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Micheline B. SoleyView profile

Assistant Professor

• Quantum Computing
• Quantum Dynamics
• Ultracold Chemistry
• +5 more

Micheline B. Soley is an Assistant Professor in the Department of Chemistry at the University of Wisconsin-Madison with an affiliate appointment in Physics. She leads the Soley Research Group, which focuses on developing quantum computing algorithms, tensor-network methods, and quantum control strategies to address fundamental challenges in quantum dynamics and ultracold chemistry. Her research bridges theoretical chemistry, quantum information science, and computational physics. Education: Ph.D. in Chemical Physics, Harvard University (2020) A.M. in Chemistry, Harvard University (2016) Yale Quantum Institute Postdoctoral Fellow (2020-2022) Fulbright Fellow, Max Born Institute (2013-2014) B.S. in Chemistry and Music, Yale University, Magna Cum Laude (2013) Research Interests: Her work centers on three interconnected pillars: (1) Quantum computing algorithms and tensor-network methods for exact quantum dynamics, overcoming dimensionality limitations in chemical simulations; (2) Ultracold chemistry and quantum control, developing schemes to manipulate chemical reactions and analyze ultracold collisions; and (3) Theoretical spectroscopy, creating tools to simulate UV/X-ray pump-probe experiments for mechanistic studies of processes like isomerization and proton transfer. Publication Trends: Recent articles (2023-2025) demonstrate a strong focus on quantum algorithm development (error mitigation, amplitude estimation), tensor-network applications in quantum dynamics and biomolecular simulations, quantum hardware compilation, and fundamental studies of PT symmetry and ultracold collisions. Her work consistently integrates theoretical chemistry with quantum information science. Awards and Fellowships: American Chemical Society Kavli Emerging Leader in Chemistry Award (2023) Institute for Pure and Applied Mathematics Fellow (2021) Yale Quantum Institute Postdoctoral Fellowship (2020) National Science Foundation Graduate Research Fellowship (2014) Fulbright Fellowship (2013-2014) DAAD Graduate Scholarship (2013-2014) Beckman Scholars Fellowship (2012-2013) Phi Beta Kappa (2012) Advising and Group: She mentors graduate students from Chemistry and Physics programs, including Jingcheng Dai (Chemistry), Atharva Vidwans (Chemistry/Physics), and Henry Lin (Physics-Quantum Computing). Former advisees include Preetham Tikkireddi (Quantum Circuits Inc.) and Jaden Coles (Yale PhD). Her group explores quantum computing, tensor networks, ultracold collisions, and PT symmetry.

Simone WinkoView profile

Professor

• Modern German Literature
• Literary Theory
• Emotion in Poetry
• +4 more

Prof. Dr. Simone Winko holds the Chair for Modern German Literature and Literary Theory at the University of Göttingen since 2003. Her research spans literary theory, canonization, praxeology of literary studies, and the intersection of emotions with German poetry around 1900 and digital humanities. Academic Roles: Chair at Göttingen (2003–), DFG Priority Programme 2207 leadership (2017–), Courant Center collaboration (2009–) Key Projects: DFG projects on literary change (2023–), computational literary history (2020–2023), and argumentation practices in interpretations (2018–2020) Her recent work focuses on emotions in German-language poetry , using computational methods to model text similarity and analyze historical shifts between Realism and Modernism. She explores how emotional codes and narrative strategies are embedded in lyrical structures, particularly through projects like Anthologien zeitgenössischer deutschsprachiger Lyrik (2022). Scientific Awards : 2010: 1st prize for best doctoral supervision (KissWin, BMBF-funded) Teaching & Collaboration : Supervises B.A., M.A., and Ph.D. theses; co-edits the Journal of Literary Theory and Revisionen book series. Collaborates with Fotis Jannidis, Gerhard Lauer, and Matías Martínez on computational approaches to literary studies.

