Mark F. Bocko is a Professor of Electrical and Computer Engineering and Physics at the University of Rochester, serving as Chair of the Department of Computer and Electrical Engineering since 2004. He holds a BA from Colgate University and advanced degrees (MS/PhD) in Physics from the University of Rochester. His research spans superconducting digital electronics, quantum computing, music signal processing, and smart sensor systems. Notable awards include the Excellence in Undergraduate Teaching Award (1991, 2002) and Professor of the Year (2002). His research groups focus on high-frequency digital signal processing using Josephson junctions, quantum coherence in superconducting circuits, and applications in music technology such as internet-based real-time musical collaboration. Collaborations include work with the Eastman School of Music and local industries on sensor networks and wireless technologies. Key contributions include developing GHz-rate analog-to-digital converters, quantum bit control systems, and music encoding algorithms. His NSF-funded projects explore internet2 applications for musical interaction and physical modeling in music systems.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۱۶-۳۰ از ۱۵۵ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
Ozgur Yilmaz is a Professor in the Department of Mathematics at the University of British Columbia (UBC). He is the Director of the Pacific Institute for the Mathematical Sciences (PIMS) and has held roles such as Interim Deputy Director at PIMS and Deputy Director at the Banff International Research Station (BIRS). His research focuses on applied harmonic analysis, signal processing, compressed sensing, and seismic signal processing. Education: PhD in Applied and Computational Mathematics from Princeton University (2001), B.Sc. in Mathematics and Electrical Engineering from Boğaziçi University (1997). Research Interests: Mathematical problems in analog-to-digital conversion, blind source separation, sparse approximations, compressed sensing, and their applications in seismic exploration. He has contributed to advancements in sigma-delta quantization, low-rank matrix recovery, and compressed sensing algorithms. Funding: Recipient of NSERC Discovery Grants, UBC Data Science Institute grants, and leadership in collaborative research groups (CRGs) on high-dimensional data analysis and applied harmonic analysis. His work bridges theoretical mathematics with practical applications in signal processing and AI-driven medical imaging. Students and Postdocs: Supervised numerous PhD and MSc students in areas like compressed sensing, seismic data reconstruction, and machine learning. Current advisees include Aaron Berk and Xiaowei Li. Former students hold positions at academic institutions and tech companies. Labs and Collaborations: Affiliated with UBC’s Data Science Institute (DSI), Centre for Artificial Intelligence Decision-making and Action (CAIDA), and the Institute of Applied Mathematics (IAM). Collaborates on projects integrating AI with scientific discovery, such as retinal biomarker identification using deep learning.
Gökhan Seçintiمشاهده پروفایل
استادیار
Gökhan Seçinti is an Assistant Professor in the Department of Computer Engineering at Istanbul Technical University, Faculty of Computer and Informatics. He currently serves as Vice Dean and has previously held the role of Vice Department Head. His research focuses on next-generation wireless networks, UAV communications, semantic communication, and AI-driven networking solutions. Research Interests: His work spans Unmanned Aerial Vehicles (UAVs) , Semantic and Task-Oriented Communication , Software-Defined and Cognitive Networks , 6G Communications , and AI in Networking . He develops practical testbeds for deep learning-based communication architectures and explores digital twin applications in aerial networks. Publication Trends: Recent publications emphasize decentralized UAV service deployment, beam alignment using UWB localization, TDMA scheduling for aerial swarms, and semantic flow control. These reflect a strong trend toward intelligent, adaptive, and context-aware communication systems for IoT and mobility. Best Paper Award, IEEE, 2022 Best Conference Paper, IEEE, 2016 Best Poster Paper Award, IEEE, 2015 Advising and Grants: He has supervised 4 academic works and leads multiple funded research projects, including TÜBİTAK and SRP grants on federated learning in flying networks, semantic VANETs, AI-based intrusion detection, and UAV-assisted IoT for crisis management. Labs and Teams: His work is supported by active research teams at ITU, focusing on testbed development using SDRs, digital twins, and real-world deployment of UAV networks. He collaborates internationally, including past affiliations with Northeastern University.
