Dr. Kibret Mequanint is a full Professor at Western University's Department of Chemical and Biochemical Engineering, with cross-appointments in Biomedical Engineering. Holding a PhD from University of Stellenbosch and postdoctoral experience at Technical University of Darmstadt and McMaster University, his research bridges polymer science, materials engineering, and life sciences with applications in Biomaterials , Tissue Engineering , and Regenerative Medicine . His work spans both fundamental and translational research in cell-material interactions , polymer biomaterial design , and therapeutic radiation dosimeters , with technologies transferred to commercial applications. Leading scholar and educator with awards from NSERC, CIHR, and Western University Fellow of: American Institute for Medical and Biological Engineering (AIMBE), Ethiopian Academy of Sciences, International Union of Societies for Biomaterials Science and Engineering, Canadian Academy of Engineering Extensive editorial and panel service for NSERC, CIHR, and international journals His research program has produced over 170 refereed publications, focusing on conductive hydrogels , bioadhesives , and vascular tissue engineering . Recent work on endoscopy-deliverable bioadhesives and snake venom-derived hemostatic gels has attracted global media attention. He has served in leadership roles at the Canadian Biomaterials Society and university governance bodies including Senate and Board of Governors.
Professor Hossein Rahmani serves at the School of Computing and Communications , Lancaster University , with a focus on Computer Vision and Machine Learning . His career spans institutions like the University of Western Australia (PhD), Shahid Beheshti University (MSc), and Isfahan University of Technology (BSc). Research Interests : Computer Vision, Machine Learning, Video Analysis, Action Recognition/Detection, Object/Human Pose Estimation, 3D Reconstruction, Diffusion Models, Human-Object Interaction Editorial Roles : Associate Editor for IEEE Transactions on Neural Networks and Learning Systems , Pattern Recognition , ACM Computing Surveys ; Area Chair for CVPR 2025, ICLR 2025, ECCV 2024, IJCAI 2024 His recent work leverages diffusion models for domain-generalized object pose estimation, 3D scene editing, and human mesh recovery, published in top venues like TPAMI , CVPR , ICCV , and ECCV . He received the Best Scientific Paper Award from the International Conference on Pattern Recognition and actively supervises 5 PhD students with interdisciplinary projects in digital health and data science.
Dr. Shelley Wickham is an Associate Professor and ARC DECRA Fellow at the University of Sydney, holding joint appointments in the Schools of Chemistry and Physics. She serves as a Westpac Research Fellow and leads the DNA Nanotechnology Group at the Sydney Nano Institute. Dr. Wickham is also co-Champion of the Sydney Nano Institute Grand Challenge project in Molecular Nanorobotics for Health, co-lead of the School of Physics Grand Challenge on Nanoscale brain navigation for targeted drug delivery, and faculty mentor of the University of Sydney BIOMOD team. Bachelor of Science and Master of Science in Physics from University of Sydney PhD in Condensed Matter Physics from University of Oxford Postdoctoral Fellow at Harvard Medical School, Dana-Farber Cancer Institute, and Wyss Institute Dr. Wickham's research focuses on self-assembling nanotechnology and molecular robotics, particularly in the design and assembly of programmable nanostructures out of DNA. Her work spans applications in cell biology, materials science, and nanomedicine. Current research projects include design and synthesis of self-assembling DNA nanostructures, proto-cells made of DNA gels that move under flow, new plasma fabrication methods for biomolecule micropatterning, and DNA computation circuits for navigating the brain using machine learning. Her research aligns with the Faculty of Science Research Strengths in Molecules to Materials, Preventing and Treating Disease & Disorder, and Next Generation Materials. Analysis of Dr. Wickham's recent publications reveals a consistent focus on DNA nanotechnology with increasing sophistication in structural complexity and biological applications. Her work has evolved from fundamental DNA origami structures to increasingly complex multi-component systems with practical applications in nanomedicine and biomimetic engineering. Recent publications show strong interdisciplinary collaboration across chemistry, physics, biology, and engineering disciplines, with emphasis on real-world applications including drug delivery systems and biomolecular sensors. ARC DECRA Fellow Westpac Research Fellow BIOMOD World Champions (2019) Dr. Wickham actively mentors PhD students and postdoctoral researchers in her DNA nanotechnology group. She has secured significant research funding including ARC Discovery Projects, Westpac Scholarships, and NSW Health grants. Her current grants support projects such as '3D Bio-Nanomaterial Displays with Designer Architectures and Functions' and 'RNA aptamer sensing devices for rapid detection of blood clotting.' Dr. Wickham encourages applications from diverse backgrounds and maintains active collaborations with researchers at Harvard, Oxford, and other international institutions. Dr. Wickham leads the DNA Nanotechnology Group at the University of Sydney, which is part of the Sydney Nano Institute. Her lab focuses on building tools from DNA origami - including tweezers, spanners, wrenches and springs - to better understand biological processes at the nanoscale. The group has achieved notable success with the BIOMOD team winning world championships in 2019, and continues to develop innovative approaches to molecular robotics for healthcare applications.