Alexandre Mermillod-BlondinView profile

Researcher

• Laser-Matter Interaction
• Ultrafast Optics
• Photonic Structures
• +1 more

Dr. Alexandre Mermillod-Blondin is a Principal Investigator heading a DFG-funded project on 'Micromachining with few-cycle pulses' at the Max Born Institute. His research focuses on fundamental laser-matter interactions and direct laser writing of 3D micro-optical systems in transparent materials. Key investigations include plasma formation mechanisms in dielectrics, relaxation dynamics, and applications in photonic device fabrication. His group utilizes phase-contrast microscopy and time-resolved techniques to characterize ultrafast processes.

Teresa CheungView profile

Adjunct Professor

• Biomedical Engineering
• Neuroimaging
• Magnetoencephalography (MEG)
• +4 more

Teresa Cheung is an Adjunct Professor in the Department of Engineering Science at Simon Fraser University’s Faculty of Applied Sciences. Her research focuses on neuroimaging techniques, particularly magnetoencephalography (MEG), and their applications to understanding brain networks in health and disease. She holds a Ph.D. in Physics from SFU (2012) and completed a postdoctoral fellowship at the University of Cambridge (2012–2013). Research interests include: MEG instrumentation and optically pumped magnetometers (OPM) Cortical-cerebellar networks and cerebellar activity localization Neuroimaging of neurological disorders like major depressive disorder and epilepsy Functional and structural connectome analysis across the human lifespan Multimodal integration of MEG, MRI, fMRI, and DTI data Recent work emphasizes the relationship between cardiovascular health, brain aging, and cognitive resilience. Her studies span clinical applications (e.g., depression biomarkers) and technical advancements in neuroimaging systems. Collaborations include multi-site studies on depression and aging cohorts like the Cam-CAN project. Publications highlight innovative methods in MEG system design, neural network dysfunction analysis, and lifespan brain dynamics. Her work bridges engineering, neuroscience, and clinical research to advance non-invasive brain imaging and neurophysiological understanding.

• Biomedical Imaging
• Medical Imaging Physics
• Motion Compensation in Imaging
• +5 more

Associate Professor Andre Kyme is an academic staff member in the School of Biomedical Engineering at The University of Sydney. His research focuses on developing enabling technologies for biomedical imaging, including motion compensation in MRI/PET, robotic platforms for image-guided therapy, and cross-disciplinary applications like plant salt uptake analysis using PET. He collaborates with institutions globally and advises students on projects like lameness detection in horses and AI-based motion correction. Research Interests: Kyme's work spans motion correction in medical imaging modalities, medical robotics integration with imaging systems, and innovative applications of imaging technologies in non-traditional fields. His team emphasizes leveraging advancements in computer vision, machine learning, and instrumentation to improve imaging performance and accessibility. Recent Projects: Current research includes MRI-compatible robotic platforms for therapy applications, AI-driven lameness detection in horses, and pediatric neuroimaging improvements. He leads the BREEZE initiative to enhance MRI accessibility for children with cerebral palsy through eye-gaze communication technology. Publications: His work spans 20+ years with over 50 peer-reviewed publications in journals like Physics in Medicine and Biology and IEEE Transactions. Key areas include PET/SPECT/CT motion correction algorithms, robotic systems for medical imaging, and novel imaging applications in plant science. Teaching: Kyme instructs core biomedical engineering courses including thesis supervision and capstone projects at both undergraduate and postgraduate levels. Labs/Teams: Active in the Brain and Mind Centre and Biomedical Imaging, Visualisation and Information Technologies groups at Sydney. Collaborates with industry partners like TeleMedVet and academic institutions including University of California Davis and Chinese University of Hong Kong.

