Jens Lienig has been a Professor at Technische Universität Dresden since 2002, where he directs the Chair of Development and Design of Precision Engineering and Electronics. His research spans Electronic Design Automation (EDA), electromigration analysis, 3D IC design, constraint-driven methodologies, and precision device development. He holds memberships in IEEE, VDE/VDI GMM, and technical committees, and has led conferences like ISPD 2021 as General Chair. Research interests focus on: Reliability Engineering : Electromigration-aware IC design, thermal/stress modeling in interconnects. Advanced Design Automation : 3D physical design algorithms, analog layout generators, constraint propagation. Precision Devices : MEMS sensors, peristaltic pumps, SAW motors, pyroelectric detectors. Recent articles (2019–2025) emphasize electromigration robustness, aerosol sensor signal processing, and open-source EDA tools. Over 15 doctoral students have completed under his supervision, including dissertations on electromigration, MEMS, and infrared sensors.
Professor Sheng Chen at the University of Southampton holds a prestigious academic rank in the Electronics and Computer Science department. His research interests span wireless communication systems, machine learning for signal processing, underwater robotics, and digital twin technology. IEEE Fellow Royal Academy of Engineering Fellow Chartered Engineer Research Focus: Professor Chen specializes in advanced wireless communication systems including MIMO technologies, channel estimation techniques, and next-generation 6G protocols. His work extends to industrial cybersecurity applications and underwater stereo matching algorithms. Recent Contributions: His latest publications demonstrate expertise in memristor-based signal processing circuits, label distribution learning using renormalization group theory, and innovative interference mitigation strategies in dynamic TDD systems. Current research projects: Optimising control system integrity (Royal Academy of Engineering), NEWCOM (European Union)
Paolo Ciampolini is a full Professor in the Department of Engineering and Architecture at the University of Parma, Italy. He has been a permanent faculty member since 2001 and previously held academic positions at the University of Perugia and the University of Bologna. He is actively involved in teaching, research, and international collaboration, particularly in electronics, digital design, and ICT for health. He serves as the European Coordinator of the ERASMUS+ GREATER project and is a visiting professor at INES-Ruhengeri in Rwanda. Research Interests: Development of semiconductor device models and simulation tools High-frequency circuits and signal integrity in ICs Radiation-hardened circuits for high-energy physics (collaboration with CERN and INFN) Assistive technologies and IoT for Active and Assisted Living Non-invasive monitoring using sensor networks and machine learning Low-power and VLSI digital design His recent publications focus on sleep posture classification using accelerometer and vision-based CNN systems, contactless sleep monitoring with smart beds, and machine learning for heartbeat detection from ballistocardiographic signals. These works highlight a strong trend toward applying electronics and AI to healthcare challenges, particularly for elderly and disabled individuals. Scientific Leadership and Projects: Scientific Coordinator: FOOD (AAL-JP, EU, 2011–2013) Scientific Coordinator: HELICOPTER (AAL-JP, EU, 2013–2016) European Coordinator: NOAH (AAL-JP, EU, 2016–2019) Participant: ACTIVAGE (H2020 IoT-LSP, EU, 2017–2021) European Coordinator: GREATER (ERASMUS+, 2024–present) Member: Advisory Board of several European projects Board of Directors: CLUSTER Health (Emilia Romagna regional health innovation network) Teaching and Academic Service: Current courses: Electronics 1, VLSI Digital Design, ICT for Health and Well-being Previously taught: Logic Design, Computer Architecture, Analog Circuits, Microelectronics, Semiconductor Physics Chairman of the Board of Electronics, University of Parma (2001–2010) President, Collaboration Center on Assistive Technologies (Centro TAU) Labs and Research Groups: His work is conducted within the research infrastructure of the Department of Engineering and Architecture at the University of Parma, with strong ties to the Centro TAU and collaborations with INFN and CERN. His current research integrates sensor design, IoT networking, and data analytics in health-focused applications.
Dr. Peter Mather is a Senior Lecturer in the Department of Engineering at the School of Computing and Engineering, University of Huddersfield. He leads the Complex Pathway program and is affiliated with the Centre for Efficiency and Performance Engineering and the Secure Societies Institute. His research spans analogue/digital electronics, sensor networks, and sustainable technology. PhD in 'Performance optimisation of VLSI circuits' (University of Huddersfield, 1995) MEng/BEng Electronics Course Leader since 2003 Research focuses on non-linear ADC development , partial discharge sensor networks , weapon detection , renewable energy systems , and optical coding via FPGA . His work contributes to UN SDGs for sustainable energy and security technologies. Recent publications analyze WLAN architectures, chaotic ADCs, and radiometric localization techniques. Scientific contributions include: 15+ publications in 2021 (3) and 2020 (2) with Scopus citations Expertise in wireless sensor networks, pulse position modulation, and visible light communication KTP award for radiation detection innovation (2018) He supervises PhD students in signal measurement and FPGA-based optical coding schemes, leveraging expertise in VHDL implementation and Sigma-Delta ADCs.
