Antonio Calvo Morata is an Assistant Professor at the Universidad Complutense de Madrid (UCM), specializing in Software Engineering and Artificial Intelligence. He belongs to the research group "Ingeniería del software y e-learning" and focuses on applying learning analytics and serious games to address educational challenges, particularly in bullying prevention and STEM recruitment. His work integrates AI-driven tools to enhance game development and assessment workflows. Education: Doctorate from UCM (2020) with a thesis on using learning analytics for serious games validation in cyberbullying contexts. Supervisors included Dr. Baltasar Fernández Manjón and others. Research Interests: Development of inclusive serious games, AI applications in education, game-based learning analytics, and tools simplifying game validation (e.g., Simva framework). His studies span STEM education outreach, collaborative learning methodologies, and bioelectrical signal analysis for game evaluation. Key Contributions: Designed the Conectado serious game for bullying awareness, validated through rigorous analytics. Pioneered frameworks blending visual and data mining techniques for educational game improvement. Explored AI tools to streamline serious game authoring and deployment. Labs/Teams: Active in the UCM's Software Engineering and e-learning research group, focusing on educational technology innovation.
Dr. Faheem Ershad is an Assistant Professor in the Department of Electrical & Computer Engineering at the University of Houston, affiliated with the College of Engineering. His research focuses on soft bioelectronic systems integrating wearable/implantable devices with tissues, leveraging 3D biofabrication, optoelectronics, and machine learning. He leads the bioelectronic Synergy Lab, emphasizing interdisciplinary approaches to cardiac health and neural modulation. Education: B.S. (Biomedical Engineering, UH), Ph.D. (Biomedical Engineering, Penn State), Postdoc (UIUC) Lab: bioelectronic Synergy Lab – develops hybrid bioelectronic-tissue systems for diagnostics and therapy Key Research Areas: Stretchable bioelectronics, tissue integration, ambulatory biosensors, electrophysiology His work bridges electrical engineering, materials science, and medicine, with recent innovations in drawn-on-skin sensors, rubbery semiconductor electronics, and bioprinted cardiac tissues. Over 20 peer-reviewed articles showcase advancements in soft electronics for healthcare applications. Notable Awards: NSF Career Award Editorial Contributions: Guest Editor for Biosensors special issue Current projects include developing customizable wearable devices and exploring machine learning-driven bioelectronic interfaces. The lab actively collaborates with industry through its NSF-funded programs and maintains a strong focus on translational research.
Prof. David Valeriu is a Professor at the Department of Electric Engineering, Technical University of Iasi. His research focuses on electromagnetic compatibility, biomedical instrumentation, and environmental monitoring of electromagnetic fields. He leads projects investigating the health effects of electromagnetic fields on humans, including effects on bioelectric signals and induced currents in the body. His work also involves developing advanced measurement systems and materials for electromagnetic shielding. Key research areas include: Electromagnetic field measurements in hospitals, power substations, and residential areas Biomedical signal processing (ECG, PPG, brain activity) Development of low-cost embedded platforms for medical applications Electromagnetic interference mitigation in medical devices and imaging systems His recent studies address: Long-term magnetic field surveys in laboratories and hospitals Exposure assessment of mobile phone and power line emissions Omni-directional shielding materials for high-frequency radiation Integration of biosignal monitoring systems with ambient assisted living Prof. Valeriu has contributed to over 50 peer-reviewed publications, with a focus on electromagnetic field characterization and biomedical engineering applications. His work frequently explores the intersection between environmental safety and medical technology.
Reto A. Wildhaber is a Professor for Digital Biomarkers and Signal Processing at Fachhochschule Nordwestschweiz (FHNW) and a Senior Researcher at the Signal and Information Processing Laboratory (ISI) , ETH Zürich. He specializes in biomedical signal analysis, model-based signal processing, and development of medical sensor systems. Education : Dr. sc. ETH, Dr. med. Research : Focuses on digital biomarkers, clinical trials for medical devices, and advanced signal processing techniques for physiological signals. Teaching : Co-teaches courses in Biomedical Engineering and Medical Informatics, including 'Model-Based Signal Processing and Diagnostics' and 'Digital Biomarkers'. Publications : His work spans cardiovascular diagnostics, neural signal processing, and esophageal mapping technologies, with recent studies on intracoronary ECG analysis and smartwatch ECG signal characterization. Patents : Holds patents for medical catheter designs and ECG monitoring systems. Projects : Develops open-source tools like lmlib.ch for biomedical signal processing and CLabUZH for cardiopulmonary simulations.