Jennifer HicksView profile

Research Professor

• Biomechanical Modeling
• Machine Learning in Biomechanics
• Musculoskeletal Dynamics
• +3 more

Jennifer Hicks is the Executive Director of the Wu Tsai Human Performance Alliance at Stanford University, focusing on collaborative research to advance understanding of human performance through biomechanical modeling and machine learning. She also serves as Director of Research for the NIH-funded Mobilize Center and Restore Center, integrating engineering tools into rehabilitation science. Her work emphasizes predictive modeling of surgical outcomes, mobile health data analysis, and exoskeleton design. Dr. Hicks leads software development for the OpenSim project, guiding its user-centric evolution and promoting open-source biomedical tools. Her research spans musculoskeletal dynamics, wearable technology, and clinical applications of AI. Key contributions include smartphone-based motion capture (OpenCap) and foundational datasets like AddBiomechanics. She co-develops training programs for interdisciplinary teams and advocates for large-scale health data utilization. Dr. Hicks' efforts bridge academia and industry, supporting translational research in neurorehabilitation, sports performance, and chronic disease management.

• 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.

Sina SarehView profile

Professor

• Soft robotics
• Multi-modal mobility
• Manipulation and attachment
• +1 more

Sina Sareh is a robotics researcher at the Royal College of Art (RCA), where he leads the RCA Robotics Laboratory within the School of Design. He has established himself as an expert in soft robotics and multimodal sensing, developing innovative solutions for human safety and access problems in industrial operations. Dr. Sareh's educational background includes: PhD in Robotics from the University of Bristol, where he worked on monolithic design of flexible actuators for operation in confined liquid environments MSc in Control Systems from the University of Sheffield BSc in Electrical Engineering from Amirkabir University of Technology, Tehran Dr. Sareh's research focuses on soft robotics, multi-modal mobility, manipulation and attachment, and multimodal sensing. His work bridges the gap between robotics engineering and practical applications, particularly in medical and industrial settings. He has developed novel approaches to robotic attachment inspired by octopus biology, created haptic interfaces that mimic the feeling of touching human internal organs, and designed soft robotic technologies to help articulate pain symptoms. His research consistently demonstrates innovation in creating adaptable robotic systems that can operate effectively in complex, unstructured environments where traditional rigid robots face limitations. His publication record demonstrates a strong trajectory in robotics research, with emphasis on soft robotics, medical applications, and novel sensing techniques. The research shows progression from fundamental soft actuator design to practical applications in surgery, industrial operations, and human-robot interaction, with a consistent focus on solving real-world problems through biologically inspired approaches. Dr. Sareh has successfully secured multiple research grants, including EPSRC funding for 'Getting a Grip' and 'Multi-vendor Interoperability in Robotics,' as well as InnoHK funding for 'Intelligent Medicine Warehousing.' He has also served as an impact assessor for the Research Excellence Framework (REF) 2021 in Engineering and is a member of the editorial board at IET Cyber-physical Systems and Robotics Journal. Currently, Dr. Sareh advises research students including Filippo Sanzeni, and maintains active collaborations with industry and academic partners through the RCA Robotics Laboratory, which serves as a hub for interdisciplinary robotics research at the intersection of design, engineering, and human-centered applications. His work on projects like 'Topographies of Pain' and 'Reminisys' demonstrates a commitment to applying robotics technology to improve healthcare outcomes and quality of life.

• 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.

