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MA DongView profile

Assistant Professor

• Mobile Computing
• Wearable-Based Human Sensing Systems
• Health Monitoring
• +3 more

MA Dong is an Assistant Professor at the School of Computing and Information Systems (SCIS) at Singapore Management University (SMU). He holds a PhD from the University of New South Wales (2020), and was a postdoctoral researcher at the University of Cambridge. His research focuses on mobile computing, wearable-based human sensing systems, and health monitoring using embedded machine learning. He is also a visiting researcher at the University of Cambridge since April 2025 and will join as an Associate Professor there in 2026. Education: PhD (UNSW), MEng and BEng (Central South University). Research Interests: Wearable systems for health monitoring (e.g., respiratory rate tracking, gait analysis), robust physiological sensing, tiny machine learning on embedded devices, and human-computer interaction through earables. His work emphasizes practical implementations of wearable technology for real-world scenarios, such as smart earbuds for authentication, health tracking, and activity sensing. Publications: Over 50+ peer-reviewed articles in top venues like MobiCom, PerCom, CHI, and Nature journals. Key topics include earable technology, ECG-text multimodal learning, and energy-efficient sensing systems. Awards: Google South Asia Research Award (2024), Mark Weiser Best Paper Awards (2024, 2025), and EPFL Engineering Ph.D. Summit recognition. Students: Advising PhD candidates Xiao Ma, PHAM Hung Manh, and Changshuo Hu. Also hosts visiting scholars from Shandong University and Beijing Institute of Technology.

• Systems Engineering
• Automation Engineering
• Intelligent Instrumentation
• +7 more

Francisco Javier Pérez Castelo is a Professor in the Department of Industrial Engineering at Universidade da Coruña (UDC), specializing in Systems and Automation Engineering. He is affiliated with the Escola Técnica Superior de Enxeñaría and leads research in the Cyber Science and Technology Research Group. His research focuses on Intelligent Instrumentation, Industrial Internet of Things (IIOT), Knowledge Engineering, Expert Systems, and Intelligent Systems for modeling, optimization, and control . His work bridges theoretical control systems with practical applications in marine engineering, power electronics, and industrial automation. His research has significant applications in ship automation, marine systems control, and industrial robotics. Pérez Castelo's publication record shows a consistent trajectory in control systems and automation, with recent work emphasizing intelligent instrumentation, IIOT applications, neural networks, and expert systems in marine environments. His research has evolved from fundamental control theory to applied intelligent systems with strong industry connections. Patent: Universidade da Coruña (UDC) - 22/03/2013 request date, 11/08/2015 grant date Patent: Universidade da Coruña (UDC) - 01/10/2010 request date, 26/12/2013 grant date Patent: Universidade da Coruña (UDC) - 04/02/2008 request date, 29/03/2011 grant date Patent: Universidade da Coruña (UDC) - 19/07/2005 request date, 20/05/2009 grant date He has supervised numerous bachelor's and master's theses on topics including autonomous vehicles for ship maintenance, marine stability optimization, digital camera stabilization systems, and solar-powered LED lighting. His research has been supported by various funding entities including EMALCSA, CONSELLERIA DE EDUCACIÓN, Instituto Nacional de Ciberseguridad, and Ministerio de Ciencia e Innovación. Pérez Castelo actively collaborates with researchers across Spain and internationally, with projects spanning from 1995 to the present, demonstrating sustained research productivity. He teaches across multiple programs including the Master's Degree in Industrial Informatics and Robotics, Degree in Naval Engineering, and Degree in Marine Technologies, covering subjects such as Industrial Drives, Automation and Control Systems, Ship Installation Automation, and Advanced Control of Marine Systems. His teaching laboratory is located in the Laboratorio de Automática (ETSNM).

• Digital Circuits and Systems
• Energy-Efficient Circuits and Systems
• Embedded Systems
• +7 more