Dmitry A. Konovalov is a researcher at James Cook University with interdisciplinary expertise spanning computational biology, marine ecology, and machine learning applications. His work bridges theoretical and applied research across diverse domains including wildlife conservation, fisheries management, medical imaging, and environmental science. Developed deep learning solutions for underwater fish detection and whale identification Created bioelectrical impedance methods for turtle body condition assessment Contributed to statistical genetics and kinship analysis methodologies Worked on electron transport physics in biomolecular systems Developed biomedical imaging tools for fish measurement and pearl oyster analysis Research interests center on computational methods for ecological monitoring, including image processing, acoustic analysis, and genetic modeling. Current work focuses on developing automated tools for wildlife assessment and environmental data analysis. Recent publications demonstrate expertise in deep learning applications for marine biology, with projects spanning fish biomass estimation, turtle adipose analysis, and whale recognition systems. His work also includes environmental health risk assessment and signal processing in biological contexts.
Phil Campbell is a Research Professor in the Biomedical Engineering Department at Carnegie Mellon University (CMU), with courtesy appointments in Biological Sciences and Mechanical Engineering. He is affiliated with the Engineering Research Accelerator and the Bioengineered Organs Initiative. His research focuses on biomaterials, tissue engineering, and extracellular vesicle-based therapies, with over 25 years of multidisciplinary collaboration between engineers and clinicians. Campbell holds a Ph.D. in Physiology from Pennsylvania State University (1988) and earlier degrees in Animal Science from Auburn University. Research interests include biomaterials development, cell engineering, and immunomodulation strategies for regenerative medicine. Notable projects include ARPA-H-funded bioelectric medicine implants for diabetes treatment, NIH-backed exosome research with the University of Pittsburgh, and soy protein-based wound dressings via collaboration with OmegaSkin. His work emphasizes spatial control of cellular behavior using biopatterned microenvironments and biomimetic scaffolds. Recent grants include a $42M ARPA-H award for implantable bioelectric devices and a $34.9M grant for obesity/diabetes therapies. Key innovations include dissolvable microneedle drug delivery systems, exosome-functionalized polymers, and 3D-printed ice for biomedical applications. Campbell’s lab also explores exosome-mediated horizontal gene transfer in Streptococcus pneumoniae and epigenetic targeting in bone marrow microenvironments. Collaborative projects span academic and industry partnerships, including Coya Therapeutics for exosome engineering platforms. His team’s work has been highlighted in media for advancements in curcumin delivery, 3D-printed cartilage, and bioelectric medicine. Students under his guidance, such as Nader Rezazadeh, focus on bioactive scaffold development and entrepreneurial applications.
Prof. Dr. Özlem Coşkun is a full-time faculty member at Süleyman Demirel University's Department of Electrical and Electronics Engineering within the Faculty of Engineering and Natural Sciences. She holds a PhD in Physics and has extensive academic qualifications including degrees from the same university. Education: Bachelor's in Electronics and Communications Engineering (2002) Master's in Electronics and Communications Engineering (2005) Doctorate in Physics (2009) Research Focus: Her work centers on bioelectromagnetics, electromagnetic effects on biological tissues, medical electronics, and antenna design. Key research areas include: Electromagnetic exposure safety assessments Biotelemetry and implantable device design Antenna systems for wireless communication Health monitoring technologies Recent Article Trends: Recent publications emphasize: Electromagnetic field effects on biological systems (testicular tissue, blood cells) Advanced antenna designs (MIMO, patch, implantable) Arduino-based biomedical instrumentation Health monitoring systems for elderly care Grants & Labs: While specific grants aren't listed, her work suggests involvement in: Biomedical engineering research facilities Electromagnetic field measurement labs Collaborations with clinical institutions
