Mark Hebblewhite is a Professor in Ungulate Ecology at the Wildlife Biology Program, University of Montana. His research integrates ecological theory with applied wildlife management, focusing on species like elk, wolves, and grizzly bears. Institution: University of Montana Academic Rank: Professor Research Interests span: Wildlife-habitat interactions Predator-prey dynamics Conservation of endangered species Remote sensing for forest and wildlife monitoring Climate change impacts on ecosystems Recent Publications emphasize: Multi-scale movement ecology Remote sensing integration for forest inventory Anthropogenic effects on wildlife behavior Fire ecology and post-disturbance recovery LiDAR and satellite-based vegetation mapping Collaborations include researchers from the University of Alberta, University of British Columbia, Colorado State University, and the Wildlife Conservation Society.
Bernard Doudin is a Professor at the University of Strasbourg, working with the Magnetic Objects on the NanoScale (DMONS) group at the Institute of Physics and Chemistry of Materials of Strasbourg (IPCMS). He holds office 1014 and can be contacted at bernard.doudin@ipcms.unistra.fr. Doudin has been actively coordinating several major research initiatives including STnano Coordinator for Innovative Training Networks, Coordinator of the Graduate School Quantum Science and Nanomaterials QMat, and Coordinator of the Interdisciplinary Thematic Institute Quantum Science and Nanomaterials. Doudin's research focuses on nanoscale devices that leverage the spin degree of freedom, with expertise spanning spintronics, 2D electronic detectors, multi-stimuli devices, and magnetic forces at the nanoscale. His work bridges physics, materials science, and chemistry, exploring applications in molecular electronics, nanofluidics, and electrochemistry. He has pioneered original systems and concepts in spintronics, evolving toward multifunctional devices that take advantage of quantum properties at the nanoscale. Analysis of his recent publications (2022-2025) reveals a strong focus on van der Waals heterostructures, magnetic microhydrodynamics, and graphene-based spintronic devices. His research shows a clear trend toward integrating multiple physical phenomena (magnetic, electrical, optical) in single devices, with particular emphasis on neuromorphic computing applications, magnetically controlled fluid dynamics, and photoferroelectric effects. The publications demonstrate interdisciplinary collaboration across physics, materials science, and engineering disciplines. PhD prize of the University of Lausanne (top 2%) NSF Career grant (1998) Adjunct Director of the NSF MRSEC Center (2000) Chaired Professor of the French Ministry (2005) Fellow of the University of Strasbourg International Studies (2014) Fellow of the Institut Universitaire de France (Senior, 2021) Professor Doudin has secured significant research funding and coordinates multiple large-scale projects including the Innovative Training Networks Marie Skodowska-Curie actions and the Graduate School Quantum Science and Nanomaterials. His leadership extends to scientific direction of cleanroom facilities and interdisciplinary research initiatives that bring together approximately 50 principal investigators across various quantum science and nanomaterials projects. Doudin leads research activities at IPCMS, particularly within the DMONS group focusing on magnetic phenomena at the nanoscale. His work integrates experimental approaches across spintronics, nanofabrication, and materials characterization, with strong connections to both fundamental physics and potential applications in next-generation electronic devices.
Dr. Andy Nguyen is a Senior Lecturer in the School of Engineering at the University of Southern Queensland. He holds a PhD from Queensland University of Technology (QUT), an MEng from the National University of Civil Engineering (NUCE), and a BEng from NUCE. His research focuses on structural health monitoring, integrating machine learning and deep learning techniques to assess infrastructure integrity. Key areas include damage detection in bridges, pavements, and buildings, as well as sustainable construction materials like bamboo. Nguyen leads projects such as the 'Next Generation Living Laboratory for Engineering Education and Engagement,' emphasizing real-world applications of technology in civil infrastructure. His work spans crack detection algorithms, finite element model updating, and vibration-based structural analysis. He collaborates on AI-driven solutions for autonomous vehicle object detection and smart maintenance planning. Nguyen’s contributions include over 50 peer-reviewed publications and active supervision of postgraduate research in composite materials and transport infrastructure. His research outputs highlight advancements in computational mechanics, sensor technologies, and data-driven methods for infrastructure resilience. Nguyen’s expertise bridges civil engineering challenges with cutting-edge machine learning, advancing both theoretical and applied solutions for sustainable and safe structures.
