Real-time Visualization Professors and Supervisors | ApplySharif

جست‌وجوی استاد و پژوهشگر

استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشی‌تان را پیدا کنید و با او ارتباط بگیرید.

نمایش ۷۲۱-۷۳۵ از ۷٬۳۸۹ استاد راهنما

اطلاعات این پروفایل‌ها از صفحات عمومی دانشگاه‌ها جمع‌آوری شده و ممکن است به‌روز نباشد.

Xin Liمشاهده پروفایل

استاد

Duke UniversityUnited States

Xin Li is a Professor in the Department of Electrical and Computer Engineering at Duke University and serves as the Associate Vice Chancellor at Duke Kunshan University. He holds a Ph.D. from Carnegie Mellon University (2005) and has held leadership roles in research consortia like the FCRP Focus Research Center and the Center for Silicon System Implementation (CSSI). His research bridges integrated circuits , machine learning , and cyber-physical systems , with applications in autonomous driving, battery lifetime prediction, and smart buildings. Education : Ph.D., Carnegie Mellon University (2005); M.S., Fudan University (2001); B.S., Fudan University (1998) His work emphasizes robust design methodologies for analog/RF circuits, data-driven predictive modeling , and Bayesian inference for high-dimensional variation spaces. Recent publications focus on generative adversarial networks for circuit design, multi-view imputation for incomplete data, and knowledge-driven autonomous systems . He has received numerous accolades, including the NSF CAREER Award (2012) , IEEE Donald O. Pederson Best Paper Awards (2013, 2016) , and IEEE Fellow (2017) . He has served as Editor for journals like IEEE Transactions on Biomedical Engineering and as Chair for conferences including ISVLSI and CAD/Graphics.

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Ronald J. Glotzbachمشاهده پروفایل

دانشیار

Purdue UniversityUnited States

Ronald J. Glotzbach is an Associate Professor at Purdue University's West Lafayette campus within the School of Applied and Creative Computing . His work focuses on web programming and development , leading projects that integrate dynamic content, databases, and educational technologies . He has taught courses such as CGT 356 (Web Programming), CGT 353 (Interactive Media), and CGT 456 (Advanced Web Programming). B.S. in Computer Graphics Technology M.S. in Technology Ph.D. in Curriculum and Instruction (pursuing) His research explores leading-edge web technologies for delivering interactive content, emphasizing web-enabling software, dynamic media integration, and mobile programming . Key trends in his publications include RSS technologies in education , web-based evaluation systems , and geospatial data tools for environmental sciences. Scientific awards include: Outstanding Professor (2003, 2004) CGT Dwyer Award for Outstanding Undergraduate Teaching (2005) CGT Outstanding Un-Tenured Faculty Award (2008) Professor Glotzbach has led numerous student teams in CGT projects , served as SIGGRAPH Student Volunteer Chair (2003-2005) , and collaborated with industry partners like Boeing (F-15 Distributed Mission Trainer) and Microsoft (XML Documents Testing Team) . He also provided expert testimony in a copyright case (2006) for Wargo & French, LLP.

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Philipp Koehnمشاهده پروفایل

استاد

Johns Hopkins UniversityUnited States

Philipp Koehn is a Professor in the Department of Computer Science at Johns Hopkins University, with additional affiliation at the University of Edinburgh. His primary research focuses on statistical and neural machine translation, specifically developing methods to leverage large-scale digital information for cross-lingual communication. He leads the Machine Translation Research Group and maintains key resources like the Moses toolkit and Europarl corpus. His research interests span: Core machine translation techniques (statistical/neural approaches) Low-resource and unsupervised translation methods Cross-lingual representation learning Speech-to-speech translation systems Large-scale parallel data mining and alignment Evaluation methodologies for generated text Koehn's recent publications demonstrate strong focus on improving translation efficiency (dynamic compression, streaming models), robustness (noise handling, error correction), and accessibility (low-resource languages, radio speech processing). Key trends include multilingual generalization, document-level coherence, and human-centered evaluation. Significant scientific recognition includes: ACL Fellow (2024) IAMT Award of Honor (2015) European Inventor Award Finalist (2013) He currently advises PhD students Rachel Wicks, Elina Baral, Bismarck Odoom, and Weiting Tan. His Machine Translation Group develops widely-used open-source tools and organizes major conferences including WMT and MT Marathon.

