جست‌وجوی استاد و پژوهشگر

Ruohan Gaoمشاهده پروفایل

استادیار

• Computer Vision
• Machine Learning
• Multisensory Machine Intelligence
• +۳ مورد دیگر

Ruohan Gao is an Assistant Professor in the Department of Computer Science at University of Maryland, College Park, leading the UMD Multisensory Machine Intelligence Lab. He holds affiliations with UMIACS, MRC, and AIM institutes. His research focuses on Computer vision and machine learning Multisensory machine intelligence (sight, sound, touch) Robotic manipulation through sensory fusion Audio-visual spatialization Sim2Real transfer methods His recent publications (2025-2022) span ICCV (5 papers) CVPR (6 papers) CoRL (4 papers) ECCV (2 papers) BVMC (1 paper) covering topics like differentiable acoustic rendering, audio-visual navigation, and embodied AI systems. Scientific recognition includes Michael H. Granof Award (UT Austin Top Dissertation) BMVC Best Paper Runner-Up CVPR Highlight Paper CVPR Best Paper Finalist He actively mentors students and collaborates with institutions including Stanford University, UT Austin, and Northwestern University (future affiliation).

Lars Krecklauمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Procedural Modeling
• Real-Time Rendering
• +۳ مورد دیگر

Dr. Lars Krecklau is a researcher at the Department of Computer Science , RWTH Aachen University . He specializes in procedural modeling, real-time rendering, and urban reconstruction. His work includes algorithms for efficient 3D visualization of cityscapes and interactive modeling tools for non-programmers. Research Focus : Procedural modeling, real-time rendering, urban visualization Key Contributions : Procedural facade rendering, historical city interpolation, interconnected structure modeling His publications focus on GPU-accelerated procedural graphics, temporal interpolation of historical data, and intuitive 3D modeling interfaces. He has contributed to frameworks like Houdini and developed techniques for memory-efficient rendering. Email : krecklau@informatik.rwth-aachen.de

T N. Vijaykumarمشاهده پروفایل

استاد

• Computer Architecture
• Machine Learning
• High-Performance Computing
• +۷ مورد دیگر

T. N. Vijaykumar is a Professor of Electrical and Computer Engineering at Purdue University, with a courtesy appointment in Computer Science. He joined the university in 2003. His research focuses on computer architecture, machine learning acceleration, high-performance computing, and hardware-software co-design. He holds degrees from Birla Institute of Technology and Science (BE, MSc) and the University of Wisconsin (MS, PhD in Computer Science). Education: B.E. (Hons), Electrical and Electronics Engineering, Birla Institute of Technology and Science (1990) M.Sc. (Tech), Computer Science, Birla Institute of Technology and Science (1992) M.S. and Ph.D., Computer Science, University of Wisconsin (1997) His research interests span GPU architectures , memory systems , neural network acceleration , and secure computing . Recent work includes optimizing sparse tensor processing, secure speculative execution, and distributed training frameworks for mobile robotics. Publications highlight contributions to GPU kernel concurrency, neural radiance fields, and memory consistency verification. His work often bridges hardware design and software efficiency, with applications in data centers and edge computing. Notable grants include projects like QED (scalable hardware memory verification) and ESPIM (sparse processing-in-memory for ML inference). He has also contributed to frameworks like Disorf for real-time rendering in robotics. Labs/Teams: Active involvement in Purdue’s Computer Science and ECE departments, with collaborations on AI hardware and systems research.