- Computer Security
- Cryptography
- Computer Systems
- +۵ مورد دیگر
Henry Corrigan-Gibbs is an Assistant Professor at the Massachusetts Institute of Technology (MIT) in the Department of Electrical Engineering and Computer Science. He is affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL) and collaborates with the PDOS and CSS research groups. Henry co-hosts the MIT Security Seminar series. Education : PhD in Computer Science from Stanford University (advisor: Dan Boneh), Postdoc at École polytechnique fédérale de Lausanne (EPFL) (host: Bryan Ford), and B.S. in Computer Science from Yale University . Research Interests Henry focuses on computer security , cryptography , and systems research , building technologies that: Empower end users through privacy-preserving design Implement strong cryptographic security in real-world deployments Scale to millions of users while maintaining security Key projects include: Tiptoe for private web search Prio for privacy-preserving aggregate statistics used by Apple and Google Express for metadata-hiding communication SafetyPin and True2F for secure authentication Scientific Contributions Standards Influence : IETF and NIST standards recommend his private-aggregation systems Industry Impact : Deployed in Apple iOS , Google Android , and Mozilla Firefox Non-profit Deployment : Co-founder of Divvi Up for real-world Prio implementations Academic Recognition 2023 MIT EECS Jerome Saltzer Award for teaching excellence 2020 ACM Doctoral Dissertation Honorable Mention 2016 Caspar Bowden Award for PET research 2015 IEEE Security & Privacy Distinguished Paper Award Multiple IACR Best Young Researcher Paper Awards (2015–2018) Advising and Collaborations Current advisees include: PhD students: Alexandra Henzinger , Ryan Lehmkuhl Postdoc: Emma Dauterman Collaborates with industry (Apple, Google, Mozilla) and standards bodies (IETF, NIST) to translate research into practice.
Oliver Deussen is a Professor of Visual Computing at the University of Konstanz, recognized by the German Informatics Society (GSI) as a Fellow for his contributions to computer science. His research focuses on visualization, robotics, and environmental modeling, particularly in plant and landscape representation. He has pioneered methods in image manipulation and robotic painting, emphasizing digitalization's societal impacts. His work spans computational biology (e.g., schooling fish behavior) and AI-driven creative technologies. Research Interests: Visualization techniques, swarm behavior analysis, robotic creativity, and interdisciplinary applications of computer science. He explores how computational methods can model natural systems and enhance human-machine interaction. Awards: Fellow of the German Informatics Society (GSI) His research often bridges theory and practice, with contributions to SLAM frameworks, style transfer algorithms, and uncertainty visualization tools. Collaborations in robotics and biology reflect his commitment to applied computational research.
Utku Yavuzمشاهده پروفایل
استادیار
Dr. Utku Yavuz is an Assistant Professor in the Biomedical Signals and Systems Department at the TechMed Centre. His expertise spans neuromuscular physiology, wearable sensor technologies, and clinical monitoring systems. He holds a PhD in Biomedical Engineering from Ege University, complemented by earlier degrees in Physics Engineering (Hacettepe University) and Biophysics (Hacettepe University). Research Focus: Motor unit physiology, neuromuscular modeling, and clinical applications of wearable sensors. Key Areas: Spinal motor neuron behavior, electromyography (EMG), and translational technologies for diabetes and musculoskeletal health. Dr. Yavuz’s work bridges neuroscience and engineering, addressing challenges in prosthetic design, real-time neuromuscular signal decoding, and improving clinical decision-making through sensor data analysis. Recent studies include optimizing wearable glucose monitors and analyzing muscle-tendon dynamics in amputees. His research outputs span 43 publications, with contributions to high-impact journals like BMC Digital Health and IEEE Sensors Journal . Collaborations include institutions focused on biomechanics, robotics, and clinical informatics. Advising: Supervised 1 graduate project, though specific advisee names are not listed. Active in academic activities such as thesis examinations and conference presentations.