Милорад Б. Тошић is a Full Professor at the Faculty of Electronic Engineering, University of Niš, specializing in Computer Science. He earned all his academic degrees (BSc 1989, MSc 1992, PhD 1998) from the same institution in Electrical Engineering and Computer Science. His research spans Semantic Web Technologies, Distributed Systems, and E-Learning Systems, with notable contributions in federated testbeds, trust-based peer assessment, and collaborative wiki tagging. His work bridges theoretical computer science with practical applications in education and embedded systems. His publication trends show consistent contributions from 1991 to 2014, with recent focus shifting from hardware design (1990s) to semantic technologies and e-learning systems (2000s-2010s), demonstrating adaptability across evolving technological domains. US Patent Application No. 09/636,552 for Internet-Enabled Embedded Device Technology validated by Motorola, Microchip, Philips, and Delphi As former Science and Technology Advisor to the Serbian Minister (2002-2003), he contributed to national science policy. His current research involves 4 national and 3 international projects totaling 7 impact-factor journal publications. His patented embedded device technology has achieved commercial validation through major global electronics firms.
Valencia Joyner Koomson is an Associate Professor in the Department of Electrical and Computer Engineering at Tufts University’s School of Engineering. She also holds concurrent appointments in the Tisch College and the Department of Computer Science. Her primary affiliation is with the Advanced Integrated Circuits and Systems Lab, where her research focuses on silicon-based VLSI systems, optoelectronic integration, and biomedical imaging applications. Dr. Koomson received her Ph.D. from the University of Cambridge and previously worked at the University of Southern California’s Information Sciences Institute (USC/ISI), specializing in radiation-hardened VLSI systems for military and aerospace applications. Her academic journey includes a B.S. and M.Eng. from MIT, followed by a Marshall Scholarship and Intel Foundation support. She has held visiting professorships at MIT, Boston University, and Rensselaer Polytechnic Institute. Notable awards include the NSF CAREER Award and recognition as a National Science Foundation Graduate Research Fellow. Research interests span mixed-mode VLSI systems (analog/digital/optical), optoelectronic system-on-chip integration, and applications in medical imaging and optical wireless communication. Her lab develops wearable health monitoring devices, including the AHOMKA hypertension management platform for Ghana. Recent work includes miniaturized NIRS instruments, microfluidic devices for cell analysis, and millimeter-wave circulators in CMOS. Dr. Koomson has authored over 85 publications and secured grants from NIH, NSF, and industry partners. Current projects include mHealth platforms, noninvasive brain stimulation systems, and culturally adapted healthcare solutions. She actively mentors graduate students in interdisciplinary research combining electrical engineering with biology and public health. Grants: Over 39 funded projects, including NIH’s AHOMKA initiative and NSF’s HDR Tripods Center. Labs: Advanced Integrated Circuits and Systems Lab (AICS Lab) with collaborators in biomedical and materials sciences. Teaching: Courses on VLSI design, digital electronics, and wearable systems.
Alex Doboli is a Professor in the Department of Electrical and Computer Engineering at Stony Brook University, State University of New York. He is also affiliated with SUNY Korea’s Department of ECE. His academic journey includes a Ph.D. in Computer Engineering from the University of Cincinnati (2000) and earlier degrees from Politehnica University Timisoara, Romania (B.Eng. 1990, Doctorate 1997). He served as junior faculty at Politehnica University before joining Stony Brook in 2000. His research focuses on Electronic Design Automation (EDA) , Cyber-Physical Systems , and Human-inspired Machine Learning . Key areas include analog/mixed-signal design, innovation methodologies, and data-driven design approaches. He has authored over 170 peer-reviewed publications and co-authored a textbook on mixed-signal design. His lab, the Mixed-Domain Embedded Systems Laboratory , explores team behavior modeling, IoT integration, and cognitive architectures. Dr. Doboli has advised 17 Ph.D. and 12 M.S. students. Notable awards include the IBM Partnership Award (2001) and the Traian Lalescu Award (1987). He serves as an Associate Editor for Integration, the VLSI Journal and holds leadership roles in professional organizations like the IEEE Long Island Circuits and Systems Society. His teaching spans undergraduate and graduate courses in programming, algorithms, VLSI design, and machine learning. Current courses include ESE 327: Fundamental Algorithms for Machine Learning and ESE 589: Learning Systems for Engineering Applications . Recent research highlights include automated dialog systems (diaLogic), IoT-human behavior integration frameworks, and studies on artistic understanding in neural networks. His work bridges EDA, machine learning, and embedded systems to advance design innovation and human-centric technologies.