Christian KrupitzerView profile

Professor

• Food Informatics
• Self-adaptive Software Systems
• Machine Learning
• +4 more

Jun.-Prof. Dr. Christian Krupitzer is a Tenure Track Professor in Food Informatics at the University of Hohenheim's Institute of Food Science and Biotechnology, part of the Faculty of Natural Sciences. He leads the Department of Food Informatics and is a member of the Computational Science Hub (CSH). His research focuses on self-adaptive software systems, machine learning (especially edge computing), IoT technologies, and software engineering applied to food processing and agricultural systems. Education: PhD in Business Information Systems (Dr. rer. pol.), University of Mannheim (2018) M.Sc. and B.Sc. in Business Information Systems, University of Mannheim (2010–2012) High School Diploma (Abitur) from Wilhelmi-Gymnasium Sinsheim (2007) Research Interests: Krupitzer’s work integrates computational methods with food science, emphasizing adaptive systems for food quality monitoring, IoT in agriculture, and machine learning for predictive analytics. He explores edge computing’s role in real-time decision-making and secure group communication schemes for IoT networks. Publications: His recent work spans predictive maintenance in Industry 4.0, digital twins in food systems, and blockchain applications in supply chain authentication. The articles highlight trends in interdisciplinary approaches combining AI, IoT, and domain-specific challenges in food production and logistics. Awards: No scientific awards explicitly listed in the provided materials. Grants & Advising: While specific grants are unmentioned, his roles as department head and tenure-track professor suggest involvement in research funding. No formal advisee list provided, though his team includes postgraduate researchers like Dana Jox, Daniel Einsiedel, and others. Labs & Teams: Leads the Food Informatics department and collaborates with the Computational Science Hub. His team focuses on developing innovative solutions for food systems through computational methods.

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.

Ian C. BruceView profile

Professor

• Auditory modeling
• Hearing aids
• Cochlear implants
• +4 more

Dr. Ian Bruce is a Professor in the Department of Electrical and Computer Engineering at McMaster University, Hamilton, ON, Canada. He has been with the department since 2002, conducting interdisciplinary research that bridges electrical engineering with auditory neuroscience. His work has significant implications for hearing technologies and auditory rehabilitation. Education: B.E. (electrical and electronic) from The University of Melbourne (1991) Ph.D. from the Department of Otolaryngology, The University of Melbourne Dr. Bruce's research program focuses on auditory modeling, hearing aids, cochlear implants, tinnitus, neural coding of speech, and digital speech processing. His work centers on understanding the physiological mechanisms of auditory processing and applying this knowledge to develop improved hearing technologies. He has pioneered computational models of the auditory periphery that accurately predict speech intelligibility for hearing-impaired listeners, directly informing hearing aid and cochlear implant design. Analysis of Dr. Bruce's recent publications (2019-2025) reveals a consistent focus on cochlear implants and auditory nerve modeling, with increasing integration of machine learning techniques. His work demonstrates a sophisticated balance between physiological accuracy and computational efficiency, with recent papers exploring WaveNet-based approximations of cochlear models and DNN-based auditory processing. A significant portion of his research examines the relationship between neural responses and perceptual outcomes in hearing-impaired individuals, particularly regarding temporal processing and speech understanding. Scientific Awards and Recognitions: Fellow of the Acoustical Society of America Member of the Association for Research in Otolaryngology Registered Professional Engineer in Ontario Associate Editor of the Journal of the Acoustical Society of America Dr. Bruce has mentored numerous graduate students through various capstone design projects across multiple engineering disciplines including biomedical, electrical, mechanical, and software engineering. His teaching portfolio includes specialized courses in biomedical signals and systems, cellular bioelectricity, models of the neuron, and advanced signal processing. He has consistently supervised M.Eng. projects and independent studies, demonstrating commitment to training the next generation of engineers in auditory technology development. Dr. Bruce's research is conducted within McMaster University's interdisciplinary biomedical engineering framework, collaborating with clinicians and researchers in otolaryngology and audiology. His laboratory work focuses on developing and validating computational models that simulate auditory nerve responses to both natural and prosthetic stimulation, with direct applications to improving cochlear implant performance and hearing aid algorithms for real-world listening environments.

