) and teaches courses such as ECE 340 (Electronic Circuits 2) and ECE 432 (Radio Frequency Integrated Devices and Circuits). Education: B.S. from Beijing University of Post and Telecommunication (China) and Queen Mary, University of London (UK), 2011; M.S. and Ph.D. from USC, 2013 and 2019, all in electrical engineering. Research Interests: High-speed ADCs/DACs RF/mm-wave transceivers Time-approximation filters (TAF) Analog/mixed-signal design automation Memristor-based computing Biomedical interfaces Key Awards: IEEE SSCS Predoctoral Achievement Award (2017–2018) Best Student Paper Award at IEEE RFIC (2022) Ming Hsieh Institute Scholar (2019–2020) Lab Focus: The Shiyu Su Lab develops integrated circuits for communications, sensing, and computing, with a focus on AI-driven methodologies and digital-analog co-design. Collaborations include work with Prof. Wei Wu (USC) on memristor-based systems.

Qingguo Liمشاهده پروفایل

استاد

• Biomechanical system design
• Energy harvesting
• Wearable sensors
• +۴ مورد دیگر

Qingguo Li is a Professor and Associate Head at the Department of Mechanical and Materials Engineering , Queen's University , and a member of the Ingenuity Labs Research Institute . He specializes in biomechanical system design, energy harvesting, wearable sensors, gait analysis, and load carriage systems. His research integrates robotics, biomedical engineering, and sensor technology to develop human-centric devices and mobility aids. Current Roles : Professor, Associate Head, Queen's University Research Institute : Ingenuity Labs Research Institute Lab : Bio-Mechatronics and Robotics Laboratory His work focuses on biomechanical energy harvesting , IMU-based motion analysis , and assistive device development . Key applications include stroke rehabilitation, gait monitoring, and wearable power generation systems. Articles span cable-driven robots , smart walkers , and 3D printing mechanisms , emphasizing human-robot interaction and dynamic modeling . The lab explores sensor calibration , adaptive control algorithms , and human movement optimization . Areas of impact include rehabilitation engineering , load carriage stability , wearable sensor accuracy , and assistive robotics . His team develops solutions for gait asymmetry detection , post-stroke mobility , and low-cost energy systems , leveraging machine learning and kinetic modeling .

Abbas Samaniمشاهده پروفایل

استاد

• Biomedical Engineering
• Medical Imaging
• Computational Modeling
• +۵ مورد دیگر

Prof. Abbas Samani is a Professor at the Department of Electrical and Computer Engineering and holds a joint appointment in the Department of Medical Biophysics at Western University . He is a core faculty member of the Biomedical Engineering Graduate Program and an Associate Scientist at Imaging Research Laboratories of Robarts Research Institute . His academic journey includes a Ph.D. from the University of Waterloo, an M.Sc. from the University of Tehran, and a B.Sc. from Amirkabir University of Technology. His research focuses on biological tissue computational modeling and its applications in medical imaging, intervention, and image analysis . He develops computer/image-assisted tools for minimally invasive disease diagnosis and therapy , targeting heart disease, cancer, and lung disease . Key projects include myocardium biomechanical modeling , handheld medical devices for breast cancer screening , and lung disease diagnostics via CT image segmentation . His recent publications emphasize ultrasound elastography , finite element modeling , and inverse problems in biomechanics , primarily in journals like IEEE Transactions on Computational Imaging and Translational Oncology . His work spans both computational modeling and medical device development . Selected Graduate Supervision : Ph.D. Candidates : Seyed Hassan Haddad, Elham Karami, Seyed Mohammad Hesabgar Graduated Ph.D. Students : Ali Sadeghi Naini, Seyed Reza Mousavi M.Sc. Students : Cristian Linte, Patrick Courtis, Joseph O'Hagan, Hatef Mehrabian, Hirad Karimi, Hosein Amooshahi, Seyed Mohammad Hesabgar, Nastaran Ghadarghadr, Shadi Shavakh, Ehsan Salamati, Ehsan Omidi Teaching Contributions : Graduate: BME9519B/CAMI9519B/ECE9202B/ECE9022B - Advanced Image Processing and Analysis , MBP9530A - Human Biomechanics and Biomedical Applications Undergraduate: ECE4438B - Advanced Image Processing and Analysis , ES1050 - Introductory Engineering Design and Innovation Studio , MBP3330F - Human Biomechanics and Biomedical Applications Research Affiliations : Robarts Research Institute - Associate Scientist at Imaging Research Laboratories Western University - Core Faculty, Biomedical Engineering Graduate Program