Amir Bahadori serves as Professor and Nuclear Engineering Program Director in the Department of Mechanical and Nuclear Engineering at Kansas State University's Carl R. Ice College of Engineering, holding the Hal and Mary Siegele Professorship in Engineering. He directs the Radiological Engineering Analysis Laboratory (REAL) and established the Institute for Radiation Health Studies (IRHS) in 2024, focusing on radiation protection, space radiation environments, and radiation health effects. His educational background includes: Ph.D. in Biomedical Engineering, University of Florida (2012) M.S. in Nuclear Engineering Sciences, University of Florida (2010) B.S. in Mechanical Engineering and Mathematics, Kansas State University (2008) Bahadori's research spans radiation transport modeling, dosimetry, and risk assessment with applications in space exploration, medical physics, and radiation epidemiology. He develops computational frameworks for radiation exposure scenarios and biological response prediction, emphasizing space radiation protection for Artemis missions and chronic exposure studies through the Million Person Study collaboration. Analysis of his recent publications reveals dominant themes in space radiation measurement (Artemis missions), radiation epidemiology (Million Person Study innovations), and advanced detection systems (miniaturized neutron spectrometers). His work increasingly integrates big data approaches for radiation risk assessment and electrostatic shielding concepts for deep-space exploration. His scientific recognition includes: NASA Graduate Student Research Fellowship (2009) Certified Health Physicist designation Big 12 faculty fellowship (2022-2023) NCRP council election (2024) Two USPTO patents Bahadori secures substantial research funding from NASA for space radiation instrumentation, Department of Energy projects via the Kansas City National Security Campus, and collaborative epidemiological studies. He mentors nuclear engineering graduate students while leading interdisciplinary teams developing radiation protection solutions for aerospace and medical applications. His laboratory infrastructure includes the REAL with Beocat high-performance computing resources, radiation detectors, and a 3D printer, plus the IRHS with a Precision X-ray XRad320 irradiator and radon chamber. These facilities support collaborations across K-State colleges and external organizations for radiation health effect studies.
Neda Haj Hosseini is a Senior Lecturer and Associate Professor in Biomedical Engineering at Linköping University's Department of Biomedical Engineering (IMT) . She contributes to teaching courses like TBMT56 - Medical Technology and TBME08 - Biomedical Modeling and Simulation , while leading research initiatives in AI-driven cancer diagnostics and biomedical optics. Research Focus: Development of AI methods for cancer diagnostics, optical coherence tomography (OCT) applications, and fluorescence spectroscopy in surgical guidance Affiliations: Center for Medical Image Science and Visualization (CMIV) , Analytic Imaging Diagnostic Arena (AIDA) , Swedish Medical Technology Association Recent Research Trends demonstrate expertise in applying deep learning to: Pediatric brain tumor classification using multimodal imaging Optical biopsy techniques for intraoperative decision support Automated biomarker quantification in histopathology Medical imaging data integrity and algorithm validation Scientific Awards include grants from: Joanna Cocozza Foundation (2022) Swedish Childhood Cancer Foundation (2024) Academic Leadership involves mentoring students in projects such as: "Multiple Instance Attention-based Learning for Brain Tumor Classification" "Vision Transformers for Multiclass Brain Tumor Tissue Classification" "Reaction-diffusion Models for Image-driven Tumor Simulation"
Leah Schubert, PhD is an Associate Professor in the Department of Radiation Oncology at the University of Colorado Anschutz Medical Campus School of Medicine. She serves as Director of the Medical Physics Residency Program, leading educational initiatives in medical physics training. Her professional focus centers on improving safety, quality, and educational standards in radiation oncology physics. Dr. Schubert earned her PhD from the University of Wisconsin - Madison in 2009 and completed her undergraduate studies with a BS from the University of California–San Diego in 2003. She is board certified in Therapeutic Medical Physics by the American Board of Radiology (2012). Her research spans medical physics education, radiation safety, quality assurance, and functional imaging applications in radiation therapy. She has pioneered work in physics plan review training, safety checklist implementation, and 4DCT-ventilation imaging for functional avoidance radiation therapy. Her educational research focuses on concept inventories, virtual interviewing for residency matches, and cross-institutional residency training frameworks. Analysis of her recent publications reveals a consistent focus on improving safety culture in radiation oncology through systematic approaches including failure modes and effects analysis, simulated error training, and safety checklist development. Her work increasingly incorporates cross-institutional collaboration and educational innovation in medical physics training. ABR Volunteer Services Award, American Board of Radiology (2023) Board Member at Large, Society of Directors of Academic Medical Physics Programs (2022) AAPM Fellow, American Association of Physicists in Medicine (2022) Excellent Patient Safety Role Model, University of Colorado Hospital (2021) ABR Volunteer Services Award, American Board of Radiology (2020) IAEA Competition Towards a Strong Safety Culture in Radiation Medicine, International Atomic Energy Agency (2019) As Director of the Medical Physics Residency Program, Dr. Schubert oversees comprehensive training for future medical physicists, implementing innovative approaches to curriculum development and assessment. Her leadership extends to national committees including the AAPM Work Group on Periodic Review of Medical Physics Residency Training and various SDAMPP committees. She has secured funding for educational initiatives focused on improving residency training standards and safety culture development. Dr. Schubert collaborates extensively with multi-institutional research teams, particularly in the area of 4DCT-ventilation imaging and its clinical applications for functional avoidance radiation therapy. Her work bridges clinical practice, safety initiatives, and educational innovation in medical physics.