Felix Wechslerمشاهده پروفایل

پژوهشگر

• Computational Optics
• 3D Printing
• Optical Propagation
• +۳ مورد دیگر

Felix Wechsler is a Doctoral Assistant and PhD Student in Photonics at the École Polytechnique Fédérale de Lausanne (EPFL), working in the Laboratory of Applied Photonics Devices (LAPD) under Prof. Christophe Moser. He is also a PhD Student Representative in the EDPO-GE group within the Doctoral Program in Photonics. His primary affiliation is with the School of Engineering (STI) and the Department of Microengineering (IEM) at EPFL. Education: Felix holds a Bachelor of Science in Informatics and Physics from the Technische Universität München (TUM), and a Master of Science in Photonics from Friedrich Schiller University Jena (FSU Jena). Research Interests: His research focuses on computational tools for tomographic 3D printing, optical wave propagation, and microscopy. He develops innovative methods using Julia programming, including packages like SwissVAMyKnife.jl and Dr.TVAM. His work aims to improve volumetric additive manufacturing through advanced optical techniques and algorithmic optimization. Publications: Recent work includes scalable optical propagation methods, MEMS-based light modulators for holographic manufacturing, and inverse rendering frameworks for tomographic additive processes. These contributions highlight advancements in both theoretical and applied aspects of optical engineering and manufacturing. Awards: No scientific awards have been explicitly mentioned in the provided information. Advising & Collaborations: Felix has not yet advised students, but his research is supported through collaborations and institutional funding at EPFL. His involvement in developing open-source tools reflects his commitment to reproducibility and community-driven science. Labs & Teams: He is part of the LAPD laboratory and collaborates with the Realistic Graphics Lab (RGL) at EPFL, as evidenced by his reposts on Bluesky.

Daljit Singh Dhillonمشاهده پروفایل

استادیار

• Computer Graphics
• Bio-physical Modeling and Simulation
• Realistic Appearances
• +۳ مورد دیگر

Dr. Daljit Singh Dhillon is an Assistant Professor in the Visual Computing division at Clemson University's School of Computing. He joined Clemson in January 2019 after a research associate position at Imperial College London (2017–2018) and a Swiss National Science Foundation fellowship at the University of Geneva (2016–2017). His research focuses on modeling material appearances, surface geometries, and bio-physical systems, with applications in computer graphics, fabrication, and interdisciplinary collaborations. Education PhD in Computer Science, University of Bern, Switzerland (2011–2015) M.Sc. (Engg.), Indian Institute of Science, Bengaluru (2007–2010) Bachelor's in Computer Engineering, University of Mumbai (1995–1999) Research Interests His work bridges visual computing and interdisciplinary fields, emphasizing practical measurement and modeling of materials like skin, holographic surfaces, and biological nanostructures. Notable contributions include spectral skin reflectance modeling, diffraction effects in reptile skin, and feather appearance rendering. He also collaborates on NSF-funded projects, such as developing light-scattering models for bird feathers. Grants & Awards NSF-Small Grant ($477K) for feather light-scattering research (2020) SNSF Early Postdoc Mobility Fellowship (2016–2017) Labs & Teams He leads research on material appearance and surface geometry processing at Clemson, with students like Makayla Master (PhD) and Srihith Alwala (research assistant). Collaborations include paleontologists and biologists for projects like feather structural modeling.

Feng Luoمشاهده پروفایل

استاد

• Deep Learning
• Bioinformatics
• Computational Biology
• +۳ مورد دیگر

Feng Luo is a Professor at the School of Computing , Clemson University, and founding director of the Clemson AI Research Institute for Science and Engineering (AIRISE). He earned his Ph.D. in Computer Science from the University of Texas at Dallas in 2004 and held a postdoctoral position at the University of Texas Southwestern Medical Center before joining Clemson in 2006. Research Focus: Deep Learning, High-Throughput Biological Data Analysis, Computational Genomics Laboratory: BigData Analytics Research Group ( BigData@Clemson ) His research spans Deep Learning applications in bioinformatics, with emphasis on genomic data analysis and network biology . Recent work includes genome assembly algorithms, methylation detection, and AI-driven cybersecurity for IoT devices. His 15 most recent publications (2024-2025) focus on advanced AI/ML methods for 3D genome reconstruction , molecular structure generation , video denoising , and diffusion model security , reflecting interdisciplinary work bridging Computer Science with Genomics and Materials Science . Dr. Luo has advised numerous graduate students and postdocs, several of whom now hold positions at companies like Amazon , Meta , and LinkedIn . He actively serves on university and professional committees as a Senior IEEE Member and ACM Member . His funded projects include NSF , DOE , and NIFA grants addressing citrus disease resistance , off-road autonomy , and AI-enabled healthcare .

