Mark Bocko is a Distinguished Professor of Electrical and Computer Engineering at the University of Rochester, affiliated with the Hajim School of Engineering & Applied Sciences. He holds roles as Director of the Center for Emerging and Innovative Sciences (CEIS) and Director of Audio & Music Engineering. He earned his PhD in Physics from the University of Rochester in 1984, focusing on gravitational wave detectors. His research spans audio signal processing, sensors, superconductivity, and quantum computing. Notable contributions include flat-panel loudspeaker development, non-contact ECG sensors, and quantum coherence studies in Josephson junctions. Research interests include audio and acoustic signal processing, computer audition, and sensor technologies. His work integrates interdisciplinary approaches, combining electrical engineering, physics, and computer science. Awards include the 2012 Goergen Award for Teaching and Mercer Brugler Distinguished Teaching Professor (2008–2011). Recent publications address modal crossover networks for loudspeakers, vibrational touch sensing, and room impulse response modeling. He has advised PhD students on topics like spatial audio rendering and musical vibrato analysis. His labs focus on advancing audio engineering and smart sensor systems through collaborative industry partnerships.
J. Edward Colgate is the Walter P. Murphy Professor of Mechanical Engineering and Director of the Human Augmentation via Dexterity (HAND) Engineering Research Center at Northwestern University's McCormick School of Engineering. He also holds the title of Breed Senior Professor of Design. His academic career includes leadership roles as founding co-Director of the Segal Design Institute and director of the Master of Science in Engineering Design and Innovation program. Colgate earned his Ph.D. (1988), S.M. (1986), and S.B. in Physics (1983) from the Massachusetts Institute of Technology. Colgate's research focuses on physical human-robot interaction with specialization in surface haptic interactive design and electroadhesion technology development. His work spans three interconnected domains: haptic interfaces (including wearable haptic arrays and Touchbot systems), robot dexterity through Shape-Based Remote Manipulation (SBRM) for overcoming communication delays, and high-speed electroadhesive actuators. The Northwestern Haptics Lab under his direction aims to create realistic virtual environments by merging these research vectors. His publications demonstrate consistent focus on tactile perception mechanisms, electroadhesion applications, and haptic rendering algorithms. Recent work explores texture playback fidelity, wearable electroadhesive arrays, robotic manipulation, and human-swarm control systems, reflecting interdisciplinary integration of mechanical engineering, materials science, and neuroscience principles. Awards: Elected to National Academy of Engineering (2021) for contributions to haptics, human-robot systems, and design education Inducted into National Academy of Inventors (2015) Educational initiatives include developing Northwestern's Design Thinking and Communication curriculum, establishing the Certificate in Engineering Design, and creating the Master of Science in Engineering Design and Innovation. He teaches ME 390: Introduction to System Dynamics using a flipped classroom model. Colgate directs the Northwestern Haptics Lab within the Center for Robotics and Biosystems, focusing on fundamental haptics research with applications in virtual reality, prosthetics, and human-assistive devices. The lab maintains active industry partnerships for technology transfer of haptic innovations.
Jihyun Lee is an Assistant Professor in the Department of Mechanical and Manufacturing Engineering at the Schulich School of Engineering, University of Calgary. She was awarded the Anna Boyksen Fellowship by the Technical University of Munich Institute for Advanced Study (TUM-IAS) in 2021, hosted by Prof. Michael Zäh. Doctorate in Mechanical Engineering from University of Michigan-Ann Arbor (2016) Prior post at Korea Institute of Machinery and Materials (2016-2019) Her research focuses on mechatronics, robotics, manufacturing automation, and control systems , with applications in machine tools, additive manufacturing, and precision measurement. She integrates artificial intelligence and optimization to enhance industrial automation. Recent publications highlight work on vibration control , sensor fusion , and flexible manufacturing systems . Her team explores dynamic modeling , nanocomposite sensors , and human-in-the-loop robotics for industrial and marine applications. 2020 Remote Teaching Award, Schulich Engineering 2020 Early Achievement Award, Association of Korean-Canadian Scientists and Engineers 2018 Best Achievement Award, KIMM She supervises doctoral and master’s students at the University of Calgary, emphasizing hands-on experience and MATLAB/Python simulation skills in her lab. Her work bridges quantum logic and industrial robotics through interdisciplinary collaborations.