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Jürgen Sauerمشاهده پروفایل

استاد

University of FribourgSwitzerland

Jürgen Sauer is a Full Professor at the University of Fribourg , affiliated with the Department of Psychology under the Faculty of Letters and Human Sciences . With over 120 publications, his research focuses on Human-Machine Interaction , Usability Testing , User Experience (UX) , and Automation Design , particularly in high-stakes environments like X-ray baggage screening and spaceflight simulations . Email: juergen.sauer@unifr.ch Phone: +41 26 300 7622 Address: RM 01 bu. C-1.117, Rue PA de Faucigny 2, 1700 Fribourg Orcid: 0000-0003-2105-1694 His research projects, funded by the Swiss National Science Foundation (FNS), include: Improving work design for airport security officers (2019-2024): Developed pictorial scales for measuring psychological constructs in security environments. Social stress and support in hybrid teams (2018-2023): Investigated machine-induced social stressors and mitigation through social support. Automation in visual inspection tasks (2014-2018): Examined adaptable automation for baggage screening and system reliability effects. Usability testing effectiveness (2012-2016): Analyzed cultural background impacts and non-usability product features influencing test outcomes. Key contributions include the Luggage Inspection Simulation (LIS) environment for modeling work environments and the development of pictorial usability scales for multilingual applicability. His work bridges ergonomics , human factors , and applied psychology , with notable collaborations with researchers like Adrian Schwaninger and Andreas Sonderegger . His recent publications (2025-2014) analyze: Human-machine performance under false alarms and miscues Social stressor dynamics in hybrid teams Usability scale animation effects Phubbing behavior in professional contexts Accessible website design for non-disabled users

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Jim Tørresenمشاهده پروفایل

استاد

University of OsloNorway

Jim Tørresen is a Professor of Computer Science at the Department of Informatics, University of Oslo, where he has been employed since 1999 (Associate Professor 1999-2005, Professor since 2006). He serves as group leader for the Robotics and Intelligent Systems (ROBIN) research group and is also a Principal Investigator at the Centre for Interdisciplinary Studies in Rhythm, Time and Motion (RITMO). His academic career includes visiting positions at Cornell University's Creative Machines Lab (2010-2011) and Kyoto University in Japan (1993-1994). His educational background includes a Dr.ing. (Ph.D.) in Computer Architecture from the Norwegian University of Science and Technology (1996) and an M.Sc. in Computer Architecture from the same institution (1991). Before his academic career, he worked in industry at Navia Aviation (1998-1999) and NERA Telecommunications (1996-1998). Tørresen's research spans artificial intelligence, robotics, and bio-inspired computing. His work focuses on biology-inspired algorithms, programmable logic (FPGA), robotics (simulation, prototyping, control), and human-robot interaction. He has made significant contributions to areas including evolutionary computing, reconfigurable hardware, and adaptive systems. His research often bridges theoretical computer science with practical applications in healthcare, music, and industrial settings. His recent publications demonstrate a strong focus on human-robot interaction, particularly in healthcare contexts for elderly care, as well as applications in sports science, musical robotics, and geological engineering. His work shows a consistent pattern of interdisciplinary research that combines machine learning techniques with domain-specific challenges. Tørresen has also authored a popular science book on artificial intelligence in the "what is" series by Universitetsforlaget, which discusses fundamental concepts, methods, future perspectives, and ethical aspects of AI. He has been active in academic leadership, serving as General Chair for the 22nd International Conference on Field Programmable Logic and Applications (FPL) in 2012 and the 9th Joint IEEE International Conference of Developmental Learning and Epigenetic Robotics in 2019. As group leader of ROBIN, he oversees research on intelligent systems that operate in dynamic environments requiring runtime adaptation. The group works at both fundamental and applied levels, using evolutionary algorithms for robot learning and machine learning techniques for classification and recognition tasks in various application domains.