Marco Paggi is a Full Professor of Structural Mechanics at the IMT School for Advanced Studies Lucca, Italy, since 2017. He previously held academic roles at Politecnico di Torino (Assistant Professor, 2007-2013) and has been an Alexander von Humboldt Fellow at Leibniz University Hannover. His research focuses on fracture mechanics, contact mechanics, and computational methods applied to renewable energy systems, composite materials, and multi-scale modeling. Key Themes: Fracture propagation, contact interfaces, phase field modeling, photovoltaic durability, and material heterogeneity. Awards: Stanford Top 2% Scientists (2020-2024) Research.com Top Scientists (2022-2024) European Structural Integrity Society Young Scientist Award (2010) Publications: His work spans tribology, computational fracture mechanics, and material degradation, with recent emphasis on phase field modeling for quasi-brittle materials and photovoltaic systems. He has pioneered methods for multi-scale and multi-physics analysis of structural systems. Mentorship: Supervised 17 PhD graduates and 14 postdocs, including award-winning researchers like Pietro Lenarda and Zeng Liu.
Trevor E. Carlson is an Assistant Professor at the School of Computing, National University of Singapore (NUS), focusing on high-efficiency microarchitectures, hardware/software co-design, and secure chip design for IoT and server applications. He earned his Ph.D. in Computer Science from Ghent University (2014) and B.Sc./M.Sc. in Electrical & Computer Engineering from Carnegie Mellon University (2002/2003). Research Interests include energy-efficient processors, secure computing platforms, neuromorphic accelerators, and fast simulation methodologies. He co-developed the Sniper Multi-Core Simulator used globally for performance/power evaluation. Scientific Awards : Best Paper Award, International Conference on Embedded Computer Systems (2016) Best Paper Award, International Symposium on Performance Analysis of Systems and Software (2013) Heidelberg Laureate Forum participation (2015) HiPEAC Technology Transfer Award for Sniper Simulator (2013) Current Research involves secure Systems-on-Chip (SOCure project), hardware security for IoT, and simulation methodologies. He leads a lab with researchers working on topics like Capstone for trustless secure memory access and LABS for laser fault injection benchmarks.
Charles Rizzo is a Research Assistant Professor in the TENNLab neuromorphic computing group at the University of Tennessee, Knoxville, within the Department of Electrical Engineering and Computer Science. He earned his PhD in Computer Science (2024), MS (2021), and BS (2019) from the same institution. PhD in Computer Science, University of Tennessee, Knoxville (2024) MS in Computer Science, University of Tennessee, Knoxville (2021) BS in Computer Science, University of Tennessee, Knoxville (2019) His research focuses on neuromorphic computing, particularly for embedded applications involving event-based vision processing and machine learning with spiking neural networks. He has contributed to neuromorphic control systems, event camera data processing, and spiking network architectures. Recent publications emphasize neuromorphic hardware design (e.g., memristor-based synapses, RISP neuroprocessor), algorithm adaptation (DBSCAN clustering), and real-time applications in vision processing and control. Key subfields include event-based sensors, recurrent spiking networks, and low-power embedded systems. Charles is affiliated with the TENNLab neuromorphic computing group and supports course website development for EECS programs. His work bridges neuromorphic theory with practical implementations in embedded environments.
Albert H. Titus is a Professor in the Department of Biomedical Engineering and an Adjunct Professor in the Department of Electrical Engineering at the University at Buffalo, State University of New York. He serves as Associate Vice President for Regulatory Support in the Office of the Vice President for Research and Economic Development. His research focuses on analog VLSI design for neuromorphic visual processing, biosensors, wearable devices, optoelectronic systems, and neural networks. Education: PhD in Electrical and Computer Engineering, Georgia Institute of Technology (1997) MS in Electrical Engineering, University at Buffalo (1991) BS in Electrical Engineering, University at Buffalo (1989) Research Interests: His work spans wearable and implantable sensors, bioinstrumentation, neural network-based visual processing, analog VLSI implementations, optoelectronics, and electronic packaging. He pioneered CMOS-based neuromorphic systems and developed patented technologies for glare sensing and RF power calorimetry. Publication Trends: His recent articles emphasize CMOS-integrated sensors, machine learning for bioimpedance analysis, implantable medical devices, and xerogel-based optical biosensors. These works bridge biomedical engineering and microelectronics. Scientific Recognition: He is a Fellow of the National Academy of Inventors and has received the SUNY Chancellor’s Award for Excellence in Service (2017), NSF CAREER award, and Western New York Inventor of the Year (2010). His inventions include a patented low-power glare sensor (U.S. Patent 7,586,079) featured in Popular Science’s 2011 Top Ten Inventions. Academic Leadership: As a faculty member, he has supervised nearly 20 PhD and over 40 MS students, while teaching courses in circuits, IC design, sensors, and signal processing across electrical and biomedical engineering disciplines.