Pelin Berik Giwa is a Lecturer in the Department of Mechanical and Aerospace Engineering at the University of Central Florida (UCF). She holds a doctorate in mechatronics engineering from Johannes Kepler University and a Diplom degree in mechanical engineering from Vienna University of Technology. Her postdoctoral research spanned California State University, North Carolina State University, and Virginia Tech, with visiting roles at UCLA and Loyola Marymount University. Education : Ph.D., Mechatronics Engineering, Johannes Kepler University Diplom, Mechanical Engineering, Vienna University of Technology Research Interests : Focuses on piezoelectric actuators, nanotechnology applications in aerospace, and vibration control in aerospace structures. Her work integrates experimental benchmarking, finite element simulations, and material characterization to advance smart materials and actuator designs. Article Trends : Her publications emphasize piezoelectric crystal actuation, shear-mode sensors, and lead-free materials. Key themes include torsional actuation, nonlinear response analysis, and material optimization for aerospace applications. Awards : Erwin Schrödinger Fellowship, Austrian Academy of Sciences Max Kade Fellowship Teaching & Advising : Instructs courses like Engineering Analysis – Dynamics and Modeling Methods in MAE. While no formal advisees are listed, her roles reflect mentorship in academic and postdoctoral settings.
Mustafa Yavuz is a Professor and Director of the Nano and Micro Systems Lab (NMSL) at the University of Waterloo, Canada, affiliated with Mechanical & Mechatronics Engineering, System Design Engineering, and Electrical & Computer Engineering. He holds cross-appointments in multiple departments and has been a faculty member since 2009. His research focuses on Opto-Nano/MEMS devices, quantum electronic solids, graphene, and superconductors. Yavuz has supervised over 28 graduate students and postdoctoral fellows, leading to impactful contributions in sensors, nanomaterials, and energy harvesting. He has authored/co-authored numerous articles and holds patents in MEMS and nanotechnology. His awards include the University of Waterloo Research Excellence Award (2018) and international fellowships from MINATEC and JSPS. Education: Ph.D. Materials Engineering (University of Wollongong, 1996) Ph.D. Applied Physics (University of Wollongong, 1995) M.Sc. Materials Engineering (Middle East Technical University, 1991) B.Sc. Materials Engineering (Middle East Technical University, 1989) Research Interests: Yavuz specializes in advanced materials and MEMS/NEMS technologies, including opto-nano-MEMS devices, quantum electronic solids (superconductors, graphene), and functional nanomaterials for sensors and energy systems. His work integrates fabrication, packaging, and reliability testing of nanoscale devices for applications in photonics, biomedical sensing, and environmental monitoring. Recent trends in his articles highlight innovations in resonant MEMS mirrors, graphene-based biosensors, and laser-functionalized 2D materials. Scientific Awards: MINATEC Fellowship (2019) Waterloo Engineering Research Excellence Award (2018) International Nanoarchitectonics Fellowship (2017) JSPS Fellowship (2007) Advising & Grants: Yavuz has supervised 26 doctoral students and 28 postdoctoral researchers. His labs, including the NMSL and BioGraph Sense Inc., focus on MEMS packaging, nanojoining, and plasmonic biosensors. He has led projects funded by NSERC, CFI, and industry collaborations with companies like Apple, Samsung, and Smarter Alloys. Labs/Teams: Director of the Nano and Micro Systems Lab (NMSL), co-founder of BioGraph Sense Inc., and collaborator in the Waterloo Institute for Nanotechnology (WIN). His research group develops cutting-edge nanoscale devices with applications in healthcare, energy, and environmental sensing.