Massimo Poncino is a Full Professor at the Department of Control and Computer Science (DAUIN) within the Faculty of Engineering at Politecnico di Torino. He serves as Scientific Advisor for the STMicroelectronics partnership and coordinates basic engineering subjects. A Senior Member of IEEE since 2012 and Fellow since 2012, he has served on editorial boards for IEEE Transactions on Computer-Aided Design, IEEE Design & Test of Computers, and ACM Transactions on Design Automation. Education: Laurea in Electronic Engineering (1989) and PhD in Computer and Systems Engineering (1993) from Politecnico di Torino Academic Career: Visiting Scientist University of Colorado (1993-1994), Researcher at Politecnico di Torino (1995-2001), Associate Professor at University of Verona (2001-2004), Full Professor at Politecnico di Torino (2006-present) His research focuses on energy-efficient digital systems , including design automation of SoCs, hardware-aware AI, battery management, cyber-physical systems, and embedded systems. Recent publications highlight advancements in digital twins for batteries , low-power neural network deployment , and IoT privacy . Scientific Awards: Recognition of Service Award - ACM (2013) Certificate of Appreciation - IEEE Circuits and Systems Society (2006, 2008, 2009) IEEE Fellow (2012-) Research Involvement: EU H2020, VI/VII Framework Programs evaluator Scientific Director for projects: Approxim@ction, EMBAI, DISLO-MAN, DAMASCO Member of EDA research group Teaching: Course director for Energy Management for IoT (2019-2025) Lecturer for Computer Science courses (2003-2025)

• Engineering Education
• Self-efficacy
• Team Interactions
• +6 more

Dr. Senay Purzer is a Professor of Engineering Education at Purdue University's School of Engineering Education in West Lafayette, Indiana. Her office is located in ARMS 1331 with a research lab in WANG 3583. Her educational background shows she has established herself as a prominent researcher in engineering education, with particular expertise in understanding how students learn engineering concepts and develop design skills. Dr. Purzer's research focuses on the relationship between self-efficacy beliefs, team interactions, and student achievement; student interactions in diverse teams; the role of group argumentation in engineering design; and P-12 engineering education. Her recent publications (2023-2025) demonstrate a growing emphasis on ethical considerations in engineering design, data management, and socially transformative approaches to engineering education that address diversity, equity, and sustainability concerns. Her scholarly work spans numerous areas including design reasoning, innovation processes, assessment methodologies, and the integration of engineering concepts into K-12 education. She has published extensively in journals such as the Journal of Pre-College Engineering Education Research (J-PEER), where she has contributed annual reports and conceptual frameworks. Dr. Purzer actively collaborates with other researchers in the field, particularly with colleagues like Quintana on projects related to semantic fluency in design reasoning and argumentation processes. She is currently recruiting graduate students to work on research projects focused on engineering teamwork, diversity in engineering teams, and argumentation in engineering design.

• Advanced Device Technologies
• Materials Science
• Nanoengineering
• +4 more

Olin Hartin serves as a Professor of Practice in Arizona State University's School of Electrical, Computer and Energy Engineering, leveraging over 30 years of Fortune 500 industry experience in science and technology. Based at the Tempe campus (GWC 340, Mailcode 5706), he maintains an active research profile with 25 patents and more than 60 scholarly publications. His academic credentials include: Ph.D. in Electrical Engineering M.S. in Electrical Engineering M.S. in Physics B.S. in Physics Hartin's research centers on advanced device technologies and materials, with demonstrated expertise in nanoengineering, RF circuit design, and semiconductor physics. His work bridges theoretical modeling with practical fabrication challenges, particularly in gallium nitride transistor development and electromagnetic compatibility. Recent projects address thermal management in high-power devices and noise isolation techniques for mixed-signal integrated circuits, driven by industry applications in wireless infrastructure. Analysis of his publication history reveals sustained focus on GaN HEMTs since 2010, with increasing emphasis on machine learning applications for FPGA deployment. His work consistently targets real-world implementation challenges, reflecting his industry background through patents in antenna design, ESD protection, and RF component optimization. Professional recognition includes: Senior Member of IEEE In teaching, Hartin supervises senior design laboratories (EEE 488/489) and instructs core courses including Hardware Design Language/Programming Logic (EEE 333), Circuits II (EEE 334), and Machine Learning with FPGA Deployment (EEE 405). His industry perspective enriches curriculum development, though specific grant funding details are not publicly documented. While no dedicated research lab is specified, his patent portfolio indicates ongoing collaboration with semiconductor industry partners.

Simon JánosView profile

Associate Professor

• Internet of Things
• Mobile Robotics
• Wireless Sensor Networks
• +5 more

Dr. habil. Simon János PhD is an Associate Professor at the University of Szeged's Faculty of Engineering, Institute of Technology. Born on July 27, 1980, he maintains his office at 6724 Szeged, Moszkvai krt. 9. Room F9, with contact number +36-62-546-575. His educational background includes IT engineering and electrical engineering from Technical College of Subotica (1999-2005), Certified Computer Engineering from University of Novi Sad (2005-2008), PhD in Engineering from University of Osijek (2008-2014), and habilitation from Óbuda University Doctoral School of Security Sciences (2020). English (intermediate, complex) Serbian (advanced, complex) Dr. Simon's research focuses on design and programming of Internet of Things environments, hardware and software development of mobile robots and wireless sensor networks, and analysis of Industry 4.0 case studies. His teaching portfolio includes Computer Modeling, Simulation courses, Microcontrollers, Graphical Programming at BSc level, and Real-time systems, Autonomous and intelligent robots at MSc level. He serves as Associate Editor for Analecta Technica Szegedinensia and is a member of the Higher Education Management Education Methodology Association (FIOM). His international experience includes CEEPUS mobility to Timisoara, Erasmus mobility to multiple Romanian cities, and participation in IoTTech Expo Global in London.