Antoni Ivorra is a Professor at the Department of Information and Communication Technologies (DTIC) of Universitat Pompeu Fabra (UPF) , and a Serra Húnter Fellow and ICREA Acadèmia Fellow . He joined UPF in 2010 after completing a postdoctoral fellowship at the University of California, Berkeley (2005-2009), a short-term position at CNRS-Institut Gustave Roussy (2009), and prior work at the Biomedical Applications Group of the Centre Nacional de Microelectrònica (1998-2005). He earned a PhD in Electronics Engineering from the Universitat Politècnica de Catalunya in 2005. His research focuses on bioelectrical phenomena for biomedical applications , including electroporation , electrical bioimpedance , and injectable electronics for neuroprosthetics. His work spans device development, computational modeling, and clinical translation, with emphasis on tissue ablation and wireless implantable systems. His recent publications highlight advancements in pulsed field ablation , volume conduction for powering implants, and multiscale modeling of electroporation effects. These contributions reflect interdisciplinary expertise in biomedical engineering , electrophysiology , and medical device innovation . Scientific Awards : ERC Consolidator Grant (2016) Serra Húnter Fellow ICREA Acadèmia Fellow
Pamela Abshire is a Professor in the Department of Electrical and Computer Engineering and the Institute for Systems Research at the University of Maryland, College Park. She holds the rank of Fischell Institute Fellow and is affiliated with the Maryland Robotics Center, Brain and Behavior Institute, and Robert E. Fischell Institute for Biomedical Devices. Her work bridges VLSI circuit design and bioengineering, focusing on performance-resource tradeoffs in natural/engineered systems. Education: B.S. Physics (Caltech, 1992), M.S. and Ph.D. in Electrical Engineering (Johns Hopkins University, 1997 and 2001). Pre-UMD career included R&D roles at Medtronic (1992-1995). Research focuses on CMOS biosensors, low-power microsystems, and bio-inspired designs for applications like cell-based sensing, robotics, and medical devices. Notable projects include nose-on-a-chip odor detection systems, ant-like microrobots, and lab-on-CMOS platforms for real-time cell monitoring. Awards include IEEE Fellow (2018), NSF CAREER Award (2003), and 2021 University Distinguished Scholar-Teacher honor. Active in academic leadership roles including ADVANCE Professor (2020-2021) and editorial work for IEEE Transactions on Circuits and Systems. Grants include NSF funding for olfactory sensing, AFOSR bio-inspired flight tech, and DARPA CogniSense initiatives. Her Integrated Biomorphic Information Systems Lab collaborates on semiconductor innovation through partnerships like the Mid-Atlantic Semiconductor Collaborative. Labs/Teams: Leads the Integrated Biomorphic Information Systems Lab and contributes to Microelectronics at Maryland group. Co-develops biohybrid systems integrating CMOS, MEMS, and biological components.
Dr. Saeed Alighaleh is a Research Fellow at the University of Auckland, affiliated with the Faculty of Medical and Health Sciences (Department of Surgery) and the Auckland Bioengineering Institute (ABI). He also holds a Casual Academic role in Biological Sciences and works as a Senior Product Development Engineer at Alimetry. His research focuses on biomedical engineering, particularly gastric pacing devices and wearable systems for postoperative monitoring. PhD in Bioengineering from the University of Auckland (2020) MSc in Electrical Engineering-Digital Communication Systems from Babol Noshirvani University of Technology (2012) BSc in Electrical Engineering-Electronics from Babol Noshirvani University of Technology (2009) His research explores gastric slow-wave dynamics, electrode design for gastrointestinal motility disorders, and non-invasive diagnostic tools like body-surface gastric mapping (BSGM). Recent work includes optimizing pacing parameters for therapeutic applications and developing laser-based agricultural sensors. As an Accredited Supervisor, Dr. Alighaleh guides graduate research in the GI Research Group at ABI. He has contributed to gastric pacemaker design, ventilation artifact suppression algorithms, and energy sector prioritization frameworks, with publications spanning biomedical engineering, gastrointestinal electrophysiology, and agricultural technology.