Professor Sangbae Kim is the Jerry McAfee (1940) Professor in Engineering at the Massachusetts Institute of Technology (MIT), School of Engineering, Department of Mechanical Engineering. His research focuses on bio-inspired robotics, extracting principles from animal biomechanics to develop high-performance robotic systems. Education: B.S. from Yonsei University (2001), M.S. (2004) and Ph.D. (2008) from Stanford University. Research Interests: Bio-inspired Robotics, Robotic Actuators, Locomotion Dynamics, Composite Sensor Fabrication, and Minimally Invasive Surgical Robotics. His notable achievements include the MIT Cheetah robot capable of 13mph outdoor running and autonomous obstacle jumping, and Stickybot, a climbing robot featured in TIME's Best Inventions (2006). Recent publications emphasize soft robotics, energy-efficient legged locomotion, and bio-inspired actuator design. Kim has received prestigious awards including the NSF CAREER Award (2014), DARPA Young Faculty Award (2013), and Ruth and Joel Spira Award for Distinguished Teaching (2015). Scientific Awards: NSF CAREER (2014), DARPA YFA (2013), TIME Best Invention (2006), multiple best paper awards. Professional Service: Associate Editor roles, NSF review panels, and leadership in IEEE and ASME organizations.
Corrado De Sio is a Fixed-term Researcher at the Department of Control and Computer Science (DAUIN) , Politecnico di Torino , affiliated with the College of Computer, Film, and Mechatronics Engineering . His academic roles include course instruction and collaboration for Reconfigurable Computing , High Performance Computing (HPC) , and Operating Systems for High-Performance Supercomputers across multiple academic years (2020-2025). Research Interests focus on: Reliability of reconfigurable systems and FPGAs under radiation effects Hardware-software co-design for fault tolerance Embedded systems in aerospace and safety-critical applications Machine learning acceleration on reconfigurable hardware Radiation effects on real-time operating systems and CNN implementations Recent publications address: 2025: Selective hardening of RISCV soft-processors for space applications 2025: Real-time 'signal for help' gesture recognition systems 2024: Reliability analysis of RISC-V processors and CNN placement algorithms 2023: Fault tolerance in FPGA-based CNNs and radiation effects on RTOS Patents include: PyXEL - Python Toolkit for Reconfigurable Hardware Surveillance Software for Real-Time Violence Detection Academic Supervision : Co-supervisor for PhD candidate Arash Amini Bardpareh in Computer and Systems Engineering .
Oya Celiktutan is a Reader (Associate Professor) at King’s College London in the Department of Engineering, leading the Social AI & Robotics (SAIR) Lab within the Centre for Robotics Research. She holds a BSc in Electronics Engineering from Uludag University, and an MSc and PhD in Electrical and Electronics Engineering from Bogazici University, Turkey. Her doctoral work included a visiting research period at the National Institute of Applied Sciences in Lyon, France. She has held postdoctoral positions at Queen Mary University London, the University of Cambridge, and Imperial College London before joining King’s College in 2018. Her research focuses on multimodal machine learning for autonomous agents, addressing challenges in human-robot interaction, social awareness, and navigation. Key areas include human behavior analysis, generative models, and continual learning. Her work is supported by EPSRC, The Royal Society, EU Horizon, and industry partners like Toyota and NVIDIA. Notable awards include the EPSRC New Investigator Award (2021) and a Best Paper Award at IEEE Ro-Man 2022. Dr. Celiktutan’s lab explores socially assistive robotics, extended reality systems, and ethical AI. Recent projects include the LISI initiative to enable robots to learn social interactions from human-human data and the CL-HRI project advancing continual learning in human-centric robotics. Her research has led to datasets like MHHRI and RICA, and collaborations with companies like SoftBank Robotics. She teaches modules on Sensing and Perception, and Sensors and Actuators, emphasizing practical applications in robotics and mechatronics. Current research interests span socially-aware navigation, algorithmic fairness, and multimodal data fusion for robotics in healthcare and urban environments.
Svitlana Rogovchenko is a Professor at the Department of Engineering Sciences, University of Agder, Norway. Her academic work bridges pure mathematical research in differential equations with innovative pedagogical approaches in engineering and interdisciplinary education. Educational Background: Doctor of Philosophy in Differential Equations (1988), Institute of Mathematics, National Academy of Sciences, Kyiv, Ukraine Master of Science in Mathematics (1983), Kyiv State University, Ukraine Research Interests: Qualitative theory of ordinary and impulsive differential equations, asymptotic methods in nonlinear mechanics, mathematical modeling, and the intersection of mathematics education with engineering and biology curricula. She focuses on conceptual understanding, pedagogical challenges, and commognitive conflicts in learning differential equations. Recent Publications Trends: Her work spans mathematical modeling of vehicle crashworthiness, interdisciplinary education for biologists and engineers, and pedagogical innovations in ordinary differential equations. Articles emphasize assessment design, group work tensions, and bridging mathematical theory with applied contexts.