Jason H. Andersonمشاهده پروفایل

استاد

• Computer Engineering
• Electrical Engineering
• Computer-Aided Design (CAD)
• +۳ مورد دیگر

Professor Jason H. Anderson is a faculty member in the Department of Electrical & Computer Engineering (ECE) at the University of Toronto, affiliated with the Faculty of Applied Science & Engineering. He specializes in computer engineering, with a focus on field-programmable gate arrays (FPGAs) and related computer-aided design (CAD) tools. BSc in Computer Engineering from the University of Manitoba MASc and PhD in Electrical & Computer Engineering from the University of Toronto His research spans FPGA architecture, circuit design, and CAD tool development. He has contributed to strategic R&D projects through his academic and industry roles. Scientific awards include multiple Best Paper Awards at IEEE and ACM conferences (2017, 2014, 2011, 2010, 2009), the Xilinx Ross Freeman Award (2000), and teaching accolades such as the Gordon Slemon Award (2012) and several ECE Departmental Teaching Awards (2009-2014). He served as General Chair and Program Chair for leading FPGA conferences. As Chief Scientific Advisor and Co-Founder of LegUp Computing Inc., he bridges academic research with industry innovation. He is a licensed Professional Engineer in Ontario and an active IEEE/ACM member.

Karen Cochraneمشاهده پروفایل

استادیار

• Human-Computer Interaction (HCI)
• Mental Health Technologies
• Accessibility
• +۶ مورد دیگر

Dr. Karen Cochrane is an Assistant Professor at the University of Waterloo, specializing in Human-Computer Interaction (HCI) with a focus on wearable and tangible computing for mental health and accessibility. Her research integrates soma design, autoethnography, and design fiction to address the needs of underrepresented communities, particularly those with disabilities. Key projects include developing assistive technologies for queer/crip identities, accessible gaming wearables, and tactile interfaces for sensory exploration. She explores embodied experiences through multidisciplinary approaches, blending traditional craft practices with modern computational tools. Her work prioritizes participatory design methodologies, collaborating with occupational therapists, disabled communities, and neurodivergent individuals to co-create inclusive technologies. Recent innovations include VARitouch (a haptic feedback device), Breathing Scarf (for emotional regulation), and adaptive switches for children with motor disabilities. Her research extends into sensory narratives, exploring how fabric and data can articulate bodily experiences through projects like Sensory Data Dialogues and Queer/Crip Body Mapping. While no formal grants or awards are listed, her publications reflect a strong focus on ethical technology, accessibility, and embodied interaction. Current projects emphasize the intersection of wearable tech with identity expression, mindfulness practices, and neuromotor rehabilitation. She actively designs prototypes that bridge clinical needs with creative technology solutions, though specific lab affiliations or team collaborations are not detailed in available texts.

Mahmoud El-Sakkaمشاهده پروفایل

دانشیار

• Image Compression
• Medical Imaging
• Image Segmentation
• +۵ مورد دیگر

Mahmoud El-Sakka is an Associate Professor at the Department of Computer Science, University of Western Ontario since 1999. Previously, he was a faculty member at the University of Waterloo (1997–1999). He holds a B.Sc. and M.Sc. from Alexandria University (Egypt) and a Ph.D. in Systems Design Engineering from the University of Waterloo. His research focuses on medical imaging, image processing, and computer-aided diagnostics. He has served as Chair of the graduate program (2002–2007) and undergraduate program (2017–present) in Computer Science at Western Ontario. El-Sakka is a Senior Member of the IEEE and a licensed Professional Engineer in Ontario. His work spans grants from NSERC, internal university funding, and industry collaborations. Major research areas include image compression, segmentation, and medical applications like vascular analysis and echocardiography. He has led over 20 funded projects since 1999, emphasizing interdisciplinary approaches in healthcare technology. Academic contributions include advisory roles in summer programs, thesis evaluations, and conference participation. His service includes roles as Pro-Chancellor at convocations and involvement in equipment purchasing committees. Collaborations include consulting with NCR Canada and VRP Web Technology.

