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Associate Professor
John Sartori is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Minnesota , holding the Robert and Sydney Anderson Professorship. His research focuses on extending Moore's law through energy-efficient computing by addressing hardware bottlene | [truncated for display]
Associate Professor
Associate Professor Rifai Chai is a faculty member in the Department of Biomedical Engineering at the School of Engineering, Swinburne University of Technology. He serves as the Academic Director (Partnerships), reflecting his leadership in academic-industry collaboration. His research focuses on the intersection of biomedical engineering and artificial intelligence, with applications in brain-computer interfaces, medical technologies, robotics, and embedded systems. University: Swinburne University of Technology School: School of Engineering Department: Biomedical Engineering Position: Associate Professor Email: rchai@swin.edu.au His educational and professional background includes over a decade of experience in product development in hardware, firmware, and software design in Indonesia and Australia from 2000 to 2011. His research interests are extensive and include: Artificial Intelligence and Machine Learning Brain-Computer Interfaces Medical Device Design Assistive Technology (e.g., smart wheelchairs, exoskeletons) Cognitive Fatigue and Workload Monitoring Back Pain Assessment and Rehabilitation Embedded Systems EEG and Physiological Signal Processing Rifai Chai's recent publications demonstrate a strong focus on AI-driven healthcare solutions. His work spans advanced computational intelligence in medical imaging (e.g., lung cancer and thyroid cancer detection), EEG-based systems for driver fatigue and emotion classification, rehabilitation technologies using exoskeletons, and cybersecurity in industrial IoT. He employs deep learning, hybrid models (e.g., MLP-BiLSTM), and advanced signal processing techniques to solve real-world biomedical problems. His research consistently targets practical, non-invasive, and real-time applications in clinical and industrial settings. His scientific contributions include numerous high-impact publications in journals such as IEEE Access, Sensors, and Medical & Biological Engineering & Computing, as well as book chapters with Elsevier and Springer. He has secured multiple research grants from industry partners and the Australian Research Council, supporting projects in breast electromagnetic scanning, solar-powered charging poles, and haptically-enabled motion simulation. Rifai Chai actively supervises PhD and Master’s students, with current HDR projects covering areas such as brain-computer interfaces for prosthetics, cognitive workload monitoring, distracted driving detection, and AI in medical imaging. He leads a multidisciplinary research team working at the forefront of biomedical innovation. His lab integrates AI, robotics, and physiological sensing to develop technologies that improve health outcomes and human performance.
Professor
Salvo Rossi is a Full Professor of Statistical Machine Learning for Signal Processing at the Department of Electronic Systems, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU). He holds leadership roles as Deputy Director for Research and Deputy Manager of the Centre for Green Shift in the Built Environment. Additionally, he serves as a part-time Senior Research Scientist at SINTEF Energy Research. His work bridges academia and industry, with significant contributions to signal processing, machine learning, and IoT systems. Research Interests: Statistical Machine Learning Data Fusion in Wireless Sensor Networks Digital Twins and Industrial IoT Anomaly Detection and Fault Diagnosis Federated and Distributed Learning Graph Signal Processing His recent publications reflect a strong trend toward intelligent, distributed systems for industrial monitoring, particularly in energy and safety-critical environments. The integration of machine learning with signal processing for decision fusion in sensor networks is a central theme. Scientific Awards and Recognition: Exemplary Senior Editor, IEEE Communications Letters (2018) Department Ambassador, NTNU (2016) IEEE Senior Member (since 2011) Editorial and Professional Service: Senior Area Editor, IEEE Transactions on Signal and Information Processing over Networks (since 2025) Topical Editor, IEEE Sensors Journal (since 2022) Area Editor, IEEE Open Journal of the Communications Society (2019–2023) Executive Editor, IEEE Communications Letters (2019–2021) General Chair, IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Trondheim, 2022 He has advised numerous PhD and master’s students (not explicitly listed), led major research projects in IoT and green energy, and contributed to national and international research initiatives. His lab, SPIN (Signal Processing Group), focuses on intelligent signal processing for real-world applications in smart environments and Industry 4.0.