Ismail Serdar Ozoguz is a Professor at Istanbul Technical University, Department of Electronics and Communication Engineering. With over 163 publications and 3020 citations, his work spans oscillator engineering, neural networks, and RF/wireless systems. Institution : Istanbul Technical University Department : Electronics and Communication Engineering Rank : Professor Research interests focus on oscillator engineering , current mode circuits , and chaotic oscillators . Recent work emphasizes neural network applications in filter optimization, antenna modeling, and stochastic computing. Scientific awards include: GEBIP Award (2002) Mustafa Parlar Foundation Research Incentive Award (2003) Research Incentive Award (2004) Projects highlight nonlinear optimization in GaN amplifiers, fractional-order neural networks, and spintronics for communication/memory systems. Collaborations span biomedical engineering, wireless networks, and AI-driven optimization.
Shoba Krishnan is a Professor in the Department of Electrical and Computer Engineering at Santa Clara University's School of Engineering. Her work spans analog and mixed-signal integrated circuit design, carbon nanotube interconnect modeling, and engineering education initiatives. Education: B. Tech., Jawaharlal Nehru Technological University (1987) M.S., Michigan State University (1990) Ph.D., Michigan State University (1993) Her research focuses on high-speed data communication ICs, particularly clock/data I/O circuits, and explores carbon nanotubes as interconnect materials. She's expanding into bio-engineering instrumentation and renewable energy power electronics. Publications highlight work on low-power high-speed drivers, carbon nanotube via resistance analysis, microwave frequency modeling, and BIST structures for transceivers. She advises IEEE and Engineers Without Borders chapters at SCU.
Danny Chen is a Professor in the Department of Computer Science and Engineering at the University of Notre Dame, with a concurrent appointment in the Department of Applied and Computational Mathematics and Statistics. His research focuses on algorithm design, computational geometry, biomedical imaging, and machine learning. Ph.D., Computer Science, Purdue University (1992) M.S., Computer Science, Purdue University (1988) B.S., Computer Science and Mathematics, University of San Francisco (1985) Dr. Chen has developed over 330 publications and 5 U.S. patents, with applications in radiation therapy, biomedical imaging, and VLSI design. His recent work explores advanced deep learning architectures for medical image segmentation and tabular data analysis. Key awards include the NSF CAREER Award, Kaneb Teaching Award, James A. Burns Award, and Computerworld Honors Program Laureate. He is an IEEE Fellow and ACM Distinguished Scientist. Visiting Professor at HKUST (2003), Tsinghua University (2012), and Zhejiang University (2012) Research funded by NSF and NIH Active in program committees and NSF review panels
Hossein Esmailbeygi is a Research Fellow at the Department of Electrical and Computer Engineering, Aarhus University (AU Engineering). His work focuses on integrated circuit design and sensor technology applications in district heating networks. Primary affiliation: Electronics and Photonics Research interests include: Integrated Circuits, Sensor Technology, and Calibration Techniques. His recent publication in the Custom Integrated Circuits Conference demonstrates expertise in VLSI design for infrastructure monitoring.
Claes Hjortsberg Romlov Jensen serves as an Assistant Lecturer in the Department of Electrical and Computer Engineering at Aarhus University's AU Engineering faculty, maintaining both primary departmental affiliation and one additional institutional appointment. His research focuses on core engineering disciplines with emphasis on: Electrical Engineering Computer Engineering Signal Processing Embedded Systems Computer Networks VLSI Design These interests directly align with the department's technological innovation mandate in electrical and computational systems development.
Uğur ÇİNİ is an Associate Professor in the Department of Electronics Engineering at Uskudar University, where he has served as faculty since 2019. Previously, he worked as a research assistant at Boğaziçi University and Southern Methodist University, and gained industry experience as an R&D engineer at İsbak Inc. and Anka Mikroelektronik Inc. His educational background includes: Undergraduate Degree in Electronics and Communications Engineering from Yıldız Technical University (1999) Master's Degree in Electrical and Electronics Engineering from Boğaziçi University (2003) Doctorate in Electrical and Electronics Engineering from Boğaziçi University (2010) Dr. ÇİNİ's research spans VLSI Design, Digital Arithmetic, Analog IC Design, Circuit Design for Biomedicine, and Embedded Systems. He specializes in CMOS circuit design, biomedical instrumentation, and FPGA-based implementations, with recent projects focusing on energy harvesting converters and high-speed logic circuits for practical applications. His publication record (2017-2023) demonstrates expertise in analog/digital circuit design for biomedical instrumentation, display technologies, and reconfigurable systems. Key trends include low-power optimization, precision amplifier development, and current-mode circuit innovations addressing real-world engineering challenges in medical devices and display drivers. No scientific awards are listed in the available information. He has supervised graduate theses on energy harvesting converters (2024), source-coupled logic (2023), and FPGA implementations (2022). Administratively, he advises 100-150 students, served as Deputy Head of Department (2021-2024), and participates in Quality, Internship, Erasmus, and International Students committees. As laboratory responsible since 2020, he led the 2024 establishment of the Power Systems and Electrical Machines Laboratory, demonstrating hands-on leadership in educational infrastructure development.