Ebrahim Bedeer Mohamedمشاهده پروفایل

استادیار

• Signal Processing
• Wireless Communications
• Artificial Intelligence
• +۳ مورد دیگر

Ebrahim Bedeer Mohamed is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Saskatchewan. He joined in July 2019, following roles as an Assistant Professor (Lecturer) at Ulster University, UK, and postdoctoral fellowships at Carleton University and the University of British Columbia. He holds a Ph.D. (Distinction) from Memorial University of Newfoundland (2014), with expertise in signal processing and wireless communications. His research focuses on optimizing communication systems through advanced signal processing techniques, including faster-than-Nyquist signaling, IoT network design, AI integration, and energy-efficient protocols. Key areas include next-generation communication networks, non-orthogonal modulation, and MIMO systems. Notable contributions include work on channel estimation for FTN signaling, RIS-aided wireless systems, and LR-FHSS protocols in IoT. His publications span spectral efficiency, interference minimization, and energy management in 5G/6G contexts. He actively seeks Ph.D. students with strong backgrounds in signal processing fundamentals. Awards and grants are not explicitly listed in the provided texts. His work emphasizes practical applications, such as UAV trajectory optimization for IoT data collection and energy-efficient caching strategies in dynamic networks.

Matt Rattoمشاهده پروفایل

استاد

• Artificial Intelligence
• Human-Computer Interaction
• Critical Making
• +۷ مورد دیگر

Matt Ratto is a full Professor in the Faculty of Information at the University of Toronto , where he also serves as Associate Dean, Research . He is a faculty affiliate of the Climate Positive Energy Institute , the Schwartz Reisman Institute for Technology and Society , and an SDG Fellow with the Sustainable Development Goals Institute . His work bridges critical theory and digital innovation , focusing on the social production of knowledge through emerging technologies. His research explores critical making and socio-technical systems , with applications in 3D-printed prosthetics (deployed in Cambodia, Tanzania, and Uganda), AI-driven healthcare solutions , and climate justice in computing . He has received over $6 million in funding, including two Canada Grand Challenge grants , and founded organizations advancing equitable technology access. Ontario Minister of College and Universities’ Award of Excellence (2020) Bell Canada Usability Labs Chair in Human-Computer Interaction (2018–2023) He supervises students such as Olivia Doggett and Sarah Gram , with past advisees including Brian Sutherland and Dan Southwick . His Critical Making Lab fosters interdisciplinary collaboration, and he teaches courses like INF2241: Critical Making and INF351: Information Design Studio .

Nicola Nicoliciمشاهده پروفایل

استاد

• Digital Integrated Circuit Design
• Hardware Testing
• Post-Silicon Validation
• +۷ مورد دیگر

Nicola Nicolici is a Professor in the Department of Electrical and Computer Engineering at McMaster University. His research focuses on methods and algorithms for the design of digital integrated circuits and systems, with significant contributions in manufacturing test, post-silicon validation and debug. His work has expanded to include embedded systems, low-energy computing, and custom hardware-accelerated computing systems. Professor Nicolici's research interests span multiple areas of digital system design and validation. His early work focused on manufacturing test methodologies and power-aware testing strategies for integrated circuits. More recently, he has made significant contributions to post-silicon validation techniques, including constrained-random stimuli generation, trace signal selection, and bit-flip detection. His research has evolved to address emerging challenges in embedded computing systems, low-energy design, and specialized hardware acceleration for various applications including deep neural networks and signal processing. His recent publications reveal a strong trend toward hardware acceleration for specialized computing tasks. The research spans matrix multiplication algorithms (Strassen and Karatsuba), memory system optimization (DDR5 calibration), FPGA-based radar processing, and neural network acceleration. His work consistently bridges theoretical algorithm development with practical hardware implementation considerations, particularly focusing on precision analysis, fault tolerance, and energy efficiency. The research demonstrates a clear progression from traditional digital circuit testing to more complex system-level validation and acceleration techniques. Professor Nicolici has been actively involved in teaching courses related to system-on-chip design and test, digital systems, and embedded systems. His teaching portfolio includes advanced courses such as System-on-Chip (SOC) Design and Test and Digital Systems Design , reflecting his expertise in the field. While specific grant information isn't detailed in the provided text, his extensive publication record suggests ongoing research funding support. His research has contributed significantly to the fields of digital circuit testing, post-silicon validation, and hardware acceleration. The work has practical applications in semiconductor manufacturing, embedded systems design, and specialized computing architectures. His recent focus on neural network acceleration and memory system optimization reflects the evolving landscape of computer architecture research.