Professor
Svetlana Neretina is a Professor in the Department of Aerospace and Mechanical Engineering and a Concurrent Professor in the Department of Chemistry & Biochemistry at the University of Notre Dame, where she has been on faculty since 2022. She previously served as an Associate Professor at Notre Dame (2016–2022) and Assistant Professor at Temple University (2009–2016). Her research focuses on the synthesis and fabrication of noble metal nanostructures for applications in catalysis, sensing, and energy. Key interests include plasmonics, nanofabrication techniques such as nanoimprint lithography and dynamic templating, photocatalysis for green chemical synthesis, hydrogen generation, and the development of in situ monitoring tools for scalable manufacturing. Her work bridges materials science, chemistry, and mechanical engineering. Her recent publications demonstrate a strong trend in advanced nanomaterial design, including core-satellite assemblies, epitaxially aligned arrays, and functional oxide nanoshells. These works span high-impact journals like ACS Nano , Nanoscale , and Journal of Physical Chemistry C , emphasizing precision fabrication and real-world applicability in energy and sensing. NSF CAREER Award (2011) ACS Pride Merck Graduate Student Award (mentored student, 2025) Multiple Outstanding Graduate Student Teacher Awards (mentored students, 2020–2023) NDIIF Best Publication Image Award (mentored student, 2023) Regional and State Science Fair Awards for high school interns (2020, 2023) Dr. Neretina actively mentors a large group of PhD students and undergraduate researchers, many of whom have gone on to successful careers in academia and industry. Her lab, the Nanomaterial Fabrication Research Laboratory, has secured ongoing funding to support graduate researchers and develop new instrumentation. She emphasizes scalable, manufacturable approaches to nanomaterial synthesis, aligning research with industrial needs. The lab frequently collaborates with external groups, such as Professor Eric Borguet at Temple University, on plasmonic sensing applications. The Nanomaterial Fabrication Research Laboratory develops and applies innovative techniques like dynamic templating and hybrid nanoimprint templating to fabricate periodic arrays of complex nanostructures. The lab is equipped with custom-built instrumentation and supports interdisciplinary research at the intersection of materials, chemistry, and engineering.
Research Fellow
Kha Nguyen is a post-doctoral researcher and Visitor (Faculty) in the Department of Neuroscience and Biomedical Engineering at Aalto University. He earned his Ph.D. in Chemical Engineering from National Taiwan University of Science and Technology in December 2016. Education: Doctoral degree in Engineering and Technology, National Taiwan University of Science and Technology (awarded December 1, 2016) Research Focus: Dr. Nguyen's research centers on the intersection of nanotechnology, biomedicine, and materials science with emphasis on nanoplasmonics, biosensors, molecular self-assembly, and DNA nanotechnology. His work explores how precisely engineered nanostructures can be developed for biomedical sensing applications, with particular attention to DNA origami techniques and plasmonic responses. Research Trends: Analysis of Dr. Nguyen's publication record reveals an evolving research trajectory from fundamental nanostructure development toward increasingly sophisticated biomedical applications. His work shows consistent focus on DNA-based plasmonic systems with growing emphasis on practical biosensing applications and stability enhancements. The interdisciplinary nature of his research bridges chemistry, physics, materials science, and biomedical engineering, with strong emphasis on solution-phase synthesis methods. Research Contributions: Principal investigator on multiple Academy of Finland-funded projects including "Photo-controlled active plasmonics" (2019-2023) and "DNA-based devices for detection and sensing of biomolecular interactions" (2017-2021) Active participant in international conferences on nucleic acid nanotechnology and DNA-based sensing systems Significant media coverage with 32 press mentions across diverse fields including electronics, sustainability, and biomedical applications Research Activities: Dr. Nguyen maintains an active research program focused on developing novel DNA-based nanomaterials for biomedical applications. His work involves extensive collaboration with researchers across multiple institutions, particularly in the development of chiral plasmonic systems and silica-mineralized DNA nanostructures. He has presented his research at numerous international venues, with particular emphasis on solution-based fabrication techniques for biomedical sensing applications.
Senior Lecturer
Andrej Savin is a Senior Lecturer in the Department of Electrical Engineering at Uppsala University, Sweden, where he conducts research in marine renewable energy systems, particularly wave energy converters (WECs). He is based at the Ångström Laboratory and is actively involved in the Lysekil wave energy research project. Position: Senior Lecturer Institution: Uppsala University Department: Department of Electrical Engineering Email: andrej.savin@angstrom.uu.se His research focuses on the mechanical and electrical design, structural integrity, and performance optimization of point-absorbing wave energy converters. Key areas include mooring dynamics, power take-off systems (e.g., Low-RPM Torque Converter), ice interaction, and numerical modeling of WEC behavior under extreme and irregular sea conditions. He also explores the integration of machine learning for predicting WEC motion in hybrid offshore energy systems. The recent publications highlight a strong trend in experimental validation, structural analysis, and system-level optimization of wave energy technologies. His work spans hydrodynamics, mechanical design, thermal management, and data analysis, contributing to the advancement of reliable and efficient marine energy solutions. Andrej Savin has not received any explicitly mentioned scientific awards in the provided text. He has supervised or collaborated with multiple researchers and students, though no formal advisees are listed. His work is supported through institutional research funding at Uppsala University, particularly within the wave energy research group. He contributes to both experimental and theoretical aspects of offshore energy systems, with a focus on real-world deployment challenges in the Baltic Sea. He is part of the wave energy research team at Uppsala University, centered at the Lysekil research site, which conducts full-scale testing of wave energy converters. This team investigates power generation, survivability, sensor integration, and environmental interactions of marine energy devices.