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Ryo Ikeshiroمشاهده پروفایل

استادیار

City University of Hong KongHong Kong SAR

Ryo Ikeshiro is an Assistant Professor at the School of Creative Media, City University of Hong Kong, and co-director of the spatial audio art/research unit SoundLab. His work bridges sound art, computational creativity, and cultural studies through immersive installations, algorithmic audio-visual systems, and sonification techniques. PhD in Creative Practice (Goldsmiths, University of London) MPhil in Music (University of Cambridge) BMus (King's College London) Ikeshiro's research interrogates the materiality of sound through: Multichannel Ambisonics and directional audio Neural network-driven temporal dislocation Sonification of climate data and historical soundscapes Machine learning for artistic interpretation Interplay of identity and technology East Asian ideophonic traditions His 2010-2024 publications and installations reveal cross-disciplinary engagement with: Fractal mathematics in audiovisual art Algorithmic composition systems Interactive installation technologies Sonic cartography Historical memory in sound Collaborative research frameworks SoundLab, which he co-directs, develops spatial audio research at the intersection of: Technical innovation Cultural representation Experimental pedagogy Public engagement International artistic exchange Practice-based research

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Susann M. Brady-Kalnayمشاهده پروفایل

استاد

Case Western Reserve UniversityUnited States

Cancer Biology
Molecular Imaging
Receptor Protein Tyrosine Phosphatases (RPTPs)
+۹ مورد دیگر

Susann M. Brady-Kalnay, PhD , is the Sally S. Morley Designated Professor of Brain Tumor Research at the Case Western Reserve University (CWRU) School of Medicine. She holds professorships in the Departments of Molecular Biology and Microbiology, Neurosciences, and Pathology, and is a member of the Cancer Imaging Program at the Case Comprehensive Cancer Center. Her work bridges molecular biology, cancer imaging, and targeted therapy. Research Interests : Dr. Brady-Kalnay specializes in receptor protein tyrosine phosphatases (PTPs) in cancer progression cell adhesion dynamics in brain tumors signal transduction mechanisms molecular imaging agents for tumor detection novel therapeutics targeting proteolyzed PTPmu fragments Her lab's landmark discovery of PTPmu proteolysis in glioblastoma multiforme (GBM) has led to platform technologies for "see(k) and destroy" cancer strategies. Imaging Innovations : The lab develops fluorescent peptides (e.g., SBK2) for real-time surgical imaging SBK2-Gd MRI agents with superior tumor contrast radioisotope-conjugated PET agents for targeted radiotherapy nanoparticle diagnostics for invasive gliomas ultrasound nanobubble contrast agents These tools address critical gaps in imaging tumor boundaries and microenvironment interactions. Scientific Awards : Elected Senior Member, National Academy of Inventors (2022) Equalize National Woman Academic Inventor Finalist (2021) Mather Spotlight Prize for Women of Achievement, CWRU (2019) Distinguished Faculty Researcher, CWRU (2018) Special Achievement Award, University of Dayton National Alumni Association (2011)

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Ting-Chung Poonمشاهده پروفایل

استاد

Virginia Polytechnic Institute and State UniversityUnited States

Ting-Chung Poon is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. His research focuses on optical scanning holography (OSH), digital holography, and 3D imaging applications. He leads the Optical Scanning-Holographic Imaging Group (OSIG), which explores OSH for 3D imaging, processing, and display, emphasizing 2D optical heterodyne scanning techniques. Education: Ph.D., University of Iowa, 1982 M.S.E.E., University of Iowa, 1979 B.A., University of Iowa, 1977 Research Interests: Optical Scanning Holography (OSH) and its applications in 3D imaging Computer-Generated Holography (CGH) Quantitative Phase Imaging Optical Cryptography Efficient Hologram Algorithms His work spans theoretical advancements and practical implementations, including encryption systems, noise reduction techniques, and high-resolution 3D reconstruction. Recent Research Trends: Focus on polygon-based CGH algorithms for faster rendering Integration of machine learning for speckle noise reduction and hologram classification Development of adaptive and compressive holography methods for industrial and biomedical applications Labs & Teams: Optical Scanning-Holographic Imaging Group (OSIG) at Virginia Tech Collaborations with institutions globally, including conferences on digital holography and photonics