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Mohammad Karim, PhD, is a Professor in the Department of Electrical & Computer Engineering at the University of Massachusetts Dartmouth (UMass Dartmouth), affiliated with the College of Engineering. He previously held leadership roles including Provost, Executive Vice Chancellor for Academic Affairs, and Chief Operating Officer at UMass Dartmouth. His career includes serving as Vice President of Research at Old Dominion University (2004–2013), Dean of Engineering at City College of New York (2000–2004), and Head of Electrical and Computer Engineering at the University of Tennessee (1998–2000). He is an elected fellow of multiple prestigious organizations, including IEEE, OSA, and SPIE. Dr. Karim holds a BS Honors in Physics from the University of Dhaka (1976) and MS in Physics (1978) and MS/PhD in Electrical Engineering (1979/1981) from the University of Alabama. His research focuses on optical computing, pattern recognition, electro-optical systems, and sensors, with funding from agencies like the Office of Naval Research and NASA. He has authored 19 books, over 365 papers, and 13 book chapters, and served as guest editor for 36 journal special issues. His awards include Fellowships from IEEE, OSA, and the Bangladesh Academy of Sciences. He mentors students in MS/PhD programs and advises on research proposals. His work spans academic leadership, technical innovation, and interdisciplinary collaboration in engineering and optics.
Bernadette von Dawans is a Research Associate and Senior Academic Advisor in Research and Teaching at the Department of Biological and Clinical Psychology, Faculty I, University of Trier, Germany. She is also a licensed psychological psychotherapist and certified supervisor in cognitive behavioral therapy, leading the Psychotherapy Outpatient Clinic for Stress, Social Interaction and Behavioral Medicine. Her research focuses on the psychobiology and clinical aspects of stress, including social interaction, stress protection mechanisms (e.g., social support, oxytocin), stress management across age groups, and the impact of sex hormones on behavior. She investigates methods of stress induction and measurement, with applications in personality disorders, social phobia, and burnout. Her recent publications, primarily in psychoneuroendocrinology and clinical psychology journals, reveal a strong trend in examining how acute stress modulates social cognition, emotion recognition, prosocial behavior, and hormonal responses. She frequently employs the Trier Social Stress Test (TSST-G) and explores gender differences, hormonal influences (e.g., oral contraceptives, cortisol, oxytocin), and interventions like glucose intake or internet-based stress management. Common oxytocin receptor gene (OXTR) polymorphism and social support interact to reduce stress in humans Oxytocin, vasopressin, and human social behavior Dr. von Dawans has contributed to research on stress resilience, affiliative behaviors under stress, and the neuroendocrine underpinnings of social functioning. She collaborates extensively with researchers such as Markus Heinrichs and Gregor Domes. She supervises clinical work and contributes to training early-career researchers in clinical psychology, though no formal advisees are listed. Her work is supported by empirical studies and systematic reviews, contributing significantly to stress and social behavior research.
Stefano Palminteri is a researcher at the École Normale Supérieure in Paris, leading the Human Reinforcement Learning team at the Cognitive Neuroscience Laboratory (LNC2) since 2017. He holds a PhD in Cognitive Neuroscience from Université Pierre et Marie Curie (2012) and completed postdoctoral work at LNC2, University of Trento, and University College London. Education: Master in Pharmaceutical Biotechnology (University of Bologna, 2006); Master in Cognitive and Behavioral Neuroscience (Université Pierre et Marie Curie, 2007); PhD in Cognitive Neuroscience (UPMC, 2012). His research focuses on computational and neurobiological mechanisms of reinforcement learning, decision-making under uncertainty, and behavioral biases. He investigates how contextual factors (e.g., social influence, neurochemical states) shape learning processes in healthy and clinical populations (e.g., addiction, depression, Tourette syndrome). Recent work explores value normalization, metacognitive biases, and cross-cultural comparisons of reinforcement learning. Key trends in his publications include (1) computational modeling of reward/punishment sensitivity in psychiatric conditions, (2) neuroeconomic frameworks for decision-making under risk and ambiguity, (3) multi-agent reinforcement learning in financial market simulations, and (4) cross-domain comparisons of description vs. experience-based learning. He employs functional neuroimaging, pharmacological interventions, and behavioral experiments to uncover how brain circuits (e.g., striatum, prefrontal cortex) encode value signals. His lab offers internships in epistemic biases and reinforcement learning.
