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Andrea FaliniView profile

Professor

• Advanced MR Techniques
• Neuro-oncology
• Degenerative Diseases
• +3 more

Andrea Falini is a Full Professor of Neuroradiology at the Vita-Salute San Raffaele University (School of Medicine). He holds leadership roles including Head of the Neuroradiology Department at the Scientific Institute S. Raffaele Hospital and Head of the Advanced Diagnostic in Neuro-oncology Unit. His career spans clinical, academic, and administrative roles since 1991, with extensive experience in neuroradiology, neuro-oncology, and neuroimaging research. Education: MD (1986, University of Milan), PhD in Neurological Sciences (1989), and specialized training in Neurology and Radiology at leading institutions, including a visiting scholar position at UCSF (1996). Research interests focus on advanced MRI techniques, neuro-oncology, neurodegenerative diseases, and cognitive neuroscience. His work emphasizes functional MRI, diffusion tensor imaging, and clinical applications in glioma management and neurodegenerative disorders. Awarded the 1989 'De Visart' Prize and grants supporting his international collaborations. He has authored 218+ peer-reviewed articles, with an H-index of 40+, and actively contributes to academic committees and international conferences. Leadership roles include Vice-Director of the Neuroscience Division (2014–present) and coordination of the BraiMap Research Program. His academic teaching spans neuroradiology, biomedical engineering, and cognitive neuroscience courses.

• Structural Health Monitoring
• Computer Vision
• Artificial Intelligence
• +3 more

Roya Nasimi, Ph.D., is an Assistant Professor in the Department of Engineering at California State University, East Bay, where she joined in Fall 2023. Her expertise spans structural engineering, computer vision, and artificial intelligence, with a focus on developing innovative solutions for infrastructure monitoring and safety. Dr. Nasimi's educational background includes: Ph.D. with distinction in Structural Engineering from the University of New Mexico Master’s degree in Structural Engineering from the University of Tabriz Bachelor’s degree in Civil Engineering from the University of Tabriz Her research focuses on structural health monitoring using advanced technologies. She integrates computer vision , artificial intelligence , and machine learning to develop systems for monitoring aging infrastructure, particularly bridges. Her work includes designing low-cost and high-end sensor systems, conducting full-scale bridge experiments, and collaborating on interdisciplinary projects to enhance infrastructure safety and resilience. Her recent publications (2021-2025) demonstrate a strong emphasis on non-contact monitoring techniques using drones, lasers, and computer vision. Key trends include the application of deep learning for displacement measurement, digital twinning for infrastructure, and rockfall prevention through machine learning. Her work bridges civil engineering with cutting-edge technology to address critical infrastructure challenges. Dr. Nasimi's research is supported by multiple grants: U.S. Army Corps of Engineers Transportation Research Board (TRB) Transportation Consortium of South-Central States (Tran-SET) New Mexico Consortium She serves on two TRB standing committees and mentors students in structural health monitoring and infrastructure technology. Dr. Nasimi leads interdisciplinary research teams focused on infrastructure monitoring, utilizing drones, lasers, and computer vision systems. Her work involves field experiments on bridges and rail systems, often in collaboration with government agencies and research consortia.

• Virtual Reality
• Human-Computer Interaction
• Computer Vision
• +4 more

Robert S. Allison is a Professor in the Department of Electrical Engineering & Computer Science at York University's Lassonde School of Engineering. His research focuses on human perceptual responses in virtual environments, stereoscopic vision, and eye movement analysis. He is affiliated with the York Centre for Vision Research, Sensorium (Digital Arts & Technology), and the Centre for Innovation in Computing at Lassonde. His research interests include depth perception in natural and virtual environments, human-computer interface design for VR, machine vision applications, and the measurement of human motion. He has supervised multiple graduate students and contributed to over 260 publications. His work spans topics like cybersickness mitigation, display lag effects, and perceptual adaptation in VR. Key grants include NSERC-funded projects on perception in virtual environments and collaborations with institutions like the Australian Research Council. His teaching includes courses on human perception in human-computer interaction and digital logic design. Recent articles highlight advancements in understanding motion perception, VR-induced sickness, and multisensory integration. He collaborates widely, with affiliations including the VISTA program and York's Connected Minds initiative.