Vincent Jacquemet is an Associate Professor in the Department of Pharmacology and Physiology at the University of Montreal's Faculty of Medicine. His research laboratory is located at the Research Center of the Hôpital du Sacré-Coeur de Montréal. He is also a member of the Institute of Biomedical Engineering (IGB, UdeM), the Centre for Applied Mathematics in Bioscience and Medicine (CAMBAM, McGill), and the Groupe de Recherche en Sciences et Technologies Biomedicales (GRSTB, Polytechnique Montreal). Born in Sion, Switzerland Master degree in Physics (2000) from Swiss Federal Institute of Technology, Lausanne (EPFL) Ph.D. in Signal Processing (2004) from EPFL under J.-M. Vesin and M. Kunt Post-doctoral research at EPFL/Lausanne University Hospital and Duke University Dr. Jacquemet's research focuses on cardiac electrophysiology, neurocardiology, biophysical modeling, complex dynamical systems, computer simulation and signal processing. His work combines integrative biophysical modeling and signal processing techniques to improve diagnostic interpretation of cardiac bioelectric signals. Specific research themes include modeling atrial electrophysiology and arrhythmias, ECG signal processing, and multichannel recordings of the intrinsic cardiac nervous system. His laboratory develops three-dimensional virtual models of the human atria based on anatomical, histological and electrophysiological data, and creates patient-specific approaches to estimate and monitor the rate-corrected QT interval. Analysis of Dr. Jacquemet's recent publications reveals a strong focus on computational modeling of cardiac electrophysiology, particularly atrial fibrillation mechanisms and diagnostics. His work integrates experimental data with sophisticated computer simulations to bridge the gap between clinical observations and underlying cardiac pathology. Recent publications show expanding applications to pediatric oncology survivors, examining cardiac electrical abnormalities following cancer treatment, demonstrating the translational impact of his research. Research scholar Junior 1 from Fonds de Recherche du Quebec en Sante (FRSQ) Research scholar Junior 2 from Fonds de Recherche du Quebec en Sante (FRSQ) Dr. Jacquemet has advised numerous graduate students and postdoctoral researchers, with current doctoral and master's students working on electrophysiological modeling of atrial arrhythmias, neural control of cardiac function, and ECG signal processing. His research is conducted in collaboration with multiple institutions including Hôpital du Sacré-Coeur, East Tennessee State University, and the Lausanne Heart Group. His laboratory is equipped with office space for students, desktop workstations, and access to Linux clusters at RQCHP for high-performance computing needs.
Timothée Wintz is a Postdoctoral Researcher in the Perception team at INRIA Grenoble Rhone-Alpes since April 2020, specializing in interdisciplinary research spanning robotics, computer vision, and signal processing with applications in healthcare, agriculture, and biomedical domains. His work demonstrates strong cross-domain integration of engineering and life sciences methodologies. Educational background: PhD in Signal and Image Processing from Université Paris sciences et lettres (2017), thesis: "Super-resolution in wave imaging" (NNT: 2017PSLEE052) Wintz's research program centers on developing perception systems for real-world applications, with particular emphasis on socially relevant robotics. His work bridges theoretical signal processing with practical implementations in gerontological healthcare (socially pertinent robots), precision agriculture (microfarm robotics), and biomedical diagnostics (conductivity imaging). The technical core involves advanced computer vision algorithms, wave-based imaging techniques, and human-robot interaction frameworks designed for complex environments. Publication trends reveal a strategic evolution from fundamental imaging techniques (2016-2017) toward applied robotics systems (2020-2025), with increasing focus on societal impact. His recent work shows strong emphasis on healthcare robotics for elderly populations and agricultural automation, while maintaining methodological roots in computer vision and signal processing. The collaborative nature of his publications (e.g., 21 co-authors on the 2025 IJSR paper) indicates participation in large-scale European research initiatives. Scientific awards: No awards documented in provided materials Advising and research funding: No student supervision records indicated Participation in European Commission-funded projects evident from report publications (e.g., D5.5 report) Wintz operates within INRIA's Perception team at the Grenoble Rhone-Alpes center, which focuses on computer vision, machine learning, and robotics research with strong industry and healthcare application partnerships. The team's work integrates multimodal perception systems for autonomous agents operating in unstructured environments.