Associate Professor
Igor Paprotny is an Associate Professor at the Department of Electrical and Computer Engineering, University of Illinois at Chicago. As Faculty Research Director of the Nanotechnology Core Facility, he leads research in MEMS/NEMS, microscale robotics, and environmental sensing. PhD in Engineering Sciences (MEMS) from Dartmouth College, 2008 His research focuses on applying micro/nano-systems to airborne pathogen detection, microscale flight dynamics, photonic sensing, and physical computing paradigms. He has pioneered MEMS-based sensors for methane leak detection, coal mine safety, and real-time particulate monitoring. Recent publications highlight advancements in air-microfluidic circuits , carbon nanotube functionalization , and microscale robotics , reflecting interdisciplinary work at the intersection of Environmental Engineering , Biomedical Monitoring , and Wearable Sensor Technology . He directs the Micromechatronic Systems Laboratory (MSL) and the Air Microfluidic and Bio-surveillance Group (AMFBG) , with over 15 years of experience in MEMS design, energy harvesting, and distributed sensor networks.
Assistant Professor
Dieff Vital is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Illinois-Chicago , specializing in textile-based wireless power transfer and biomedical sensing systems. Previously served as a Bridge-to-the-Faculty scholar at UIC (2021-2023), focusing on microwave sensing of biological systems and electromagnetics-on-fabrics. Education : PhD in Electrical and Computer Engineering (2021), Florida International University; MS in Electrical and Computer Engineering (2020); B.Sc. Mechanical and Industrial Engineering (2017) from Florida Polytechnic University, graduating summa cum laude. His groundbreaking research includes bio-inspired antenna designs like the centipede-mimicking resonator for misalignment-resilient charging systems, with over 30 peer-reviewed publications and 5 patents. Key contributions to smart bandages, wearable sensors, and wireless charging infrastructure. Recent Trends : Development of clothing-integrated beamforming structures (2023), fluidically reconfigurable textile antennas for 5G/6G applications (2023), and biomimetic resonators for medical IoT charging (2022), demonstrating convergence of wearable tech with advanced electromagnetics. Honors : 2022 IEEE APS Fellowship 2021 URVI-GASS Young Scientist Award 2019 Paul Harris Fellow (Rotary International) 2022 IEEE RFID-TA 2nd Place Paper Prize Multiple NSF and IEEE travel grants Leadership : Active in IEEE technical committees (MTT-TC 26/28), session chair for wireless power transmission, and mentor in programs for underrepresented students in STEM. Holds patents for anchor-shaped antennas and smart wound-monitoring bandages.
Researcher
Dr. Ying Cheng is a Research Associate at the University of Newcastle, holding dual appointments in the School of Environmental and Life Sciences and the School of Architecture and Built Environment within the College of Engineering, Science and Environment. Her work focuses on developing innovative technologies for sustainable environmental remediation and energy recycling, with particular expertise in sensor development and green synthesized nanomaterials. Dr. Cheng earned her Doctor of Philosophy from the University of Newcastle, following a Master of Engineering from Fujian Normal University in China. Her undergraduate studies were completed at China Agricultural University, where she focused on soil aggregate and organic carbon stability in the North China plain. During her master's studies, she specialized in remediation of printing sewages using green synthesized nanomaterials and biomaterials, and her PhD research centered on the fabrication of biocompatible anode electrodes in Microbial fuel cells (MFCs) for sewage treatments and energy recovery. Her research spans multiple areas with sensor technology accounting for 70% of her focus, followed by environmental assessment and monitoring (10%), environmental nanotechnology (10%), energy generation (5%), and One Health (5%). She has developed green synthesized graphene-based nanocomposites and biomaterials for environmental applications, with particular expertise in creating functional materials that combine bacterial strains like Burkholderia species with nanomaterials for enhanced contaminant removal. Her primary research focus since graduation has been method development of rapid and reliable in-field detection and sensor invention for environmental risk assessment. Analysis of her recent publications reveals a strong trend toward integrating advanced sensing technologies with machine learning for environmental monitoring. Her work increasingly focuses on developing portable, field-deployable solutions for detecting contaminants like volatile organic compounds, arsenic, and petroleum hydrocarbons. Many of her studies combine nanomaterials with biological systems to create innovative remediation approaches, particularly for simultaneous removal of multiple contaminants from water systems. 33 peer-reviewed journal articles 1 book chapter 1 patent 6 research grants totaling $2,444,668 Dr. Cheng has secured significant research funding for projects focused on rapid field-based assessment methods for contaminated sites. Her collaborative work frequently involves researchers like Liang Wang and Ravi Naidu, with whom she has developed several field-deployable solutions that simplify environmental monitoring and make it more accessible. Her laboratory work centers on green synthesized nanomaterials for environmental applications, with established expertise in microbial fuel cells for wastewater treatment and energy recovery.