• Biomedical Engineering
• Nanotechnology
• Cancer Research
• +3 more

Yen-Cheng Liu is a former researcher at École polytechnique fédérale de Lausanne (EPFL), affiliated with the School of Life Sciences (BIOS) and multiple departments including LCOM and CMI. His work focuses on interdisciplinary research at the intersection of biomedical engineering, nanotechnology, and cancer biology. Key research areas include nanoplasmonic biosensors, single-cell analysis, optofluidic systems, and cancer immunology. He holds collaborations with institutions like the University of Lausanne and the Centre Hospitalier Universitaire Vaudois (CHUV). His research emphasizes real-time monitoring of cellular secretions, tumor microenvironment dynamics, and diagnostic platform development for pathogens and genetic diseases. Notable contributions include high-throughput microarray technologies for single-cell secretion profiling and optofluidic platforms for molecular diagnostics. Liu’s publications span journals like Advanced Science , Advanced Functional Materials , and Biosensors and Bioelectronics . His work integrates engineering principles with biological systems to address challenges in precision medicine and cancer therapy.

Nabil BassimView profile

Associate Professor

• Materials Science
• Electron Microscopy
• Nanomaterials
• +3 more

Nabil Bassim is an Associate Professor in the Department of Materials Science and Engineering at McMaster University and serves as Scientific Director of the Canadian Centre for Electron Microscopy (CCEM). His research focuses on advanced electron microscopy techniques, ion microscopy, nanofabrication, and beam-sample interactions, applied to nanomaterials, 2D materials, and structural materials like concrete and alloys. He holds a B.S. in Mechanical Engineering from the University of South Florida, and M.Sc. and Ph.D. degrees from the University of Florida. Research interests include: Development of novel electron/ion microscopy techniques Nanomaterial synthesis and characterization Beam-induced damage and doping mechanisms Structural materials analysis Machine learning optimization for microscale processes Recent publications demonstrate strong focus on semiconductor characterization, nanomaterials synthesis, and advanced microscopy techniques. Article trends highlight innovative approaches to nanoscale analysis, materials for energy applications, and correlative microscopy methods. As Faculty Lead for McMaster Engineering's Aerospace and Defense Initiative, Dr. Bassim coordinates interdisciplinary research. He co-founded the FIB-SEM User Meeting and teaches graduate courses in electron/ion microscopy characterization techniques.

• Polymer Science
• Inorganic Chemistry
• Nanotechnology
• +7 more

Ulrich B. Wiesner is the Spencer T. Olin Professor of Engineering at Cornell University since 2008, with a career spanning over two decades in polymer-inorganic hybrid nanomaterials. His work bridges materials science, chemistry, and biomedical engineering, focusing on block copolymer self-assembly for multifunctional materials. Education: Diploma in Chemistry (University of Mainz, 1988), Ph.D. in Physical Chemistry (University of Mainz & MPI-P, 1991) Research Interests center on combining soft polymeric materials with inorganic/solid-state chemistry to create hierarchical hybrid materials. Key areas include: Energy conversion and storage via mesoporous oxides/non-oxides Clean water technologies through advanced materials Nanomedicine applications in cancer therapy and bioimaging Development of C-dots: ultrasmall fluorescent silica nanoparticles Structure-directing agents from dendron architectures His article trends reveal a focus on asymmetric porous structures (2024-2025), 3D-printed quantum materials (2024), and biomedical applications of C-dots for super-resolution microscopy and targeted drug delivery (2023-2025). Scientific Awards include: National Academy of Inventors Fellow (2024) "Ambassadeur pour la Chimie Française" (2019) Arthur K. Doolittle Award (2016) ACS PMSE Fellow (2015) NSF Creativity Award (2008) Cornell Teaching Excellence Award (2005) IBM Faculty Partnership Award (2001) Carl Duisberg Memorial Award (1999) As co-director of the MSKCC-Cornell Center for Translation of Cancer Nanomedicine (2015-present), he leads interdisciplinary teams developing clinical nanoparticle probes. His work has produced >250 peer-reviewed publications and numerous patents, with recent breakthroughs in antibody fragment-nanoparticle therapeutics for gastric cancer eradication.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +12 more