Faiz Rahmanمشاهده پروفایل

دانشیار

• Semiconductor Materials
• Photonics
• Nanotechnology
• +۳ مورد دیگر

Dr. Faiz Rahman is an Associate Professor in Electrical Engineering and Computer Science at Ohio University's Russ College of Engineering and Technology. His research spans semiconductor materials, photonic devices, and lighting technologies, with specific focus on laser-driven illumination systems and zinc oxide semiconductors. Dr. Rahman holds adjunct appointments with the Nanoscale Quantum Phenomena Institute. Education: Ph.D. in Semiconductor Science & Technology from Imperial College London MSc from Imperial College London B.S./M.S. in Physics from Patna University Research expertise includes: Semiconductor materials characterization Photonics and laser technology Hybrid LED/laser lighting systems Nanofabrication techniques His publications demonstrate consistent focus on light-emitting technologies, with recent work exploring phosphor materials, microcavity structures, and UV radiation effects. The research employs methods ranging from cathodoluminescence studies to atomic layer processing. Dr. Rahman has authored books including From Edison to LEDs: The Science and Story of Light Sources and holds patents in solid-state emitters. No major scientific awards are listed. He maintains research collaborations and founded Electrospell Ltd. during his tenure at the University of Glasgow. Current projects involve omnidirectional light-trapping structures and laser-excited phosphors.

Michael Meredithمشاهده پروفایل

دانشیار

• Digital Humanities
• Augmented Reality
• 3D Graphics
• +۴ مورد دیگر

Dr Michael Meredith is an Associate Professor and Associate Head in the School of Computing and Digital Technologies at Sheffield Hallam University. He also serves as the Student Recruitment Lead for the School. His research focuses on digital humanities, augmented reality, 3D graphics, and mathematical modeling, with applications in cultural heritage, biomechanics, and interactive technologies. Meredith holds a BEng and PhD in Computer Science from the University of Sheffield. Education: BEng in Computer Science PhD in Computer Science (University of Sheffield) His research spans diverse areas including virtual world applications for historical research, consumer-grade technology for heritage digitization, and real-time inverse kinematics for character animation. He has contributed to projects modeling medieval scribal hands, virtual environments for visitor attractions, and navigational AR systems using fiducial markers. Meredith's publications reflect expertise in interdisciplinary research, blending computer science with humanities. His work has been recognized with Best Paper Awards at GAME-ON 2004 and GDTW 2004. He teaches programming and software engineering courses, emphasizing practical applications of advanced computer science concepts. Key collaborations include projects on authorship attribution in medieval manuscripts and virtual reconstruction of heritage sites using accessible technologies. His research often bridges technical innovation with cultural and historical preservation.

Anna Soraceمشاهده پروفایل

استادیار

• Cancer Imaging
• Drug Delivery
• Tumor Microenvironment
• +۲ مورد دیگر

Anna Sorace is an Assistant Professor in Biomedical Engineering at the University of Alabama at Birmingham, jointly appointed in the School of Engineering and Heersink School of Medicine. Her research advances cancer diagnostics and treatment through imaging technologies and targeted drug delivery systems. Her work integrates quantitative imaging biomarkers for early cancer treatment response assessment and optimizes therapeutic delivery using multimodal approaches. Primary research domains include tumor microenvironment analysis and precision oncology applications. Recent publications focus on computational methods for facial reconstruction and medical imaging, demonstrating consistent innovation in neural network applications for 3D geometry processing. Trends show strong emphasis on real-time clinical translation of computer vision techniques. No awards or supervised students are documented.