Taekwang JangView profile

Associate Professor

• Analog and Mixed-Signal Circuits
• Energy-Efficient Systems
• Wireless Sensor Networks
• +3 more

Prof. Taekwang Jang is an Associate Professor at the Department of Information Technology and Electrical Engineering, ETH Zürich. He leads the Energy Efficient Circuits and IoT Systems Group, focusing on analog and mixed-signal circuits for energy-constrained applications such as wireless sensor nodes and biomedical electronics. His research includes sensor interfaces, energy harvesters, power converters, and communication systems. He holds 15 patents and has authored over 80 peer-reviewed publications. Key awards include the 2024 IEEE Solid-State Circuits Society New Frontier Award and the SNSF Starting Grant. Educations: B.S. and M.S. in Electrical Engineering, KAIST (2006, 2008) Ph.D. in Electrical Engineering, University of Michigan (2017) Affiliations: Chair of IEEE Solid-State Circuits Society, Switzerland Chapter Associate Editor for Journal of Solid-State Circuits (JSSC) Research Interests: His work spans energy-efficient integrated circuits, biomedical interfaces, and IoT systems. Notable contributions include low-power keyword spotting ICs, ultra-low-noise amplifiers, and neural stimulation systems. He emphasizes practical applications in healthcare and wearable devices. Awards: 2024 IEEE Solid-State Circuits Society Distinguished Lecturer 2022 IEEE ISSCC Jan Van Vessem Award 2009 IEEE CAS Guillemin-Cauer Best Paper Award Advising & Grants: Supervises a team of researchers and has secured grants including the SNSF Starting Grant. His lab collaborates with institutions like the Competence Center for Rehabilitation Engineering and Science. Labs & Teams: Leads the Energy-Efficient Circuits and Intelligent Systems group at ETH Zurich, focusing on interdisciplinary projects at the intersection of circuits, systems, and biomedical engineering.

Stefano GregoriView profile

Professor

• Computer Engineering
• Integrated Circuit Design
• Analog and Mixed-Signal Systems
• +7 more

Stefano Gregori is a Professor at the University of Guelph's School of Engineering. He specializes in analog and mixed-signal integrated circuit design, with a focus on low-power systems, sensor networks, and microsystem integration. His research involves collaborations with industry leaders like STMicroelectronics and TSMC, emphasizing practical applications in IoT, energy efficiency, and biomedical devices. He holds a PhD and is a Professional Engineer (PEng). His work bridges theoretical design and real-world applications, such as secure cryptographic circuits and sustainable materials for biomedical composites. He actively supervises graduate students and has mentored numerous scholars, many of whom now work in leading tech companies like Qualcomm and Thales. Gregori's funding sources include NSERC, CMC Microsystems, and the Ontario Centres of Excellence. He emphasizes ethics in engineering, advocating for safety and environmental responsibility. His lab, located in Richards Building Room 3521, focuses on cutting-edge projects like energy-efficient audio amplifiers and blockchain-based IoT security.

• Electronic Design Automation (EDA)
• Computer Architecture
• Embedded Systems
• +5 more

Prof. Wolfgang Ecker is a Professor at the Technical University of Munich (TUM), affiliated with the Chair of Design Automation within the TUM School of Computation, Information and Technology . His research focuses on Electronic Design Automation (EDA), RISC-V processor architectures, and hardware-software co-design. He leads projects advancing EDA tools for embedded systems, neural network acceleration, and formal verification methodologies. Ecker's work bridges machine learning techniques with traditional EDA challenges, addressing topics like energy-efficient AI inference and automated documentation generation. His contributions span compiler optimization, FPGA implementations, and fault analysis in digital systems. Recent research highlights include contributions to the TRISTAN project for RISC-V ecosystem development, model-driven architecture frameworks, and AI-driven timing analysis. He actively collaborates on open-source EDA tools and explores Rust-based embedded systems development. Ecker’s lab emphasizes practical applications in edge computing and automotive microcontroller safety, with a strong emphasis on interdisciplinary collaboration across TUM’s CIT School. His publications (15 most recent listed) reflect a focus on EDA tool innovation, processor design, and leveraging machine learning for hardware optimization. While no specific awards are mentioned, his involvement in ERC-funded projects and leadership in international collaborations underscores his academic impact.