Hao Liu is a researcher affiliated with institutions like Chinese Academy of Sciences , Beihang University , and Stanford University . His work spans Computer Science , Artificial Intelligence , and Robotics . Key affiliations: National Space Science Center (Beijing), School of Astronautics (Beihang), Key Laboratory of Pervasive Computing (Tsinghua) Research interests include Machine Learning , Image Processing , Graph Neural Networks , and Wireless Communication Optimization His recent publications focus on: Advanced control systems for fuzzy models Medical imaging via hyperspectral analysis Transformer-based approaches in NLP and vision Quantum-safe and edge computing protocols

• Machine Learning
• Computer Vision
• Signal Processing
• +6 more

Dongwook Kim is affiliated with the Korea Advanced Institute of Science & Technology (KAIST) as a faculty member in the Department of Business and Technology Management under the College of Business. His research spans multiple domains including machine learning, robotics, signal processing, and biomedical engineering. Key contributions in Computer Vision (CNN-based semantic segmentation, 3D point cloud analysis) Significant work in Hardware Design (energy-efficient processors, neuromorphic computing) Interdisciplinary expertise in Medical Imaging (bone age assessment, retinal biomarkers) and Cybersecurity (attack detection, network analytics) Publications since 2015 demonstrate sustained innovation in AI applications , Signal Processing , and Smart City Governance . His work often integrates theoretical advances with practical implementations in real-world systems. No scientific awards or student mentorship details are explicitly documented in the provided records.

Benyamin DavajiView profile

Assistant Professor

• Integrated Microsystems
• MEMS
• Nanofabrication
• +4 more

Benyamin Davaji serves as an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University, where he joined in January 2022. He holds additional appointments as a Center Member of The Plastics Center and Core Faculty of the Institute for NanoSystems Innovation (NanoSI). His work bridges microsystems engineering, nanofabrication, and data science to develop next-generation sensing technologies. Dr. Davaji's educational background includes: Postdoctoral Associate in Electrical and Computer Engineering at Cornell University (2016-2021) Ph.D. in Electrical Engineering from Marquette University (2016) His research centers on integrated microsystems with emphasis on mechanical wave-based sensing and computation, ultrasound transducers, bio-interfaces, and microcalorimetry. The Autonomous Integrated Microsystems (AIMS) Laboratory combines physics with AI/ML to invent novel sensors and computational devices through advanced nanofabrication. Key thrusts include power-sustaining architectures and analog/digital computational integration. Recent publications (2024-2025) reveal strong trends in MEMS/NEMS optimization using digital twins, plasmonically enhanced infrared detection, ferroelectric actuators for high-speed scanning, and ultrasound-enabled metrology. His work increasingly integrates machine learning for design automation and process optimization across semiconductor manufacturing and flexible hybrid electronics. Dr. Davaji advises graduate students including Yilmaz Arin Manav (PhD'28), who won the FLEX 2024 Future Student Poster Award. He has secured over $3 million in competitive funding as PI/Co-PI, including a $550k NSF grant for MEMS actuators, $330k NSF grant for quantum detectors, and $2M DARPA grant for inertial sensors. He directs the interdisciplinary AIMS Laboratory focused on MEMS, ultrasound, and calorimetric technologies. The lab collaborates extensively with NanoSI and The Plastics Center, developing autonomous microsystems for biomedical, environmental, and industrial applications through advanced manufacturing techniques.

Soner SonmezogluView profile

Assistant Professor

• Integrated Circuits
• Micro/Nano Electro Mechanical Systems (M/NEMS)
• Implantable Medical Devices
• +4 more

Soner Sonmezoglu is an Assistant Professor of Electrical and Computer Engineering at Northeastern University's College of Engineering. His research focuses on implantable and wearable medical devices enabled by advanced microelectronics and microfabrication for neurological, diagnostic, and therapeutic applications. He leads the Sonmezoglu Lab and has secured major grants including a $13M ARPA-H award for developing photoacoustic imaging systems for early lung cancer detection. Education: PhD in Electrical and Computer Engineering, UC Davis (2017) BSc and MSc in Electrical Engineering with a minor in Solid-State Physics, Middle East Technical University (2010-2012) Postdoctoral Researcher, UC Berkeley EECS (pre-2022) Research Interests: His work spans integrated circuits, micro/nano electromechanical systems (M/NEMS), neural interfaces, and medical device integration. Key projects include ultrasonic wireless neural interfaces and millimeter-scale oxygen sensors for deep-tissue monitoring. Current initiatives include the PAIL project for lung cancer diagnostics. Awards: UC Davis Graduate Division Fellowship Scientific and Technical Research Council of Turkey Graduate Fellowship Grants & Collaborations: Principal Investigator of ARPA-H's $13M PAIL initiative. Active in the Institute for NanoSystems Innovation, contributing to chip-level technology advancements. Labs/Teams: Directs the Sonmezoglu Lab at Northeastern, focusing on next-generation biomedical device innovation through interdisciplinary microsystems engineering.