Ian C. Bruceمشاهده پروفایل

استاد

• Auditory modeling
• Hearing aids
• Cochlear implants
• +۴ مورد دیگر

Dr. Ian Bruce is a Professor in the Department of Electrical and Computer Engineering at McMaster University, Hamilton, ON, Canada. He has been with the department since 2002, conducting interdisciplinary research that bridges electrical engineering with auditory neuroscience. His work has significant implications for hearing technologies and auditory rehabilitation. Education: B.E. (electrical and electronic) from The University of Melbourne (1991) Ph.D. from the Department of Otolaryngology, The University of Melbourne Dr. Bruce's research program focuses on auditory modeling, hearing aids, cochlear implants, tinnitus, neural coding of speech, and digital speech processing. His work centers on understanding the physiological mechanisms of auditory processing and applying this knowledge to develop improved hearing technologies. He has pioneered computational models of the auditory periphery that accurately predict speech intelligibility for hearing-impaired listeners, directly informing hearing aid and cochlear implant design. Analysis of Dr. Bruce's recent publications (2019-2025) reveals a consistent focus on cochlear implants and auditory nerve modeling, with increasing integration of machine learning techniques. His work demonstrates a sophisticated balance between physiological accuracy and computational efficiency, with recent papers exploring WaveNet-based approximations of cochlear models and DNN-based auditory processing. A significant portion of his research examines the relationship between neural responses and perceptual outcomes in hearing-impaired individuals, particularly regarding temporal processing and speech understanding. Scientific Awards and Recognitions: Fellow of the Acoustical Society of America Member of the Association for Research in Otolaryngology Registered Professional Engineer in Ontario Associate Editor of the Journal of the Acoustical Society of America Dr. Bruce has mentored numerous graduate students through various capstone design projects across multiple engineering disciplines including biomedical, electrical, mechanical, and software engineering. His teaching portfolio includes specialized courses in biomedical signals and systems, cellular bioelectricity, models of the neuron, and advanced signal processing. He has consistently supervised M.Eng. projects and independent studies, demonstrating commitment to training the next generation of engineers in auditory technology development. Dr. Bruce's research is conducted within McMaster University's interdisciplinary biomedical engineering framework, collaborating with clinicians and researchers in otolaryngology and audiology. His laboratory work focuses on developing and validating computational models that simulate auditory nerve responses to both natural and prosthetic stimulation, with direct applications to improving cochlear implant performance and hearing aid algorithms for real-world listening environments.

Jonathan Roseمشاهده پروفایل

استاد

• FPGA architecture
• Computer-Aided Design (CAD)
• Field-Programmable Systems
• +۳ مورد دیگر