Professor Edwin Chihchuan Kan is a faculty member in the School of Electrical and Computer Engineering at Cornell University. He joined Cornell in 1997 as an Assistant Professor and is now a full Professor. His research focuses on near-field radio frequency sensing and RFID technologies with applications in health monitoring and senior care. Education B.S. in Electrical Engineering, National Taiwan University (1984) M.S. in Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (1988) Ph.D. in Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (1992) Research Interests Professor Kan's research spans multiple areas in electrical engineering and biomedical applications. His primary focus is on near-field radio frequency (RF) sensing technology for monitoring vital signs, muscle activities, and tissue vibration without requiring body contact. This technology enables non-invasive monitoring of internal organs and tissues. He also works extensively with RFID technologies for precision tracking, imaging, and occupant counting. His earlier work focused on CMOS technology and circuits for nonvolatile memories before shifting toward biomedical applications after 2014. His research encompasses several key areas including Sensors and Actuators, Nanobio Applications, Nanotechnology, Semiconductor Physics and Devices, Bioengineering, Biomedical Engineering, Bio-Electrical Engineering, Solid State Electronics, Optoelectronics, MEMs, Integrated Circuits, and Biomedical Imaging and Instrumentation. Research Trends Professor Kan's recent publications demonstrate a clear shift in research focus from traditional semiconductor memory technology toward biomedical applications of RF and sensor technology. His work shows increasing integration of signal processing and machine learning techniques with hardware development. The publications from 2013-2014 reflect this transition period where he was working on both memory technologies (DRAM-Flash hybrid memory, Flash memory security) and emerging biomedical sensor applications (ion-sensitive transistors, CMOS sensing of biological signals, RF biosensors). Scientific Awards Cornell Inventor Award, Cornell University (2006) Robert '55 and Vanne '57 Cowie Excellence in Teaching Award, College of Engineering, Cornell University (2003) Cornell Inventor Award, Cornell University (2003) Best Chapter Chair Award, Institute of Electrical and Electronics Engineers (IEEE) (2002) Presidential Early-Career Award for Scientists and Engineers (PECASE) Award, U.S. Government (2000) Teaching and Service Professor Kan teaches graduate courses on Semiconductor Memories and RFID, and undergraduate courses covering a wide range of topics including Introduction to Microelectronics, Quantum Mechanics, Silicon Devices, Digital Circuit Design, RF Systems, Robust Programming, and Nanofabrication. He served as the ECE Director of Graduate Studies from 2010 to 2013.
Assoc. Prof. Marko Dimitrijević is affiliated with the University of Niš, Faculty of Electronic Engineering, where he holds the position of Associate Professor since 2021. He leads the Laboratory for Electronic Design Automation (LEDA) and the Laboratory for Electronics. His academic journey includes a PhD in 2012 on 'Electronic System for Polyphase Loads Analysis Based on FPGA' and postgraduate studies from 2005. He has conducted research exchanges at Technische Universität Ilmenau (Germany), IHP Microelectronics (Germany), the University of Southampton (UK), and Universidad Politécnica de Madrid (Spain). Prof. Dimitrijević teaches courses such as 'Introduction to Electronics' and 'System on a Chip' across undergraduate, master’s, and doctoral programs. His research focuses on MPPT algorithms, harmonic detection, FPGA applications, and smart grid technologies. He has supervised two master’s theses and contributed to numerous academic publications. His work bridges theoretical advancements with practical applications in renewable energy systems and power electronics. Education: Bachelor's in Electronics and Telecommunications (2002, Faculty of Electronics, Niš) Master's in Electronics (2005, Faculty of Electronics, Niš) PhD in Electronics (2012, Faculty of Electronics, Niš) Professional Roles: Assistant Professor (2016–2021) Associate Professor (since 2021) Head of LEDA and Electronics Lab Research Highlights: Development of FPGA-based systems for polyphase load analysis MPPT controller optimization for standalone PV systems Nonlinear load characterization using machine learning Labs & Teams: LEDA focuses on electronic design automation and power electronics, while the Electronics Lab supports undergraduate teaching and experimental research.
Professor Alexandra Piryatinska is a faculty member in the Department of Statistics at San Francisco State University, located at TH 942. Her research focuses on time series analysis, EEG signal processing, complexity theory, and applications in medical diagnostics and biomarker identification. She holds a Ph.D. in Mathematics and has published extensively in interdisciplinary areas combining statistics with neuroscience and oncology. Her work emphasizes novel methodologies for change-point detection in multidimensional time series, classification of EEG records using ϵ-complexity theory, and statistical modeling of cancer drug treatment success. Notable contributions include applications in Parkinson’s disease postural balance analysis, neonatal EEG sleep stage detection, and glycoprotein profiling in breast cancer subtypes. Her research trends span algorithmic complexity-based classification, biomedical signal processing, and data-driven medical decision-making. She collaborates across disciplines to address challenges in clinical diagnostics and pharmacogenomics. Her advising and grant activities are not explicitly detailed in the provided text, though her publications suggest involvement in collaborative research projects. She is affiliated with the SF State Faculty site and maintains an active research program in statistical methods for complex biomedical data.