Manuel Jesus Espinosa GaviraView profile

Researcher

• Power Quality Analysis
• Wireless Sensor Networks
• Smart Grid Technologies
• +3 more

Manuel Jesus Espinosa Gavira is a researcher at the Department of Automation, Electronics, Architecture and Computer Networks Engineering at the University of Cádiz, Spain. He is affiliated with the TIC168 Computational Instrumentation and Industrial Electronics research group under the Information and Communication Technologies PAIDI area. Research Focus: His work centers on power quality analysis, wireless sensor networks, and smart grid technologies. Key contributions include developing instrumentation systems for voltage supply characterization, cloud-induced photovoltaic transient analysis, and synchronized sensor networks for industrial applications. His PhD thesis (2023) explored sensor networks for short-term solar prediction in microgrids and smart cities. Publications Trends: Recent work focuses on higher-order statistics (HOS) for power quality monitoring, photovoltaic plant optimization using weather forecasts, and frequency domain analysis for grid stability. These publications reflect expertise in computational instrumentation, renewable energy integration, and real-time monitoring systems.

David HovemeyerView profile

Academic

• Static Analysis
• Systems Software
• Computer Science Education
• +3 more

David Hovemeyer is an Associate Teaching Professor at the Whiting School of Engineering, Johns Hopkins University . He holds a PhD (2005) and MS (2001) in Computer Science from the University of Maryland and a BA (1994) from Earlham College. Prior to joining JHU in 2019, he taught at Vassar College and York College of Pennsylvania. Education : PhD, MS, and BA in Computer Science Research : Focuses on static analysis , systems software , and computer science education Projects : FindBugs, CloudCoder, ProgSnap2, FunWithSound His recent work includes frameworks for declarative autograders , formats for programming process data , and tools for educational software development . He has been recognized with Excellence in Teaching Awards and contributes to open-source educational platforms like GitHub. Scientific Awards : 2024 Whiting School Teaching, Advising, and Mentoring Award Excellence in Teaching Award (multiple years) David maintains an active role in the academic community through peer instruction , programming contests, and recommendation letter advising . He also develops tools like FreePoll and Declarative Autograder Framework to enhance teaching efficiency.

Roman Franz FroschauerView profile

Professor

• Software Engineering for Intelligent Automation Systems
• Human-Robot Interaction
• Control Systems
• +7 more

Roman Franz Froschauer is a Professor of Production Informatics at the Upper Austria University of Applied Sciences, Research Center Wels. Since 2018, he has served as Director of Studies for the Master's program in Robotic Systems Engineering and leads the Smart Automation & Robotics research group. His career spans academic and industrial roles, including senior software development and project management at AlpinaTec Technical Products GmbH (2010-2016). Education: Ph.D. in Computer Science (2010) from Johannes Kepler University Linz; Master's in Industrial Informatics (2005) from Upper Austria University of Applied Sciences. Research Areas: Software engineering for intelligent automation systems, human-robot interaction (HRI), control systems, and applications of IEC 61499 standards. His work focuses on proactive collaboration, trajectory planning, and user-centered design for assistive robots in office and industrial settings. Scientific Activities: Active in peer-review, conference organization, and technology development. Projects include VRoboCoop (human-robot trust), MARIE (office robotics), and Autility (automated utility vehicles). Key Contributions: Frameworks for modular manufacturing (PlugBot), skill-based engineering, and intralogistics automation (ATLAS).

Oscar CasasView profile

Associate Professor

• Electronic Instrumentation
• Biomedical Engineering
• Sensor Interfaces
• +4 more

Dr. Jaime Oscar Casas is an Associate Professor of Electronic Engineering at the Universitat Politècnica de Catalunya (UPC), affiliated with the School of Telecommunications and Aerospace Engineering in Castelldefels (EETAC) and the Department of Electronic Engineering. He has held this position since receiving his Doctor Ingeniero de Telecomunicación degree from UPC in 1998, following his 1994 Ingeniero de Telecomunicación degree from the same institution. His research focuses on electronic instrumentation , bioimpedance sensors , and noninvasive physiological measurement systems . He is a key member of UPC's ISI Research Group (Instrumentation, Sensors & Interfaces) and the AGROTECH-UPC Agrofood Technology Research Center . His work bridges biomedical engineering, wearable technology, and precision agriculture, with over 338 documented research activities including articles, patents, and grants. Notable contributions include innovative systems for ECG monitoring, impedance plethysmography, and noninvasive cardiovascular diagnostics. He has led projects funded by EU Horizon 2020, Spanish Ministry of Science, and Catalan Government programs. Awards include the Women in TIC Award 2019 and the Hemav Foundation Awards . He advises engineering students on real-time signal processing and wearable device development. His lab develops low-power medical sensors, smart agricultural monitoring tools, and systems for human-motion analysis with over 70 indexed journal articles and 106 conference presentations. He collaborates with industry partners on projects like the 6G-OpenLab and eSMILE initiative for assistive technologies.