Dr. Morteza Ghorbani is a researcher and faculty member at Sabancı University's Faculty of Engineering and Natural Sciences (FENS), specializing in fluid mechanics and environmental engineering. He leads the AquaCav project, a collaborative effort with Oxford Brookes University, focused on developing sustainable water treatment solutions using hydrodynamic and acoustic cavitation. His research addresses global challenges such as PFAS pollution and wastewater management, with applications in biomedical devices and energy-efficient technologies. Key collaborations include projects funded by the International Science Partnership Fund (ISPF), leveraging his expertise in microfluidic systems and cavitation dynamics. Dr. Ghorbani's work combines experimental and numerical methods to optimize cavitation-based processes for environmental and biomedical applications. His contributions span from fundamental fluid dynamics studies to applied technologies like flexible cystoscopes and clot-on-a-chip platforms. Scientific achievements include the ISPF Research Collaboration Grant (2024) and advancements in PFAS removal, graphene exfoliation, and microalgae cultivation. His research group at Sabancı University explores interdisciplinary solutions at the intersection of engineering, nanotechnology, and sustainability.
Kimia Zamiri Azar serves as an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Central Florida, focusing on hardware security and verification methodologies. Her research bridges theoretical formal methods with practical security implementations in semiconductor design and testing. Her educational background includes: Ph.D. in Electrical and Computer Engineering, George Mason University (2021) Postdoctoral Research, University of Florida Dr. Azar's research spans hardware security with emphasis on system-level verification, VLSI design-for-trust, and advanced IC testing. She pioneers techniques in logic locking, secure heterogeneous integration, and IC supply chain security, developing frameworks for authenticated encryption in Systems-in-Package and runtime security monitoring. Her work integrates formal verification with innovative testing methodologies to address hardware trust challenges across the semiconductor lifecycle. Analysis of her recent publications reveals two dominant trends: (1) Application of large language models (LLMs) to hardware design tasks including high-level synthesis code generation and RTL optimization, and (2) Advancement of secure heterogeneous integration techniques for System-in-Package architectures with focus on counterfeit prevention and split-test security protocols. These directions address critical gaps in hardware trustworthiness amid increasingly complex semiconductor supply chains. Her scientific contributions have earned significant recognition: Best Paper Award at ICCAD 2019 Best Paper Award at ISVLSI 2020 Best Paper Award at ICCAD 2020 Best Paper Award at IEEE DCAS 2020 Best Paper Award at HOST 2022 Best Paper Award at DATE 2023 Dr. Azar secures substantial research funding from premier agencies including NSF, SRC, DARPA, AFRL, DoD (NG), and Microsemi. Her grants support projects spanning hardware security validation frameworks, secure heterogeneous integration, and AI-augmented verification methodologies. She actively mentors students in her research group, guiding publications in top venues like IEEE D&T, IEEE TC, and DAC while fostering industry-academic collaborations. Her work directly impacts semiconductor security standards through patented innovations and open-source verification tools. As an active IEEE and ACM member, she contributes to community advancement through conference organization (HOST, DATE), journal editorial roles, and workshop leadership on hardware security standards. Her research group collaborates with semiconductor industry leaders to translate theoretical security frameworks into practical design-for-trust methodologies for next-generation integrated circuits.