Jonathan Rose is a Professor in the Edward S. Rogers Sr. Department of Electrical and Computer Engineering at the University of Toronto . He received his PhD in Electrical Engineering from the University of Toronto in 1986 and held postdoctoral and research roles at Stanford University's Computer Systems Laboratory (1986-1989). His academic career spans decades, including a 1998-1999 sabbatical at Xilinx and leadership roles at Altera Toronto Technology Centre. He served as Department Chair of Electrical and Computer Engineering (2004-2009) and directed the Engineering Business Minor (2010-2017). Currently, he chairs the Engineering Entrepreneurship Hatchery Advisory Board and engages with organizations like Academics without Borders and Massey College. His research has historically focused on FPGA architecture , Computer-Aided Design (CAD) , Field-Programmable Systems , and Soft Processors . More recently, his work explores the Automation of Medicine , particularly in mental health. His contributions include co-founding the ACM FPGA Symposium and receiving numerous awards for teaching, research, and leadership. Scientific Awards : University of Toronto Engineering Alumni Hall of Distinction Award, 2017 Best Paper Award, ACM TRETS, 2016 University of Toronto President’s Teaching Award, 2016 Foreign Member of the American National Academy of Engineering, 2011 Fellow of the Royal Society of Canada, 2012 The 15 most recent articles reflect his interdisciplinary engagement, spanning Political Science , Public Policy , and Deliberative Democracy , with sub-fields such as Employability Support , Electoral Reform , and Local Governance . His career bridges engineering innovation and societal challenges, particularly in governance and policy.

Esam Abdel-Raheemمشاهده پروفایل

استاد

• Digital Signal Processing
• Biomedical Engineering
• Cognitive Radio Networks
• +۳ مورد دیگر

Dr. Esam Abdel-Raheem is a Professor in the Department of Electrical and Computer Engineering at the University of Windsor, Faculty of Engineering. His research focuses on digital signal processing, biomedical engineering, cognitive radio networks, and VLSI design. He holds a Ph.D. from the University of Victoria (1995) and is a Professional Engineer (P.Eng.) in Ontario and a Senior Member of IEEE. Education: B.Sc. Electrical Engineering, Ain Shams University (1984) M.Sc. Electrical Engineering, Ain Shams University (1989) Ph.D. Electrical Engineering, University of Victoria (1995) Research Interests: Dr. Abdel-Raheem’s work spans signal processing for communications, biomedical signal processing, and VLSI implementations. He has pioneered algorithms for cognitive radio networks and adaptive filtering. His recent studies leverage deep learning for medical diagnostics (e.g., lung nodule detection, Parkinson’s disease voice analysis) and cognitive radio spectrum sensing. Publications Trends: Recent work emphasizes biomedical applications (e.g., CT scan analysis, diabetic retinopathy detection) and machine learning integration in communications (e.g., federated learning for traffic crowdsourcing). His articles often bridge theoretical signal processing with practical implementations in hardware (e.g., FPGA-based filters). Awards/Grants: Not explicitly listed in the text, though his senior IEEE membership and prolific publications suggest sustained professional recognition. Lab/Teams: While not detailed, his research themes imply involvement in interdisciplinary teams focusing on biomedical engineering, telecommunications, and VLSI design.

Adrian Chanمشاهده پروفایل

استاد

• Non-invasive sensor systems
• Biomedical signal processing
• Biomedical image processing
• +۳ مورد دیگر

Adrian Chan is a Professor at Carleton University's Department of Systems and Computer Engineering, Faculty of Engineering and Design. He holds the title of Director of the Research and Education in Accessibility, Design, and Innovation (READi) program. His expertise spans biomedical engineering, signal processing, and accessibility technologies. Education: Ph.D. in Electrical Engineering (University of New Brunswick), M.A.Sc. in Electrical Engineering (University of Toronto), B.A.Sc. in Computer Engineering (University of Waterloo). Research focuses on non-invasive sensors, biomedical signal/image processing, machine learning, and accessibility solutions. Notable projects include the Abilities Living Laboratory and collaborations with healthcare institutions like The Ottawa Hospital. His work addresses challenges in neonatal transport safety, placental imaging for maternal health, and wearable medical devices. Publications highlight advancements in AI-driven ECG analysis, histopathology segmentation, and clinical monitoring systems. Over 150 students have been mentored, with many securing prestigious awards. Awards include the 2024 CMBES Fellowship, 2023 Carleton Research Achievement Award, and 2012 3M Teaching Fellowship. Grants include NSERC CREATE programs and CFI funding for the Abilities Living Laboratory. Leadership roles include interim Assistant Vice-President (Academic), Associate Dean (Graduate Programs), and Shad Valley Program Director. Active in community initiatives like the READi training program and accessibility advocacy.