Professor
Dr. Sudharman K. Jayaweera is a Professor in the Department of Electrical and Computer Engineering at the University of New Mexico, Albuquerque, NM. He holds a PhD in Electrical Engineering from Princeton University (2003), an MS in Electrical Engineering from Princeton University (2001), and a BE in Electrical and Electronic Engineering with First Class Honors from the University of Melbourne, Australia (1997). He is a Senior Member of IEEE and serves as an editor for IEEE Transactions in Vehicular Technology. Dr. Jayaweera's research spans several key areas in modern communications and signal processing: Cognitive radios and autonomous learning systems Wireless communications and statistical signal processing Machine learning applications in communications Smart-grid technologies and cyber-physical systems Satellite communications and space networks Vehicular networks and distributed systems His recent work shows a clear trend toward integrating artificial intelligence with traditional communications systems, particularly focusing on UAV networks, spectrum management, and security aspects of cognitive radio systems. The publications reflect a strong emphasis on practical implementations of theoretical concepts, with applications ranging from smart grids to space communications. Dr. Jayaweera has received numerous scientific awards including the IEEE PACRIM 2011 Gold Award for Best Communications Paper, the IEEE AVSS '06 Best Paper Award, and the WPMC '03 Excellent Paper Award. He has also been recognized with fellowships including the National Research Council (NRC) Senior Fellow at the Naval Postgraduate School and ASEE Air Force Summer Faculty Fellow. As an advisor, Dr. Jayaweera has mentored numerous graduate students to completion of their PhD and MS degrees. His former students have gone on to successful careers at institutions including Syracuse University, SUNY Oswego, Qualcomm, Sandia National Labs, and other leading technology companies. He also directs the EYES Summer Internship program for international students at UNM. Dr. Jayaweera leads the Communications and Information Sciences Lab (CISL) and the Cognitive Radio Lab (CRL) at UNM, where his teams work on cutting-edge research in autonomous cognitive radios (which he terms "Radiobots"), machine learning for communications, and next-generation wireless systems.
Professor
Darko Stefanovic is a Professor of Computer Science (and courtesy faculty in Chemical & Biological Engineering) at the University of New Mexico. He has been continuously active in teaching and research since at least 2000, with a focus on programming languages, molecular computing, and scientific simulations. University: University of New Mexico Department: Department of Computer Science Academic Rank: Professor His research interests span molecular computing , DNA nanotechnology , and synthetic biology , with recent publications exploring applications in artificial β-cells , heterochiral translators , and reservoir computing with chemical systems . Many publications involve collaborations with researchers in biochemistry, nanotechnology, and systems biology. Teaching activities include numerous offerings of courses such as Compiler Construction , Programming Paradigms , Software Foundations , and Algorithms and Data Structures at both undergraduate and graduate levels. Course materials often emphasize functional programming (e.g., Standard ML), λ-calculus, and logic programming implementations. Recent publications (2025–2019) demonstrate ongoing work in molecular robotics , DNA-based computation , and synthetic cell engineering . These works frequently appear in venues related to biomolecular computing , nanotechnology , and synthetic biology . Teaching Career spans multiple decades at UNM, covering topics from foundational programming to advanced compiler construction. Course materials show emphasis on formal methods, programming language theory, and computational models, including implementations of λ-calculus interpreters and Prolog systems.