Prof. Dr. Matthias Weidlich is a faculty member at Humboldt University of Berlin within the Institute of Computer Science under the Faculty of Mathematics and Natural Sciences . His research focuses on Process Mining , Complex Event Processing , and Data Privacy with applications in Business Process Management and Scientific Workflows . Research Interests: Business Process Management and Process Mining Complex Event Processing and Stream Data Analysis Data Privacy and Security in Process Systems Scientific Workflow Systems and User Behavior Heterogeneous Network Embeddings Algorithm Design and Optimization Recent Publications (2023-2025) demonstrate expertise in: Efficient stream processing techniques Privacy-preserving process mining frameworks Scientific workflow analysis tools Graph neural network applications Multi-modal data integration Adaptive querying systems Contact: Office: Unter den Linden 6, 10099 Berlin Phone: 030 2093-41277 Email: matthias.weidlich@hu-berlin.de Web: hu.berlin/data
Richard Axel is a University Professor at Columbia University, holding appointments in the Vagelos College of Physicians and Surgeons as Professor of Neuroscience, Professor of Biochemistry and Molecular Biophysics, and Professor of Pathology and Cellular Biology. He serves as Codirector of Columbia's Mortimer B. Zuckerman Mind Brain Behavior Institute and is an Investigator at the Howard Hughes Medical Institute since 1984. Dr. Axel earned his AB from Columbia College and MD from Johns Hopkins Medical School. His Nobel Prize-winning research identified over 1,000 odorant receptors in the nose that transmit olfactory information to the brain, revolutionizing our understanding of the sense of smell. His early work with colleagues developed groundbreaking gene transfer techniques that enabled the introduction of virtually any gene into any cell, leading to novel approaches for gene isolation and analysis of gene function. Dr. Axel's research focuses on understanding how olfactory information is processed in the brain to create internal representations of the external world. His work spans molecular neuroscience, neural circuitry, and the relationship between sensory input and behavioral output. He has pioneered techniques that have advanced our understanding of neural function and sensory processing mechanisms. Analysis of Dr. Axel's recent publications reveals a continued focus on olfactory processing systems, with increasing integration of computational approaches and machine learning to understand neural representations. His work spans from molecular mechanisms to circuit-level analyses, with particular emphasis on how odor information is encoded and transformed in the brain to produce meaningful perceptions and behaviors across multiple model systems. Nobel Prize in Physiology or Medicine (2004) Howard Hughes Medical Institute Investigator (1984-Present) The Royal Society Foreign Member (2014) Gairdner Foundation International Award (2003) American Philosophical Society Member (2003) National Academy of Sciences Member (1983) Richard Lounsbery Award (1989) American Association for the Advancement of Science Fellow (2018) American Academy of Arts and Sciences Fellow As Codirector of the Zuckerman Institute, Dr. Axel oversees one of the world's leading neuroscience research centers, fostering interdisciplinary collaboration across multiple departments. His lab continues to train the next generation of neuroscientists, investigating how sensory information is transformed into meaningful perceptions and behaviors. Dr. Axel's early work on gene transfer techniques laid the foundation for numerous advances in molecular biology and neuroscience, including the isolation and analysis of the CD4 gene, the cellular receptor for HIV. Dr. Axel leads the Axel Lab at Columbia University, which is part of the Zuckerman Institute. His research team investigates how organisms recognize olfactory information in the environment and transmit it to the brain, where it is processed to create internal representations of the external world. The lab employs multidisciplinary approaches combining molecular, cellular, and systems neuroscience to unravel the neural circuits underlying sensory processing and behavior, with particular focus on understanding how these representations translate stimulus features into appropriate innate and learned behaviors.