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Bradley Hayesمشاهده پروفایل

دانشیار

University of ColoradoUnited States

Bradley Hayes is an Associate Professor in the Department of Computer Science at the University of Colorado Boulder, affiliated with the College of Engineering and Applied Science. He leads the Collaborative AI and Robotics (CAIRO) Lab, focusing on creating autonomous robots that collaborate effectively with humans through advances in explainable AI, machine learning, and human-robot interaction. His prior research includes foundational work at MIT's Interactive Robotics Group and Yale's Social Robotics Lab. Research interests span Explainable AI, Learning from Demonstration, Hierarchical Reinforcement Learning, Computer Vision, Natural Language Processing, and Cognitive Science. His work emphasizes making human-robot teams more efficient and safe through innovations like emotionally expressive robotic motion, socially aware navigation, and AR-based collaboration tools. Key contributions include techniques for robust robotic exploration, generative occupancy mapping, and systems for improving human trust through predictable robot behavior. His work has been applied to teleoperation training, surgical assistance, and space exploration scenarios. Grants and partnerships support development of assistive robotic canes and AR interfaces for collaborative tasks. Lab activities emphasize translating theoretical advancements into practical systems through close collaboration between researchers, engineers, and end-users. Education efforts include developing foundational robotics curricula addressing autonomy, perception, and control systems.

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Bastian Pfauمشاهده پروفایل

پژوهشگر

Max Born Institute for Nonlinear Optics and Short Pulse SpectroscopyGermany

Dr. Bastian Pfau serves as Department Head of the “Imaging and Coherent X-rays” (B2) division and Project Coordinator for “Transient Structures and Imaging with X-rays” at the Max Born Institute in Berlin, where he has conducted postdoctoral research since 2016. His work pioneers nanoscale magnetic imaging using coherent X-ray techniques, with significant contributions to ultrafast magnetization dynamics and topological spin structures. His academic foundation includes a Dr. rer. nat. (PhD) in Physics from Technical University Berlin (2013) with thesis “Imaging magnetic nanostructures using soft x-ray Fourier transform holography,” and a Diplom (MSc) in Physics from Technical University Dresden (2006) focused on “Combining photon correlation spectroscopy and fluctuation analysis for investigating diffusion dynamics.” Additional research experience spans Lund University (2014-2015), Technical University Berlin (2010-2013), and Helmholtz Center Berlin (2006-2010). Dr. Pfau’s research centers on developing and applying X-ray holography and coherent diffraction imaging to visualize magnetic nanostructures at nanometer-femtosecond scales. His group specializes in ultrafast magnetization dynamics , skyrmion imaging , and element-specific magnetic probing using soft X-rays. Key innovations include achieving 5 nm resolution magnetic imaging and demonstrating all-optical helicity-independent switching via plasmonic nanostructures, with applications in next-generation spintronic devices and magnetic storage technologies. Analysis of his 15 most recent publications reveals dominant themes in nanoscale magnetic imaging (particularly skyrmions and topological textures), ultrafast opto-magnetic effects using extreme ultraviolet radiation, and advanced X-ray methodologies for capturing transient magnetic states. His work consistently bridges fundamental physics with practical instrumentation development, as evidenced by contributions to laser-driven plasma sources and tabletop X-ray setups. As Department Head of B2, Dr. Pfau leads a multidisciplinary team operating cutting-edge X-ray microscopy facilities at MBI. The group maintains strong collaborations with international synchrotron facilities (including BESSY II) and free-electron laser centers, focusing on developing MHz-repetition-rate pump-probe capabilities and high-resolution magnetic imaging techniques. Current projects emphasize real-time visualization of light-induced phase transitions and magnetic switching phenomena in functional materials.