Prof. Dr. Roland Zengerle serves as Full Professor for Application Development at the Institute of Microsystems Technology within the Faculty of Engineering at Albert Ludwigs University of Freiburg, concurrently holding the position of Director at Hahn-Schickard Institute for Microanalysis Systems in Freiburg. His academic leadership spans microsystems engineering with a focus on translational research bridging fundamental science and clinical applications. Zengerle's research expertise centers on Microfluidics, Lab-on-a-Chip systems, Bio-MEMS, Electrochemical Energy Systems, and Tomographic Reconstruction of Mesoporous Materials. He pioneers hybrid manufacturing techniques integrating molten metal printing with polymer processing to develop point-of-care diagnostic platforms and advanced energy systems. Current projects include UTI-Diag for urinary tract infection diagnosis and PhotonMed, a 32-million-euro medical technology initiative where his MEMS Applications Laboratory develops centrifugal microfluidic solutions. Analysis of his recent publications reveals a dominant trend toward multi-technology integration: centrifugal microfluidics combined with 3D bioprinting for organoid-based drug testing, molten metal printing for flexible electronics, and bead-based immunoassays for infectious disease detection. The work demonstrates strong clinical translation focus, particularly in cancer diagnostics (circulating tumor cell isolation), infectious disease testing (TB diagnostics), and regenerative medicine (spheroid/organoid handling). His laboratory has secured significant funding for high-impact projects including: UTI-Diag: Molecular diagnostics for urinary tract infections PhotonMed: Medical technology innovation consortium livMatS: Living, Adaptive and Energy-autonomous Materials Systems Zengerle actively mentors researchers through Freiburg's Master Lab program and Writer's Studio initiative while promoting young talent via Bootcamp training. His group maintains strategic alliances with Hahn-Schickard spin-offs and industry partners, leveraging university cleanroom facilities and specialized service centers for microfabrication. The MEMS Applications Laboratory operates as a hub for interdisciplinary innovation, combining microfabrication expertise with clinical insights to develop commercializable diagnostic solutions. Current infrastructure supports centrifugal microfluidic cartridge development, 3D-bioprinting of tissue models, and electrochemical sensor integration, with ongoing work focused on automating complex biological workflows for point-of-care applications.
Dr. Amina Stoddart is a Professor at Dalhousie University specializing in water quality and treatment technologies. She leads the NSERC Industrial Research Chair in Water Quality and Treatment and co-leads the Nova Scotia Pilot Monitoring Program for Lead in Drinking Water. Her research focuses on UV LED disinfection systems, biofiltration for manganese control, and pandemic-related wastewater monitoring. She has received the NSERC Discovery Grant (2019) and AWWA ACE Conference Poster Competition awards. Key Projects: NSERC Industrial Research Chair in Water Quality and Treatment, Lead Monitoring Program. Awards: NSERC Discovery Grant, AWWA Poster Competition. Her work bridges environmental engineering and public health, addressing challenges like nanoplasic mitigation, viral detection in wastewater, and sustainable water treatment. She supervises multiple PhD and MASc students in these areas.
Ivan Selesnick is a Professor of Electrical and Computer Engineering at the NYU Tandon School of Engineering, with joint appointments in Biomedical Engineering and Radiology. He holds affiliations with the Center for Advanced Technology in Telecommunications (CATT) and leads the Selesnick Lab. His research focuses on signal and image processing, sparse signal models, wavelet analysis, and biomedical applications. He received his degrees from Rice University (BS, MEE, PhD in EE) and has been recognized with prestigious awards including the Alexander von Humboldt Fellowship (1997), NSF Career Award (1999), and IEEE Fellow (2016). Education: BS, MEE, and PhD in Electrical Engineering from Rice University (1990, 1991, 1996). He joined NYU Tandon in 1997 and served as a visiting professor at the University of Erlangen-Nuremberg in 1997. Research Interests: Signal Processing, Sparse Signal Models, Wavelet Analysis, Biomedical Signal Processing, and Optimization Techniques. His work emphasizes applications in medicine, imaging, and engineering systems. Awards: In addition to his fellowships, he received the Jacobs Excellence in Education Award (2003) and the Budd Award for Best Engineering Thesis (1996). He has held editorial roles at IEEE Transactions on Image Processing, Signal Processing Letters, and Computational Imaging. Teaching: Courses include Signals, Systems, and Transforms (EE 3054), Digital Signal Processing I/II (EL 6113/EL 7133), Wavelets and Filter Banks (EL 7163), and Biomedical Signal Processing (EL 9133). Labs and Affiliations: Director of the Selesnick Lab, involved in NYU Tandon Future Labs (business incubators) and CATT (telecommunications research). His research spans biomedical sensing, radar signal processing, and algorithm development for medical diagnostics.