Anders Sejr HansenView profile

Assistant Professor

• 3D Genome Structure
• Gene Expression Regulation
• Chromatin Dynamics
• +5 more

Anders Sejr Hansen is an Assistant Professor of Biological Engineering at MIT, leading the Hansen Lab focused on understanding 3D genome structure and its functional implications. He holds a PhD from Harvard University and completed postdoctoral training at UC Berkeley. His research integrates advanced imaging, genomics, and computational methods to study chromatin dynamics, enhancer-promoter interactions, and their roles in gene regulation across health and disease. Education: Bachelor's/Master's in Chemistry, University of Oxford (2010) PhD in Chemistry and Chemical Biology, Harvard University (2015) Postdoctoral Research, UC Berkeley (2015–2020) Research Interests: His work spans molecular mechanisms of genome organization, development of novel microscopy techniques (e.g., MINFLUX, expansion microscopy), and computational models for 3D genomics. Key areas include chromatin dynamics, loop extrusion by cohesin/condensin, and the impact of 3D structure on gene expression in cancer and aging. Awards: NIH K99 Pathway to Independence Award (2019) NIH Director’s New Innovator Award (2020) Pew-Stewart Scholar for Cancer Research (2021) NSF CAREER Award (2024) NIH Director’s Transformative Research Award (2024) Advising & Grants: Hansen mentors PhD students and postdocs, including notable advisees Viraat Goel and Domenic Narducci. His lab has secured major grants from NIH, NSF, and private foundations, supporting interdisciplinary projects in imaging, genomics, and synthetic biology. Labs/Teams: The Hansen Lab at MIT collaborates with institutions globally, advancing technologies like Region Capture Micro-C (RCMC) and deep learning models (e.g., Cleopatra) for high-resolution genome mapping. The lab also explores synthetic biology approaches to engineer genome structures.

Ljubisa StankovicView profile

Professor

• Signal Processing
• Time-Frequency Analysis
• Radar Signal Processing
• +2 more

Ljubisa Stankovic is a Full Professor at the University of Montenegro with extensive academic and political experience. He has served as Rector of the University of Montenegro (2003-2008), Member of the National Academy of Sciences and Arts (CANU) since 1996, and Ambassador of Montenegro to the United Kingdom since 2010. As an IEEE Fellow (2012), he has made significant contributions to signal processing research. His research focuses on Signal Processing , particularly Time-Frequency Analysis , Data Processing in Joint Time and Frequency Domain , Analysis of Non-Stationary Signals , and Radar Signal Processing . With about 300 technical papers published (83 in leading international journals, mainly IEEE editions) and several textbooks in Signal Processing, his work has substantially influenced the field. The analysis of his recent publications reveals a consistent focus on advanced time-frequency methods applied to radar systems, non-stationary signal analysis, and emerging applications in machine learning and quantum processing. His research shows evolution from theoretical foundations toward practical implementations in communications, radar, and biomedical applications. His notable scientific achievements include: Member of the National Academy of Sciences and Arts (1996) Highest State award of Montenegro '13. jul' (1997) Fellow of the IEEE (2012) Fulbright fellowship (1984-1985) Alexander von Humboldt fellowship (1997) Volkswagen award grant (2001) Scientific Achievement Award by Montenegrin Academy of Science and Art (1991) Stankovic has held significant editorial positions including Associate Editor for IEEE Transactions on Image Processing, IEEE Signal Processing Letters, and IEEE Transactions on Signal Processing since 2003. He was also a member of the IEEE Signal Processing Society's Technical Committee on Theory and Methods (2002-2008). His research group received a Volkswagen Foundation research grant (2001-2003), demonstrating his ability to secure competitive funding. Beyond academia, he has held prominent political positions including Vice-president of Montenegro (1989-1991) and Member of Yugoslav Parliament (1992-1996).