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Yannis Stylianouمشاهده پروفایل

استاد

University of CreteGreece

Yannis Stylianou is Professor of Speech Processing at University of Crete and Senior Research Scientist at Apple. Former positions include AT&T Labs Research, Bell-Labs, and Toshiba Cambridge Research Lab. IEEE Fellow with PhD from ENST-Paris and over 200 publications. Research spans: Adaptive speech/audio modeling Neural speech synthesis/enhancement Biomedical signal processing Awards include: IEEE Fellowship French Ministry Research Fellowship ENST Graduate Scholarship Recent work focuses on neural TTS architectures, intelligibility enhancement, and multimodal synthesis. Organizes annual International Summer School on Speech Processing.

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Geoffrey Handsfieldمشاهده پروفایل

استادیار

University of North Carolina at Chapel HillUnited States

Geoffrey Handsfield is an Assistant Professor at the University of North Carolina at Chapel Hill, holding appointments in the Department of Orthopaedics and the Lampe Joint Department of Biomedical Engineering. His work integrates advanced medical imaging, computational modeling, and mechanical experimentation to improve clinical orthopaedic medicine and understand musculoskeletal form and function. Educated at East Carolina University (B.S. Physics, Summa Cum Laude with Mathematics Minor), the University of Virginia (Ph.D., Biomedical Engineering), and as a Whitaker Postdoctoral Scholar at the University of Auckland, his research focuses on musculoskeletal MRI, computational modeling of muscle-tendon interactions, and pediatric cerebral palsy rehabilitation. Education: Ph.D., Biomedical Engineering, University of Virginia, 2014 Postdoctoral Fellowship, Auckland Bioengineering Institute, 2014–2016 (Whitaker Scholar) B.S., Physics (Summa Cum Laude), Mathematics Minor, East Carolina University, 2008 Research Interests: Dr. Handsfield’s lab pioneers techniques like ultra-high contrast MRI and 3D ultrasound to study muscle-fascia interactions, tendon mechanics, and pediatric cerebral palsy. Key areas include: Image-based computational models for personalized musculoskeletal analysis Muscle architecture and regeneration in children and athletes Biomechanical interventions for cerebral palsy rehabilitation Non-invasive muscle profiling for clinical decision-making Awards: Aotearoa Early Career Research Fellow, Robertson Foundation Early Career Research Award, Australia-New Zealand Orthopaedic Research Society Whitaker Postdoctoral Scholar Academic All-American in Swimming & Diving (2007–2008) Advising & Grants: While specific grant details are not listed, his lab’s focus on pediatric cerebral palsy and musculoskeletal modeling suggests involvement in NIH-funded or foundation-sponsored research. No formal advisees are listed in the provided data. Labs & Teams: His interdisciplinary lab collaborates with clinicians and engineers to translate imaging and modeling innovations into clinical practice, focusing on tools like the dSIR MRI sequence and high-dimensional muscle clustering for athlete and pediatric populations.

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Hao Zhangمشاهده پروفایل

دانشیار

University of Massachusetts AmherstUnited States

Hao Zhang is an Associate Professor in the Department of Computer Science at the Manning College of Information and Computer Sciences (CICS), University of Massachusetts Amherst. He directs the Human-Centered Robotics Laboratory (HCRLab), focusing on lifelong collaborative autonomy, robot adaptation, and human-robot teaming. His research integrates robotics, AI, and machine learning to develop algorithms for real-world applications like manufacturing, autonomous driving, and environmental monitoring. He holds an NSF CAREER Award and DARPA Young Faculty Award, among other recognitions. Dr. Zhang earned a PhD from the University of Tennessee, Knoxville (2014) and an MS from the Chinese Academy of Sciences (2009). His work addresses challenges in unstructured environments through innovations like self-reflective terrain adaptation and graph-based perception systems. He actively promotes equity in robotics through his PROGRESS outreach program. His research sponsors include NSF, DARPA, and industry partners such as Toyota. Publications span conferences like RSS, ICRA, and IROS, with best paper awards. He serves on editorial and program committees for top-tier journals/conferences including RA-L, NeurIPS, and AAAI.