Lingyang Chu is an Assistant Professor at McMaster University's Department of Computing and Software, previously serving as a postdoc fellow at Simon Fraser University under Jian Pei. He earned his Ph.D. in Computer Science from the University of Chinese Academy of Sciences. Research interests span data mining , machine learning , and statistics , with focus on trustworthy AI (privacy, interpretability, security, robustness, fairness), federated learning , and graph-based machine learning . His work includes scalable data mining on large graphs and deploying systems like personalized federated learning on Huawei Cloud's Harmony OS devices. Publications emphasize adversarial attacks, medical AI, graph robustness, and federated learning frameworks. His advising record includes 28 mentees across Ph.D., M.Sc., and internship levels. Scientific achievements include Best paper candidate at ICME'13 Best demo award at ICMR'13 Academic service roles include: Program Committee: NeurIPS, SIGKDD, CVPR, ICML, and 12+ other top-tier conferences Journal Reviewer: IEEE TKDE, ACM Transactions on KDD, and 8+ journals Editorial Board: ACM Transactions on KDD (Associate Editor) Grant Reviewer: Hong Kong RGC Labs/teams: Maintained open-source ALID algorithm (VLDB'15) for dominant cluster detection, demonstrating technical leadership in scalable graph mining
Dr. Gabriella Lindberg is an Assistant Professor in the Department of Bioengineering at the University of Oregon's Knight Campus, leading the Lindberg Lab. Her research focuses on developing bioinks, hydrogels, and bioresins to engineer musculoskeletal tissues that replicate native biological environments. She holds a PhD from the University of Otago and previously served as a Research Fellow in the Christchurch Regenerative Medicine and Tissue Engineering (CReaTE) Group. Dr. Lindberg has secured significant grants, including a New Zealand Health Research Council Emerging Researcher Grant, and has won multiple awards such as the ISBF Young Investigator Award (2019) and CMDT/MedTech CoRE awards. Her work spans collaborative projects with institutions in New Zealand, Germany, Netherlands, and Australia. Current lab members include researchers like Vinni Thoms (Lab Manager) and Tim Wheeler (Postdoctoral Scholar). The lab is recruiting for postdoctoral and graduate positions in immunomodulation for osteoarthritis and bone marrow tissue engineering. Key research platforms include biofabrication, biomaterials, and organoid development. Dr. Lindberg’s research emphasizes clinical relevance, with projects addressing patient variability and disease progression modeling. Her team explores oxygen control in 3D-printed constructs and integrates inflammatory biology with biomaterials science. The lab’s long-term goals include advancing 3D bioassembly for musculoskeletal repair and hematological disease treatments. Notable contributions include work on vitreous humor as a biomaterial, automated 3D bioassembly, and the development of photoclickable gelatin bioinks. She has mentored numerous students, including PhD candidates Axel Norberg and Bram Soliman, and supervised master’s and undergraduate researchers in tissue engineering and biofabrication techniques.
Doug Bowman is the Frank J. Maher Professor in the Department of Computer Science at Virginia Tech and Director of the Center for Human-Computer Interaction. His work focuses on advancing virtual reality (VR), augmented reality (AR), and 3D user interfaces, with a strong emphasis on human-computer interaction and immersive environments. Education: Ph.D., Computer Science, Georgia Institute of Technology (1999) M.S., Computer Science, Georgia Institute of Technology (1997) B.S., Mathematics and Computer Science, Emory University (1994) Research Interests: Bowman explores the design and evaluation of immersive technologies, including VR/AR interfaces, 3D interaction techniques, and the application of these technologies in fields like healthcare, education, and collaborative work. His work often addresses challenges in spatial awareness, gaze-driven systems, and context-aware interfaces. Recent publications highlight trends in collaborative AR/VR systems, glanceable interfaces, and adaptive techniques for immersive analytics. His research emphasizes real-world applications, such as medical training through AR and improving productivity in virtual workspaces. Lab Affiliation: Director of Virginia Tech’s Center for Human-Computer Interaction, which focuses on interdisciplinary research in interactive technologies.