Wei David DaiView profile

Assistant Professor

• Robust Deep Learning
• Data Quality
• Distributed Computing Systems
• +4 more

Dr. Wei David Dai is an Assistant Professor of Computer Science at Purdue University Northwest and Director of the Advanced Intelligence Software (AIS) Lab. His research focuses on robust deep learning, data quality, and public safety technologies like gunshot detection systems. He previously worked at IBM China as a senior engineer and served in Arkansas state government as a data scientist. Education: Ph.D. in Computer and Information Sciences (University of Arkansas at Little Rock, USA, 2020) M.S. in Information Science (University of Arkansas at Little Rock, USA, 2016) M.S. in Software Engineering (South China University of Technology, China, 2013) B.S. in Computer Science (Central South University, China, 2007) Research Interests: His work spans robust deep learning models, distributed computing systems, and privacy-preserving technologies. Notable projects include public safety innovations such as acoustic gunshot detection and AI-driven campus security systems. Articles Trends: Recent publications emphasize public safety applications (e.g., mass school shooting simulations) and deep learning robustness evaluation (e.g., the Accuracy-Stability Index metric). Earlier works address cloud computing optimization and data quality frameworks. Awards: Recipient of the 2024 Excellence in Research Award and multiple IBM honors for technical excellence and instruction. Grants & Advising: Leads the Indiana Space Grant Consortium-funded satellite imaging project and Purdue Provost Grant for gunshot detection. Advises doctoral and master’s students on AI ethics, distributed systems, and public safety. Labs: The AIS Lab develops AI tools for public safety, equipped with GPU resources for audio and image analysis.

• Microelectronics
• Biomedical Engineering
• Neural Prosthetics
• +3 more

Matthias Kuhl is a Professor at the Institute of Microsystems Technology (IMTEK) at the University of Freiburg since April 2022. He leads research projects focused on neural probes, biomedical implants, and integrated microelectronic systems. His work includes developing low-power neural interfaces, stress sensors, and energy-efficient circuits for medical applications. Research Interests Neural probes with electronic depth control Implantable biomedical devices CMOS integrated sensors and actuators Energy harvesting for autonomous systems Microfabrication and 3D-printed electronics Key Projects Advanced EDC: Intracortical neural probes with electronic depth control ComBiNE: Bidirectional neural exchange components SEAM-WiT: Implantable neural probe transceivers Multi-material 3D-printed electronics His recent publications emphasize low-power neural front-ends, stress sensor integration, and biomedical system design. He advises numerous graduate students on topics ranging from CMOS circuit design to biohybrid systems. Labs & Teams He leads the Professur für Mikroelektronik lab, specializing in microelectronic systems for biomedical and industrial applications. Collaborates with orthodontic, neurobiology, and materials science groups.

• Terahertz Microsystems
• RF/Microwave MEMS
• Sub-THz Radar Concepts
• +3 more

Joachim Oberhammer is a Professor in Microwave and THz Microsystems at KTH Royal Institute of Technology in Stockholm, Sweden. He leads research in radio-frequency/microwave/terahertz micro-electromechanical systems (MEMS) and has held academic roles since 2005. His work includes pioneering advancements in THz communication, sub-THz radar concepts, and MEMS-based components. Oberhammer has been awarded the 2023 Young Engineer Award by the European Microwave Association and holds multiple grants, including an ERC Consolidator Grant (2013) and SSF framework grants (2014–2025). He has authored over 200 peer-reviewed publications and holds four patents in MEMS and THz technology. Education: M.Sc. in Electrical Engineering (Graz University of Technology, 2000), Ph.D. in Microwave Engineering (KTH, 2004). Postdoctoral research at Nanyang Technological University (2004) and Kyoto University (2008). Guest professorships at Universidad Carlos III de Madrid (2019–2020) and NASA-JPL (2014). Research focuses on MEMS fabrication, THz systems integration, and radar technologies. Key projects include the EU-funded M3TERA and Car2TERA projects, and leadership in SSF framework grants for electronics research. He coordinates the EU RIA projects TeraMeasure and TESLA, advancing terahertz applications. Teaching responsibilities include MSc and PhD courses in MEMS engineering, radar systems, and integrated circuits. His lab develops high-performance THz components, including waveguide switches, antennas, and filters, with applications in communication, sensing, and aerospace.