Associate Professor
Dr. Balázs Rakos is an Associate Professor at the Budapest University of Technology and Economics (BME), affiliated with the Department of Automation and Applied Informatics . His research bridges nanotechnology, biophysics, and optical computing. His work focuses on: Integrating photoswitchable proteins with photonic devices for optical computing Developing infrared energy harvesting systems using nanoantennas and MIM diodes Modeling dipole-dipole and Coulomb-coupled protein arrays for molecular electronics Designing self-adapting pixel antenna systems for dynamic signal processing His publications from 2025–2015 reveal a trajectory from infrared sensor technologies to biophotonics and renewable energy applications , with a recurring emphasis on nanoscale biomolecular systems .
Researcher
Dr. Volkmar Schultze is a Researcher in the Quantum Systems Work Group Quantum Magnetometry at the Leibniz Institute of Photonic Technology (Leibniz-IPHT) in Jena, Germany. His work focuses on developing high-resolution magnetic field sensors using optically pumped magnetometers (OPMs) and superconducting quantum interference devices (SQUIDs) for applications in geomagnetic prospection (e.g., archaeometry) and biomedical investigations (e.g., magnetoencephalography). His research spans sensor design, noise reduction, and orientation error compensation. Key contributions include innovations in light-shift dispersed Mz (LSD-Mz) mode and heading error mitigation in Earth’s magnetic field. He collaborates on magnetorelaxometry imaging and quantum-limited resolution systems, with a focus on eliminating magnetic shielding requirements. Recent publications highlight advancements in portable OPM systems (2022), dead-zone-free sensors (2023), and spin-exchange relaxation suppression (2016). His work bridges quantum physics , applied instrumentation , and cross-disciplinary applications in geophysics and medicine. Labs & Teams : He collaborates with interdisciplinary teams at Leibniz-IPHT, including co-authors like Gregor Oelsner, Christian B. Schmidt, and Ronny Stolz. His work integrates theoretical modeling (e.g., density-matrix simulations) with experimental sensor development.
Researcher
Anasua Chatterjee is a researcher at the Center for Quantum Devices, part of the Niels Bohr Institute at the University of Copenhagen. Her work focuses on quantum dot arrays, spin qubits, and semiconductor-based quantum computing platforms. She collaborates with leading quantum research groups and contributes to advancements in quantum device calibration, optimization, and noise mitigation. Affiliation: Center for Quantum Devices, Niels Bohr Institute, University of Copenhagen Her research spans quantum device automation, charge sensing, and real-time control of qubit fluctuations. Recent publications highlight her expertise in radio-frequency reflectometry, gate voltage optimization, and topological superconductivity in hybrid devices. Key article trends include autonomous calibration of quantum dots using evolutionary algorithms, spin qubit control via FPGA-based feedback systems, and integration of superconducting elements with semiconductor platforms. These studies often involve collaborations with institutions in the U.S. and Europe. While no formal awards are listed in the provided texts, her work appears integral to scaling quantum processors and improving qubit coherence for fault-tolerant systems.
Assistant Professor
Dr. Marissa Wechsler, a first-generation Hispanic biomedical engineer, returned to her alma mater The University of Texas at San Antonio (UTSA) in 2021 as an Assistant Professor in the Margie and Bill Klesse College of Engineering and Integrated Design. As UTSA's first biomedical engineering undergraduate student (class of 2015), she now leads a 12-member research team in her biomaterials and cell engineering lab while teaching advanced courses like BME 4443: Stem Cell Engineering. Academic Journey: UTSA BME program pioneer (2015) → NSF Graduate Research Fellowship → Ph.D. from UT Austin Leadership Roles: Founding faculty member of UTSA Sigma Xi chapter (2023), SWE faculty advisor, ESTEEMED mentor Research Focus: Specializes in biomaterials engineering with emphasis on: Stimuli-responsive hydrogels for drug delivery and tissue regeneration Stem cell engineering through controlled microenvironments Biosensing platforms using nanoparticle-hydrogel hybrids Regenerative medicine applications for vascular diseases Recent publications demonstrate expertise in RNA-based vaccine delivery systems , nanoparticle engineering , and mitochondrial dysfunction analysis in peripheral artery disease. Her work combines material science innovation with clinical translation potential. Award Highlights: 2023: Sigma Xi Grant-in-Aid of Research 2021: National Science Foundation Graduate Research Fellowship (during studies) Mentorship Impact: As a former participant in federal research programs (RISE, MARC), she now mentors through: Leading 12-member research team (undergraduate to postdoctoral) Sigma Xi leadership (President-elect) Faculty advisor for Society of Women Engineers ESTEEMED program mentor
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