Wenfeng Zhao is an Assistant Professor in the Department of Electrical and Computer Engineering at Binghamton University. He holds a PhD from the National University of Singapore (2014) and BS/MS degrees from Huazhong University of Science and Technology (2007-2009). Prior to this role, he conducted postdoctoral research at the University of Minnesota's Biomedical Engineering Department. His research focuses on neural engineering, compressed sensing, ultra-low-power VLSI systems, and in-memory computing. Key areas include hardware security, biomedical signal processing, and energy-efficient computing architectures. His work spans applications in neural interfaces, cryptographic hardware, and IoT edge devices. Recent publications highlight advancements in block-cipher-in-memory architectures, emotion recognition via EEG analysis, and energy-efficient FPGA accelerators for neural networks. His research also addresses challenges in cryogenic memory systems and MRI-compatible neural recording devices. Zhao's contributions emphasize interdisciplinary approaches at the intersection of hardware design, signal processing, and cybersecurity. His lab develops novel solutions for low-power embedded systems and trustworthy IoT infrastructure.
Ken Wong is an Associate Professor in the Department of Computing Science at the University of Alberta's Faculty of Science. He also serves as Associate Chair within the same department. Holding a PhD in Computer Science from the University of Victoria (1999), his research focuses on software engineering challenges such as reverse engineering, program understanding, and software visualization. He emphasizes improving software evolution through tools like architecture recovery and root cause analysis, with applications in web/mobile platforms and diverse system understanding. Teaching highlights include developing Massive Open Online Courses (MOOCs) via Coursera, including the 'Software Product Management Specialization' and courses on Agile practices, client needs analysis, and software metrics. His recent publications (2023–2025) span AI-driven healthcare innovations (e.g., medical imaging, photoacoustic tomography) and advanced computer vision techniques (e.g., diffusion models, video inpainting). Notable collaborations include EVAREST studies on heart failure management and lung transplantation outcomes. His work bridges software engineering theory and practical applications in healthcare technology, with contributions to federated learning frameworks (e.g., FedLPPA) and AI-augmented clinical decision support systems. Research also extends to autonomous driving (DriveGPT4-V2) and 3D human avatar generation (DreamAvatar), showcasing interdisciplinary impact.
Mario A. Svirsky is the Noel L. Cohen Professor of Hearing Science and Professor of Neuroscience at NYU Grossman School of Medicine. He leads the Laboratory for Translational Auditory Research, focusing on auditory neural prostheses like cochlear implants and their impact on speech perception and neuroplasticity. His work bridges clinical care and scientific discovery, addressing how the brain adapts to sensory deprivation and degraded auditory input. Education: PhD in Biomedical Engineering from Tulane University (1988). Postdoctoral training at MIT and prior academic appointments at Indiana University and Purdue University before joining NYU in 2005. Research: Explores cochlear implant performance optimization, speech perception in hearing-impaired individuals, and neuroplasticity mechanisms. Collaborates with the Froemke Lab on animal models of cochlear implantation. Active in developing computational models and signal processing techniques to improve implant efficacy. Funding: Principal investigator on multiple NIH grants (e.g., R01 DC016839, R01 DC016834) and industry partnerships. His lab’s work has advanced clinical management strategies for cochlear implant users, including those with contralateral hearing aids. Labs/Teams: Directs the Laboratory for Translational Auditory Research, collaborating with multidisciplinary teams including engineers, neuroscientists, and clinical audiologists. Mentors postdocs, audiologists, and medical students in auditory research.
Dr. Christos Papavassiliou is an Associate Professor in the Department of Electrical and Electronic Engineering at Imperial College London, part of the Faculty of Engineering. His research focuses on instrumentation electronics, memristor modeling, signal integrity, and novel device technologies such as SiGe devices, RF MEMS, and ReRAM. He leads the Space Lab and collaborates with the National Centre for Scientific Research in Athens. He holds senior membership in IEEE and is a member of the IET. Education: Ph.D. in Applied Physics, Yale University (1983–1989) MPhil in Applied Physics, Yale University (1983–1988) MS in Applied Physics, Yale University (1983–1985) B.S. in Physics, MIT (1979–1983) Research Interests: Memristor-based neuromorphic computing and stochastic systems High-performance instrumentation hardware and data acquisition Multi-state memristive memory and selectorless arrays Integration of memristors with CMOS for hybrid circuits Applications in biomedical wearables and edge AI deployment Key Contributions: Developed novel memristor models for circuit simulation Pioneered work on memristor-based true random number generators Advanced understanding of resistive drift and energy-constrained storage Designed FPGA-based systems for analog circuit emulation Labs & Teams: Active in the Space Lab at Imperial College, focusing on interdisciplinary research in electronics and space applications.