• Pervasive Sensing
• Tiny Machine Learning (TinyML)
• Edge AI
• +7 more

Prof. Eiman Kanjo is a Professor of Pervasive Sensing & TinyML and Head of the Smart Sensing Lab at Nottingham Trent University. She leads the Smart Nottingham and Smart Campus initiatives, focusing on impactful applications of mobile sensing, wearable tech, and edge AI. Her work bridges academia, industry, and community, emphasizing privacy-preserving AI for mental health, environmental monitoring, and social prescribing. Education: PhD in Computer Science (2005), University of Abertay Dundee. Formerly a Research Associate at the University of Cambridge and researcher at the University of Nottingham’s Mixed Reality Lab. Collaborates with organizations like the tinyML Foundation, Health Data Research UK (HDRUK), and the Alan Turing Institute. Research Interests : Pervasive computing, TinyML, Edge AI, wearable devices, environmental sensing, mental health technologies, and community-driven solutions for urban wellbeing. She pioneered early mobile sensing systems like NoiseSPY (2010) and MobSens (2009). Key Projects : 5G Connected Forest (£10m DCMS grant) : Smart environmental monitoring in Sherwood Forest. TagWithMe : AI-driven proximity-based games for community wellbeing. EPSRC Green+ Network : Tech for healthier environments. Awards & Recognition : Top 50 Women in Engineering (2023). Outstanding Educator of the Year Award (EDGE AI Foundation, 2023). 2021 Vice-Chancellor’s Outstanding Research Team Award (Smart Sensing Lab). Grants & Collaborations : Over £10m in funding from EPSRC, InnovateUK, MOD, and DEFRA. Partners include Nottingham City Council, tinyML Foundation, Health Data Research UK, and industry stakeholders. Labs & Initiatives : Leads the Smart Sensing Lab , developing technologies for Green Social Prescribing at Rufford Country Park and Highbury Mental Health Hospital.

Mohamed AtiaView profile

Associate Professor

• Sensor Fusion
• Autonomous Systems
• Embedded Systems
• +12 more

Mohamed Atia is an Associate Professor in the Department of Systems and Computer Engineering at Carleton University's Faculty of Engineering and Design. He conducts research in sensor fusion for autonomous systems, including robotics, autonomous vehicles, and the Internet of Things, with an emphasis on real-time embedded implementation. PhD, Electrical and Computer Engineering, Queen’s University (2013) M.Sc., Computer Systems, Ain Shams University (2006) B.S., Computer Systems, Ain Shams University (2000) His research focuses on sensor fusion , integrating data from heterogeneous sensors such as GNSS, IMU, Vision, Radar, and LiDAR under real-time constraints on embedded platforms like FPGAs and microcontrollers. He applies advanced signal processing, estimation theory, machine learning, and AI to solve challenges in state estimation, observability, fault tolerance, and concurrency management. Dr. Atia’s work has applications in intelligent vehicles, indoor navigation, mobile robotics, smart buildings, medical devices, and remote sensing . He leads a research lab focused on embedded multi-sensor systems, where students develop practical solutions for autonomous navigation and SLAM. His teaching emphasizes hands-on learning through labs and projects. He teaches undergraduate courses in computer systems, embedded systems, and signal processing, and a graduate course (SYSC 5807) on Advanced Topics in Computer Systems, specifically Sensor Fusion Systems . Scientific Awards: Alberta Innovate Association Award (2011) IEEE Excellence in PhD Research (2013) Mitacs Elevate Industrial Postdoc Award (2014) NSERC PDF Award (2015) Queen’s University Teaching Award (2016) Dr. Atia has advised graduate students such as Hamza Sadruddin and Alan Zhang , who have presented at IEEE Sensors and ION GNSS+ conferences, with Zhang winning Best Presentation. He has no listed grants in the provided text but has received prestigious fellowships. His research lab supports innovation in real-time embedded sensor fusion with links to industry and open-source tools.