Marcelo M. Wanderleyمشاهده پروفایل

استاد

• Music Technology
• Computer Music
• Digital Musical Instruments (DMIs)
• +۵ مورد دیگر

Marcelo M. Wanderley is a Professor and Director of the Centre for Interdisciplinary Research in Music Media and Technology (CIRMMT) at McGill University's Schulich School of Music. His academic roles include Area Coordinator for Music Technology and membership on the Executive Committee. He holds a PhD in acoustics, signal processing, and computer science from Université Pierre et Marie Curie (Paris VI). Wanderley's research focuses on novel interfaces for music performance, digital musical instruments (DMIs), and human-computer interaction. He has authored influential works such as New Digital Musical Instruments: Control and Interaction Beyond the Keyboard (2006) and pioneered research in gestural control of music. His work integrates engineering, computer science, and musicology to create innovative performance tools, including the T-Stick and Karlax instruments. He has held visiting professorships at Université de Bretagne Sud, Universidade Federal de Minas Gerais (Brazil), and the University of Mons (Belgium), where he was awarded prestigious chairs. Wanderley's awards include the Inria International Chair (2016–2020) and the Distinguished Visitor Award from the University of Auckland. His research has been widely cited in the International Conference on New Interfaces for Musical Expression (NIME), and he actively contributes to editorial boards (e.g., Computer Music Journal ) and academic leadership roles. Wanderley's lab, the Input Devices and Music Interaction Lab (IDMIL), develops open-source frameworks like Puara and Probatio for DMI design and mapping. Key research areas include haptic feedback systems, motion capture of musical performances, and accessibility in music technology. He emphasizes interdisciplinary collaboration, bridging engineering, art, and cognitive science to advance musical expression and performance practices.

Yusuf Altintasمشاهده پروفایل

استاد

• Machining Processes
• Computer Numerical Control (CNC)
• Machine Tool Dynamics
• +۵ مورد دیگر

Yusuf Altintas is a Professor in the Department of Mechanical Engineering at the University of British Columbia's Faculty of Applied Science, holding the NSERC–P&WC-Sandrik Coromant Industrial Research Chair and coordinating the Mechatronics Option. An internationally acclaimed scholar, he is a Fellow of 10 prestigious academies including the National Academy of Engineering (NAE), Royal Society of Canada (RSC), and ASME. His academic credentials include a Ph.D. from McMaster University, an Honorary Doctor of Engineering from the University of Stuttgart, and a Doctor of Technical Sciences from Budapest University of Technology and Economics. Professor Altintas's research pioneers the integration of physics-based modeling and data-driven approaches for machining systems. His work spans virtual high-performance machining simulation, machine tool dynamics, chatter stability prediction, and intelligent process control for CNC systems. Current projects focus on digital twin development for machining processes, spindle health diagnostics, ultrasonic vibration-assisted tooling, and adaptive damping systems for aerospace manufacturing applications. His methodologies bridge theoretical mechanics with industrial implementation in die/mold and aerospace sectors. Analysis of his 2022-2025 publications reveals dominant trends in physics-informed machine learning for spindle fault detection, topology-optimized tool design, and chatter avoidance in thin-walled component machining. Key thematic clusters include digital twin implementation (28% of recent work), dynamics modeling of multi-axis systems (35%), and intelligent monitoring algorithms (22%), with growing emphasis on anisotropic material machining and 3D printing process control. Georg Schlesinger Award (2016) NSERC Strategic Research Network in Virtual Machining Grant (2016) NSERC Synergy Award (2013) ASME Blackall Machine Tool and Gage Award (2013) Special Distinguished Scientist Award from Turkey's Scientific and Technical Research Council (2013) He directs the Manufacturing Automation Laboratory at UBC, leading an international research consortium on virtual machining systems supported by NSERC and industry partners including Sandvik Coromant and Pratt & Whitney Canada. His team develops real-time process monitoring frameworks and physics-based simulation tools that have been adopted in aerospace manufacturing for blade machining and die/mold production. The laboratory maintains advanced testbeds for five-axis machining dynamics, spindle health monitoring, and ultrasonic vibration-assisted tooling, serving as a hub for industry-academic collaboration in next-generation manufacturing technologies.