Lin CaiView profile

Associate Professor

• Wireless Communication
• Networking
• Green Radio Communication Networks
• +5 more

Lin Cai is an Associate Professor in the Department of Electrical and Computer Engineering at Illinois Institute of Technology, serving as Director of Graduate Affairs. She holds a Ph.D. in Electrical and Computer Engineering from the University of Waterloo, Canada (2010). Her research focuses on sustainable wireless communication and networking, particularly in energy harvesting, IoT, and deep reinforcement learning for resource management. Key research projects include energy sustainability in renewable-energy-powered networks, energy-efficient 5G protocols, and radio resource management over unlicensed bands. She has received the NSF CAREER Award (2016-2020), Best Paper Awards, and NSERC Postdoctoral Fellowship. Her work spans theoretical frameworks and practical implementations in HetNets, MIMO, and UAV-based systems. Education: Ph.D., E&CE, University of Waterloo, Canada (2010) Affiliations: Executive Editorial Committee member, IEEE Transactions on Wireless Communications (2021–present); Associate Editor for multiple IEEE journals Teaching: Courses include ECE 407/408 (Computer Networks) and ECE 517 (Modern Wireless Network Protocols) Her research emphasizes cross-layer protocol design, sustainable capacity planning, and topology control. Notable contributions include frameworks for energy sustainable radio resource management and optimization in dense HetNets. She actively contributes to conference organization and technical program committees for IEEE INFOCOM, GLOBECOM, and ICC.

• Electronics Engineering
• Signal Processing
• Biomedical Engineering
• +3 more

Bruno Tiago da Silva Gomes is a Researcher in the Department of Electronics and Informatics at Vrije Universiteit Brussel (VUB), Belgium. His work focuses on FPGA-based hardware acceleration, biomedical signal processing, and embedded systems. He leads several high-impact projects, including ENACT (environmental health interventions) and Tech4Health (future health technologies). His research spans FPGA design, machine learning acceleration, and real-time signal processing. Education: PhD in Electronics and Informatics (2019, VUB), supervised by Professors Touhafi and Braeken. His thesis addressed streaming application acceleration on FPGAs. Research interests include Field-Programmable Gate Arrays (FPGA), biomedical sensors (e.g., photoplethysmography), beamforming, and high-level synthesis. He has co-authored over 60 publications and holds an h-index of 439. Key projects include OZR4103 (power-efficient AI for biomedical applications) and NSIS3 (decarbonisation technologies). His work integrates hardware-software co-design for edge computing and secure TinyML systems. Advising includes a Master’s thesis on PPG signal analysis. He contributes to datasets like the AMIVU Acoustic Map Imaging Dataset.

Chung-Hsing YehView profile

Associate Professor

• Multicriteria Decision Analysis
• Applied Artificial Intelligence
• Intelligent Decision Support Systems
• +6 more

Chung-Hsing Yeh is an Associate Professor at Monash University's Faculty of Information Technology, Department of Data Science & AI. He holds a visiting professorship at National Cheng Kung University, Taiwan, and has extensive experience in academic roles including Chief Examiner and Lecturer for numerous IT and business-related courses. His research focuses on multicriteria decision analysis, applied artificial intelligence, fuzzy logic, neural networks, and sustainable operations management. He has led collaborative projects on e-waste recycling, supply chain optimization, and public health policy, funded by organizations like the Ministry of Science and Technology (Taiwan) and the Australian Research Council. Education: PhD in Operations Research/Information Systems, Monash University (1988) MSc in Management Science, National Cheng Kung University (1982) BSc (Engineering) in Industrial Design, National Cheng Kung University (1977) Research Interests: His work spans decision support systems, optimization modeling, transport research, and recycling operations. Notable contributions include algorithms for production scheduling, AI-driven solutions for healthcare, and sustainable e-waste management strategies. Awards: Listed in Marquis Who's Who in the World Listed in Who's Who in Finance and Industry Listed in Who's Who in Science and Engineering Grants & Projects: Led 6 major projects, including 'Maximizing E-waste Recycling Profitability' (2019–2020) and 'Smoke-Free Policy Effectiveness' (2007–2010). Active in grant review roles for ARC and the Netherlands Organisation for Scientific Research. Teaching: Overseeing courses such as Fundamentals of Artificial Intelligence, Business Intelligence Modelling, and Management Information Systems.