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Minoru Koyamaمشاهده پروفایل

استادیار

University of TorontoCanada

Minoru Koyama is an Assistant Professor in the Department of Cell & Systems Biology at the University of Toronto Scarborough (UTSC). His research focuses on understanding the neural circuit mechanisms underlying behavioral development, particularly in zebrafish models. He employs advanced techniques such as optogenetics, voltage imaging, and CRISPR-based methods to study circuit maturation in the hindbrain and spinal cord. Education: Koyama holds a Ph.D. (2006), M.Sc. (2002), and B.Sc. (2000) in Biological Sciences from the University of Tokyo. Research Interests: His work investigates how neural circuits mature post-birth and contribute to complex behaviors, with applications to developmental brain disorders. His lab uses zebrafish as a model system, combining optics, genetics, and machine learning for behavioral analysis. Key projects include studying motor coordination development and refining imaging techniques like multi-plane microscopy and voltage indicators. Publications Highlight: Koyama’s recent work includes innovations in microscopy (e.g., HiLo speckle illumination) and genetic tools (e.g., TEMPO lineage tracing). These advancements enable precise observation of neural circuits and cellular dynamics. Lab & Recruitment: The Koyama Lab actively recruits graduate students and postdoctoral researchers. No specific grants are detailed, but his work reflects broad interdisciplinary collaborations in neuroscience and biotechnology. Labs/Teams: His lab focuses on developmental neurobiology, leveraging cutting-edge imaging and genetic engineering to explore neural circuit function across vertebrate development.

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Avniel Singh Ghumanمشاهده پروفایل

دانشیار

Carnegie Mellon UniversityQatar

Dr. Avniel Singh Ghuman is an Associate Professor in the Department of Neurological Surgery at the University of Pittsburgh School of Medicine. He serves as Director of the Cognitive Neurodynamics Lab and plays a key role in advancing MEG (Magnetoencephalography) Research at the university. His work bridges clinical neurosurgery with fundamental neuroscience research to understand visual perception mechanisms. Dr. Ghuman's educational background includes: BA in Math and Physics from The Johns Hopkins University (1998) PhD in Biophysics from Harvard University (2007) Postdoctoral training at the National Institute of Mental Health Dr. Ghuman's research focuses on how the brain transforms visual input into meaningful perception of objects, faces, words, and social images in real-world contexts. His laboratory employs both invasive (intracranial EEG) and non-invasive (MEG) techniques to examine the spatiotemporal dynamics of neural activity during visual processing. The lab integrates multivariate machine learning methods, network analysis, and direct neural stimulation to investigate information processing at both local brain regions and distributed network levels. Recent work has pioneered methods for studying brain activity during authentic social interactions and natural behavior. His publication record demonstrates significant contributions to understanding real-world face perception, neural dynamics during natural behavior, and the application of advanced analytical techniques to brain imaging data. His research has revealed how brain network dynamics form a 'punctuated equilibrium' of stable states with transitory bursts between them, coinciding with behavioral shifts in everyday activities. Dr. Ghuman has received notable recognition for his work: Young Investigator Award from NARSAD (2012) Award for Innovative New Scientists from the National Institute of Mental Health (2015) His research has been featured in prominent media outlets including MIT Technology Review, The Wall Street Journal, and Carnegie Mellon University publications. As Director of the Cognitive Neurodynamics Lab, Dr. Ghuman leads a research program that has advanced our understanding of how the brain processes visual information in real-world environments, with implications for both fundamental neuroscience and clinical applications.

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