Javier F. Medina, Ph.D., is a Professor and Brown Foundation Chair in Neuroscience at Baylor College of Medicine. His research focuses on understanding how neural circuits implement supervised learning to make predictions, particularly in the context of motor control and cognitive functions. His laboratory combines experimental techniques such as electrophysiology, optogenetics, and two-photon imaging with computational modeling and artificial neural networks to uncover the computational principles underlying brain function. Education Postdoctoral Fellowship in Neuroscience, UCSF (2007) Ph.D. in Neuroscience, University of Texas, Houston (2000) Bachelor of Science in Computer Science and Physics, Drexel University, Philadelphia (1993) Research Interests Medina’s work integrates computational neuroscience with experimental approaches to study prediction and error correction in neural circuits. His lab investigates how the cerebellum encodes temporal information, processes sensory input, and adapts through learning. Key topics include supervised learning algorithms, neural coding in Purkinje cells, and the role of prediction errors in motor adaptation. Publications His research spans themes in cerebellar circuitry, motor learning, and computational modeling. Recent work includes deep learning strategies for cell-type identification and studies on cerebellar modules for predictive control. Grants & Labs Medina leads a lab at Baylor College of Medicine, focusing on experimental and theoretical neuroscience. His work has implications for motor disorders linked to learning deficits, such as ataxia and Parkinson’s disease.
Professor Sarah Johnson is a distinguished academic in the School of Engineering at the University of Newcastle, specializing in Electrical and Computer Engineering. She holds a PhD in Electrical Engineering from the same institution and has been awarded prestigious fellowships including an ARC Future Fellowship. Her research applies engineering solutions to digital information processing and error correction coding, with significant applications in secure communications and biomedical technologies. Her research interests span: Signal processing for secure data transmission Error correction codes for reliable communication systems Biomedical applications of digital signal processing Quantum-enabled secure communications Internet of Things communication protocols Her publications primarily focus on information theory, wireless communication systems, and biomedical engineering. Recent work shows strong emphasis on index coding optimizations, quantum cryptography implementations, and biomedical signal processing techniques for neuroimaging applications. Significant awards include: NSW Premier's Prize for Excellence (2017) Pro Vice-Chancellor's Research Excellence Award (2007) Professor Johnson has secured multiple ARC Discovery grants and industry-sponsored projects, including collaborations with Quintessence Laboratories on quantum key distribution. She co-founded HunterWISE to promote women in STEM fields and has supervised numerous graduate students across engineering disciplines. She leads interdisciplinary collaborations with biomedical researchers on rehabilitation technologies and neuroimaging analysis, developing systems to monitor recovery processes and brain activity patterns.
Dr. Sherif Moussa is a Professor and Dean at the Faculty of Engineering, Applied Science and Technology, Canadian University Dubai. He holds a PhD in Electrical and Computer Engineering from the University of Quebec and an MSc from the University of Waterloo, both in Canada. Before joining CUD in 2007, he served as a lecturer at Centennial College in Toronto. His research focuses on: Wireless Communication Computer Networks Machine Learning Digital Circuit Design His recent publications explore machine learning applications in cybersecurity, MIMO-OFDM systems, FPGA implementations, and routing protocols, reflecting a consistent emphasis on optimizing wireless and network technologies. Trends show increasing work in AI-driven solutions and intrusion detection since 2018. He received the 2015 CUD Research Excellence Award and founded the university's first robotics club. He actively contributes as a reviewer and technical committee member for international conferences.