Dr. G.K. Knopf is a Professor in the Department of Mechanical & Materials Engineering at Western University, Canada. He holds a Ph.D. (1991), M.Sc. (1987), and B.E. (1984) from the University of Saskatchewan. His work bridges product design, advanced manufacturing, and bio-inspired technologies. Research Focus: Dr. Knopf’s research spans 3D shape reconstruction , laser microfabrication , micro-optics , and bioelectronic imaging arrays . Recent projects emphasize light-driven actuators , flexible electronics , and graphene-based inks for printing circuits on unconventional substrates like silk and paper. Publications: Over 150 peer-reviewed works, including two edited CRC Press volumes ( Smart Biosensor Technology , Optical Nano and Micro Actuator Technology ). Key contributions involve non-lithographic fabrication , bacteriorhodopsin photodetectors , and self-organizing feature maps for data visualization. Awards/Patents: Co-inventor of two U.S. patents (6,542,249 for 3D surface measurement; 7,573,024 for bioelectronic imaging arrays). Teaching: Leads graduate courses in Medical Device Design and Optomechatronic Systems , as well as undergraduate Mechatronics and Medical Device Development courses.
Aaron M. Dollar is the Frederick W. Beinecke Professor of Mechanical Engineering at Yale University, affiliated with the Yale Grab Lab. His research focuses on robotics, mechatronics, robotic grasping, and prosthetics, emphasizing adaptive mechanisms and human-robot interaction. He holds a PhD from Harvard University (2008) and degrees from UMass Amherst. Key research areas include dexterous manipulation, underactuated mechanisms, and assistive devices. His work bridges theory and practical applications, with contributions to prosthetic hands, robotic hands, and modular robotics systems. Recipient of prestigious awards: TR35 Innovator (2010), NSF CAREER Award (2010), DARPA Young Faculty Award (2013), and Air Force Young Investigator Award (2011). Developed the Yale MyoAdapt Hand, a single-actuator prosthetic with high functionality. Pioneered methods in real-to-sim transfer, modular lattice printing, and energy-aware robotic exploration. His lab, the Yale Grab Lab, explores robotics, prosthetics, and human motion analysis. Recent projects include autonomous calibration systems (ARC-Calib) and low-cost robotic hardware (RB5 Explorer).
Zhenhong Li is a Lecturer in Robotics and Control at the University of Manchester, holding an EPSRC Fellowship in physical human-robot interaction. He earned his B.Eng. from Huazhong University of Science and Technology (2013), and M.Sc. and Ph.D. in Control Engineering from the University of Manchester (2014 and 2019). Before joining Manchester in 2023, he was a Research Fellow in Rehabilitation Robotics at the University of Leeds (2019–2023). His research focuses on control technologies for human-robot systems, with applications in healthcare and industry. Key areas include physical human-robot interaction for rehabilitation, brain-computer interfaces, and neuromusculoskeletal modeling. He leads the Neurorobotics Lab (NRL) at Manchester and collaborates with healthcare professionals, industries, and designers via EPSRC/STFC/Wellcome Trust funding. Notable achievements include the 2019 Best Paper Award for Unmanned Systems and the 2020 EPS International Academic Pump-priming Award. In 2025, he was elected as a Senior Member of the IEEE. He actively organizes conferences and special issues, including the 2025 IEEE UK Robotics Conference and a Frontiers special issue on intelligent rehabilitation technology. Dr. Li supervises PhD candidates in robotics and control, emphasizing interdisciplinary approaches to human-robot interaction. His lab develops cutting-edge technologies like assistive exoskeletons and adaptive control systems for healthcare and industrial applications.
Buyung Kosasih is a Professor in the School of Mechanical, Materials, Mechatronic and Biomedical Engineering at the University of Wollongong. He has held this position since 2000 and focuses on teaching and research in mechanical engineering, including Machine Dynamics, Finite Element Methods, and Renewable Energy Technology. His research spans fluid dynamics in industrial processes, renewable energy systems, and aqueous lubrication. Key projects include 3D-printed surfboard fin optimization and steel coating dynamics. Research interests emphasize experimental and computational fluid dynamics, particularly in renewable energy turbines and tribological systems. Notable awards include the 2013 Outstanding Contribution to Teaching and Learning Award. He has supervised numerous students and led over 20 funded projects, including ARC grants for steel innovation and renewable energy. Collaborative work includes the Steel Research Hub and HVAC/cool roof efficiency studies.