Xiaolong Liu serves as Assistant Professor at Southern University of Science and Technology's School of Microelectronics. His academic journey includes a Ph.D. from Hong Kong University of Science and Technology (2019), M.E. from Tsinghua University (2014), and B.E. from Beijing University of Aeronautics and Astronautics (2010). Prior to his current position, he worked as Staff Engineer at eTopus Technology in Silicon Valley (2019-2021) and completed a postdoc at HKUST. Ph.D. in Electronic and Computer Engineering, Hong Kong University of Science and Technology (2019) M.E. in Microelectronics, Tsinghua University (2014) B.E. in Electronic Engineering, Beijing University of Aeronautics and Astronautics (2010) Dr. Liu's research spans cutting-edge RF/mm-Wave/THz integrated circuit design, focusing on high-performance signal generators , ultra-wideband transceivers , and low-power frequency synthesis . His work addresses critical challenges in 5G/6G communications, terahertz spectroscopy, and high-speed wireline interfaces through innovative CMOS architectures. Technical emphases include varactor-less VCOs, harmonic enhancement techniques, and magnetic tuning mechanisms for millimeter-wave systems. His publication portfolio demonstrates consistent leadership in IEEE flagship journals/conferences (JSSC, TMTT, ISSCC, VLSI), with recent work advancing Class-F oscillators, sub-sampling PLLs, and sub-THz synthesizers. Notable trends include migration toward sub-THz frequencies (2023-2025) , multi-core oscillator architectures , and elimination of harmonic tuning for simplified design. IEEE VLSI Paper Technical Highlights (2019) IEEE CICC Invited Talk (2019) IEEE TVLSI 2023 Best Reviewer Award Top 4 Most Downloaded Paper in TCAS-II (July 2022) Dr. Liu actively mentors students through SUSTech's graduate programs, with advisees consistently earning university-level thesis awards and conference recognitions. His lab maintains strong industry ties through silicon validation and collaborates on cutting-edge tapeouts in 7nm/16nm nodes. Current projects focus on cryo-CMOS interfaces for quantum computing and ultra-wideband transceivers for 6G applications. His research group operates within SUSTech's state-of-the-art microelectronics facility, specializing in mm-Wave/THz characterization and high-speed SerDes validation. The team maintains partnerships with semiconductor foundries for advanced-node prototyping and collaborates with industry leaders on real-world implementation challenges.
Dimitrios Kosmopoulos serves as Professor in the Computer Engineering and Informatics Department at the University of Patras, Greece, with extensive experience across multiple academic institutions including National Technical University of Athens (NTUA), Rutgers University, and University of Texas at Arlington. His research bridges theoretical computer science with practical applications in accessibility, agriculture, and cultural heritage preservation. Education: B.Eng. in Electrical and Computer Engineering, National Technical University of Athens (1997) PhD in Electrical and Computer Engineering, National Technical University of Athens (2002) Professor Kosmopoulos' research integrates computer vision, machine learning, and signal processing to solve real-world problems. His primary focus areas include sign language recognition systems for museum accessibility, precision agriculture applications for crop monitoring and disease detection, and digital restoration of ancient scripts like Mycenaean Linear B. His methodological innovations frequently involve geometric analysis, time-series modeling, and multimodal data fusion techniques that advance both theoretical frameworks and practical implementations. Analysis of his recent publications (2023-2025) reveals three dominant research thrusts: accessibility technologies for deaf communities (particularly museum navigation systems), agricultural automation using computer vision (olive grading, tomato disease detection), and computational archaeology (Linear B tablet restoration). His work consistently employs cutting-edge approaches including geometric knowledge distillation, coupled learning architectures, and 3D motion analysis, demonstrating strong interdisciplinary connections between computer science, agriculture, and humanities. No scientific awards were documented in the provided source materials. While specific advising details and grant information were not explicitly stated, his leadership in projects like HealthSign (sign language healthcare systems) and MuseLearn (museum accessibility platforms) indicates substantial research funding and collaborative supervision activities spanning computer vision, robotics, and assistive technology domains. Professor Kosmopoulos operates within the Division of Hardware and Computer Architecture at the University of Patras, collaborating with the Computer Technology and Architecture Laboratory, VLSI Microelectronics Laboratory, Signals and Telecommunications Laboratory, and Computer Communications Networks Laboratory. His current research integrates these facilities to develop systems like the SignGuide project for museum tours and frameworks for early pest detection in greenhouse crops, emphasizing practical implementations of machine learning in constrained environments.