Darya Frankمشاهده پروفایل
پژوهشگر ارشد
Dr. Darya Frank is a Royal Society University Research Fellow at the Division of Psychology Communication and Human Neuroscience at the University of Manchester. She leads research into neural mechanisms of memory formation and ageing, using techniques like virtual reality, MRI, and computational modeling. Her work contributes to UN Sustainable Development Goals related to education and health. Education: PhD in Neuroscience, University of Manchester (2019) MSc in Cognitive Neuroscience, University College London (2015) External Roles: Marie Curie Research Fellow, Universidad Politécnica de Madrid (2022–2024) Postdoctoral Researcher, Universidad Politécnica de Madrid (2019–2022) Research Interests: Her lab investigates adaptive memory formation , neuromodulation , and memory reactivation . They employ behavioral tasks, neuroimaging, and computational models to study how emotions, surprise, and expectations shape memory processes. Current projects include modeling dopamine's role in brain-state dynamics (funded by a 2025 PhD project). Articles Overview: Recent work explores emotional salience's impact on memory flow (2024), structural brain changes in ageing (2022), and surprise's temporal effects on memory encoding (2022). These studies highlight interdisciplinary approaches linking cognitive psychology with neuroscience. Awards: Royal Society University Research Fellowship (2024) Marie Skłodowska-Curie Individual Fellowship (2022) Grants & Labs: Accepting PhD students (e.g., dopamine neuromodulation project) and planning additional funded positions (Q3 2025). Collaborates with platforms like Dementia@Manchester and Digital Futures to advance translational neuroscience.
- Neuroscience
- Robotics
- Computational Biology
- +۴ مورد دیگر
Prof. Pavan Ramdya, the DSM-Firmenich Next Generation Chair in Neuroscience at École Polytechnique Fédérale de Lausanne (EPFL), leads the Neuroengineering Laboratory. His research focuses on reverse-engineering biological intelligence in Drosophila melanogaster to inspire neuroprosthetics, robotics, and AI. He holds a PhD in Neurobiology from Harvard University and completed postdoctoral training in robotics (EPFL), neurogenetics (UNIL), and bioengineering (Caltech). University: École Polytechnique Fédérale de Lausanne (EPFL) School: School of Life Sciences Academic Rank: Professor His lab employs computational, engineering, genetic, and microscopy approaches to study neural population dynamics, biomechanics, and gene expression in limb-dependent behaviors. Key research trends from his publications include neuromechanical modeling of Drosophila , sensory-motor integration, and AI-robotics synergy for biological discovery. HFSP Career Development Award Swiss National Science Foundation Eccellenza Grant UNIL Young Investigator Award in Basic Science FENS-Kavli Network of Excellence member The lab mentors doctoral researchers such as Sibo Wang, Victor Stimpfling, and Femke Hurtak, alongside postdoctoral fellows like Jasper Phelps and alumni including Victor Lobato Rios. Collaborations span robotics (Auke Ijspeert), microrobotics (Sakar), and computational imaging (Fua).
- Electronic Music
- Music Composition
- Music Theory
- +۳ مورد دیگر
Peter Lucas Hulen is a Professor in the Music Department at Wabash College , where he has taught for nearly 25 years. His work bridges classical acoustic composition with experimental computer-generated electronic music, informed by his classical training and later shift toward digital techniques. Research interests include: Electronic music history Music technology pedagogy Digital synthesis methods (FM, subtractive, granular) Integration of acoustic and electronic sound Algorithmic composition Interdisciplinary applications His compositions explore: Microtonal scales using superparticular ratios Wireless performance interfaces Choral liturgy adaptation Cultural sound symbolism Speaker array design Temporal structure manipulation Recent works combine academic rigor with technical innovation: 2017: Homage and Refuge , Wobbly 2015: Organum IV 2014: Magnificat , Sitting 328b 2013: Les substances botaniques , Primitive 2012: Lamentationes Jeremiae I He developed a systematic electronic music curriculum including: History and Literature Computer Programming (Max/MSP) Performance Ensembles Theory and Composition