James Tung is an Associate Professor at the University of Waterloo’s Faculty of Engineering, Department of Mechanical and Mechatronics Engineering. His research focuses on assistive technology, rehabilitation engineering, and mobility solutions for individuals with disabilities. He leads the Neural and Rehabilitation Engineering (NRE) Lab, which develops wearable sensors, robotics, and machine learning tools to enhance mobility and monitor motor rehabilitation. He teaches courses including BME 355 (Physiological Systems Modelling), BME 540 (Neural and Rehabilitation Engineering), and ME/MTE engineering modules. The lab collaborates with clinical and industry partners to translate research into practical solutions, addressing real-world mobility challenges and aging demographics. His research spans real-world gait analysis, fall risk assessment, and prosthetic design, with a focus on pediatric neurodevelopmental disorders and elderly mobility. The NRE Lab emphasizes interdisciplinary work, combining biomechanics, robotics, and data science to improve healthcare outcomes. Lab Alumni: Includes researchers like Robin Murdock (Myant Inc.), Andrew Hart, and Raj Senthilkumar, contributing to prosthetics and gait analysis. Partnerships: Engages clinical and industry stakeholders for knowledge translation and commercialization. Current projects include developing smart rollators, biofeedback prosthetics, and sensor-based assessment tools to address mobility limitations in aging populations and individuals with disabilities.
Joachim Weickert is a Professor of Mathematics and Computer Science at Saarland University where he heads the Mathematical Image Analysis Group since 2001. He received his diploma and Ph.D. in mathematics from the University of Kaiserslautern (1991, 1996), and a habilitation degree in computer science from the University of Mannheim (2001). Prior to his current position, he worked as a research assistant at the University of Kaiserslautern, as a post-doctoral researcher at the universities of Utrecht and Copenhagen, and as an assistant professor at the University of Mannheim. His research focuses on image processing, computer vision, and scientific computing, with special emphasis on techniques based on partial differential equations, variational principles, wavelets, morphological and nonlocal methods, as well as neuroexplicit approaches. He has developed mathematical models and efficient numerical algorithms for image restoration, enhancement, segmentation, compression, optic flow computation, stereo reconstruction, shape from shading, and signal processing methods for tensor fields. These ideas have been successfully applied in industry, biomedical image analysis, and other fields. Analysis of his recent publications reveals a strong trend toward combining traditional PDE-based methods with modern deep learning approaches, particularly in the areas of image inpainting and compression. His work increasingly explores the connections between numerical algorithms for partial differential equations and neural network architectures, demonstrating how mathematical foundations can inform cutting-edge AI techniques while maintaining strong theoretical guarantees. Gottfried Wilhelm Leibniz Prize (2010), considered the most important research award in Germany ERC Advanced Grant (2017) for "Inpainting-based Compression of Visual Data" Elected member of Academia Europaea - The Academy of Europe Jan Koenderink Prize for Fundamental Contributions in Computer Vision (2014) Multiple DAGM Prizes and Best Paper Awards throughout his career AAIA Fellow (2021) and Highly Ranked Scholar (2024) distinctions Professor Weickert has supervised over 250 bachelor's and master's theses and initiated the Master Programme in Visual Computing at Saarland University, the first of its kind in Germany taught in English. He has established numerous interdisciplinary collaborations with colleagues from medicine, bioinformatics, pharmacy, physics, mechatronics, and mechanical engineering. As Principal Investigator for Visual Computing within the Multimodal Computing and Interaction Cluster of Excellence, and former dean of the Faculty of Mathematics and Computer Science (2008-2010), he has played a significant leadership role in advancing visual computing research and education. He heads the Mathematical Image Analysis Group, which has been at the forefront of developing mathematical methods for image analysis. The group maintains strong connections with both theoretical mathematics and practical applications, bridging the gap between fundamental research and real-world implementation across various domains including medical imaging, industrial inspection, and multimedia processing.