Jian Liu is an Assistant Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. He leads the Mobile Sensing and Intelligence Security (MoSIS) Lab, focusing on robust AI, mobile security, computational sensing, and smart healthcare. His research has been published in top-tier venues like S&P/Oakland, CVPR, and IEEE journals, with over 6,400 citations. He holds seven U.S. patents, including two licensed to industry. Education: PhD in Electrical and Computer Engineering from Rutgers University (2019), ME and BE in Communication Engineering from Wuhan University of Technology (China). Research interests include trustworthy AI, federated learning, privacy-preserving technologies, and adversarial machine learning. His recent work includes HarmonyCloak (music copyright protection against generative AI), 3D facial authentication systems, and robust backdoor attack defenses. Notable awards include the University of Tennessee’s Professional Promise in Research Award (2025), Stanford’s World’s Top 2% Cited Scientists, and multiple best paper awards. He teaches Mobile and Embedded System Security (ECE 469/569) and has supervised projects funded by UT Grand Challenges grants. Labs/Teams: MoSIS Lab focuses on AI-driven security solutions, wearable sensing, and healthcare applications. Collaborations involve interdisciplinary projects with UT’s engineering and medical schools.
Mohan Qin is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of Wisconsin–Madison. Her research focuses on developing novel approaches for resource recovery from waste streams and the concentration and detection of microplastics in the Great Lakes. Dr. Qin received her educational degrees as follows: Ph.D. in Civil Engineering from Virginia Tech (2017) M.S. in Environmental Engineering from Peking University (2013) B.S. in Environmental Engineering from Shandong University (2010) Her primary research areas include: Bioelectrochemical systems for resource recovery from wastewater Environmental biotechnology for sustainable wastewater treatment Electrochemical processes for desalination and water treatment Membrane-based technology for selective ion removal Her work particularly emphasizes ammonia recovery from manure and wastewater, and the detection of microplastics in freshwater systems, contributing to sustainable water management and resource conservation. Analysis of Dr. Qin's recent publications (2022-2025) reveals a strong focus on ammonia recovery using membrane and electrochemical systems, with increasing attention to microplastics detection in lake water. Her work spans from fundamental transport mechanisms to practical applications in dairy manure treatment and Great Lakes monitoring, often integrating novel sensor technologies and renewable energy sources. Dr. Qin has received numerous awards, including: 2024 IWA Membrane Technology Specialist Group (MTSG) Rising Star Award 2024 University of Wisconsin-Madison Hilldale Undergraduate/Faculty Research Fellowship 2023 UW-Madison Media Fellow and Sustainability Fellow 2022 UW-Madison Madison Teaching and Learning Excellence (MTLE) Fellow Multiple awards during her graduate studies at Virginia Tech Dr. Qin actively mentors students through thesis and independent study courses (CIV ENGR 890, 990, 699) and has been awarded the Hilldale Fellowship for undergraduate research collaboration. Her research is supported by several fellowships including the UW-Madison Sustainability Fellow and Media Fellow, which likely fund her innovative work in resource recovery and microplastics detection. She leads a research group at UW-Madison focused on environmental biotechnology and electrochemical systems, collaborating with institutions like Yale University (where she completed her postdoc) and contributing to journals as an associate editor for Desalination and Water Treatment and on the early career editorial board of ACS ES&T Engineering.
Karan Ahuja is the Lisa Wissner-Slivka & Benjamin Slivka Assistant Professor of Computer Science at Northwestern University, directing the Sensing, Perception, Interactive Computing & Experiences (SPICE) Lab. He earned his Ph.D. in Human-Computer Interaction from Carnegie Mellon University (2023) and a B.Tech. in Computer Science (2017). His research focuses on creating technologies that sense and understand human behavior, with applications in mobile health, extended reality, and natural user interfaces. Key projects include LemurDx for ADHD diagnosis, EITPose for wearable hand pose tracking, and MobilePoser for full-body pose estimation via consumer IMUs. Awards include Forbes 30 Under 30 (2024), MIT 35 Innovators Under 35 Asia Pacific, and ACM SIGCHI's Outstanding Dissertation Award. He has worked at Google, Apple, Microsoft Research, Meta Reality Labs, and IBM Research. His lab emphasizes real-world deployments, with technologies licensed and integrated into products used by millions. Prospective students are invited to join his lab at Northwestern via a dedicated application form. Research spans embedded systems, computer vision, and on-device ML, with a focus on impactful applications in healthcare and XR.