Neill Campbellمشاهده پروفایل

استاد

• Visual Computing
• Machine Learning
• Computer Vision
• +۶ مورد دیگر

Neill D. F. Campbell is a Professor of Visual Computing and Machine Learning at the University of Bath, Department of Computer Science. He holds an honorary Associate Professor position at University College London. His research focuses on shape modeling, machine learning, and their applications in computer vision and graphics. Campbell directs the CAMERA research centre and co-leads the Centre for Mathematics and Algorithms for Data (MAD). He leads the MyWorld project, a £46M creative hub in the Bath-Bristol region. Education: PhD in Engineering (Automatic 3D Model Acquisition from Uncalibrated Images) from the University of Cambridge (2011), MEng in Engineering from the University of Cambridge (2006). Research Interests: Modeling shape and appearance using machine learning, Bayesian nonparametric models, generative models, uncertainty quantification, and applications in entertainment, health, and sports science. Active in developing structured uncertainty prediction networks (SUPN) and exploring generative models for inverse problems. Key Projects: MyWorld (Strength in Places Fund), CAMERA, EPSRC CDT in Statistical Applied Mathematics, and collaborations with industry partners. Recent work includes anomaly detection, depth estimation, and conditional sampling techniques. Awards: Royal Society Industry Fellow (2017–present). Over 54 research outputs spanning CVPR, ECCV, SIGGRAPH, and NeurIPS, focusing on structured uncertainty, generative models, and vision applications. Labs/Teams: Director of CAMERA, co-director of MAD, and collaborator in UKRI CDT in Responsible AI. Active in organizing workshops on uncertainty quantification in computer vision (UNCV).

Leonid Sigalمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Computer Graphics
• +۸ مورد دیگر

Leonid Sigal is an Associate Professor in the Department of Computer Science at the University of British Columbia (UBC), holding the NSERC Canada Research Chair (CRC II) in Computer Vision and Machine Learning and a CIFAR AI Chair at the Vector Institute. He also serves as an Academic Advisor to Borealis AI. His research focuses on visual understanding, including object recognition, scene analysis, motion capture, and the intersection of computer vision with machine learning and graphics. Prior roles include Senior Research Scientist at Disney Research and Adjunct Faculty at Carnegie Mellon University. Education: Ph.D. (Computer Science, Brown University, 2008), M.Sc. (Computer Science, Brown University, 2003), B.Sc. (Computer Science & Mathematics, Boston University, 1999). Research interests span computer vision challenges such as human motion analysis, activity recognition, and generative models, alongside cross-disciplinary work in robotics and psychology. Notable achievements include Best Paper Awards at WACV 2015 and AMD 2012/2006, and leadership in organizing workshops like VisStory and tutorials on 'Looking at People.' Awards include the Killam Accelerator Fellowship, NSERC DAS award, and recognition as Area Chair for CVPR 2022, ICML 2022, and IJCAI 2022. His lab advises numerous graduate students and postdocs, with active collaborations spanning industry (e.g., Disney, Borealis) and academia (e.g., CMU, Vector Institute).

Adithya K Pediredlaمشاهده پروفایل

استادیار

• computational photography
• computer graphics
• acousto-optics
• +۸ مورد دیگر

Adithya K Pediredla is an Assistant Professor in the Department of Computer Science at Dartmouth College. His research focuses on computational imaging systems that co-design hardware and software to enhance imaging capabilities. He holds a B.Tech from the National Institute of Technology, Warangal (India), an M.E. from the Indian Institute of Science (Bangalore), a Ph.D. from Rice University, and completed a postdoctoral fellowship at Carnegie Mellon University. Educational Background: B.Tech, National Institute of Technology, Warangal, India M.E., Indian Institute of Science, Bangalore, India Ph.D., Rice University Postdoctoral Researcher, Carnegie Mellon University His research interests include computational photography, computer graphics, acousto-optics, and computer vision. He explores adaptive sensing, depth imaging, computational microscopy, and imaging in non-line-of-sight scenarios. His work also involves physically-based rendering and inverse rendering techniques for advanced computational imaging applications. No scientific awards or grants are explicitly listed in the provided information. He advises no students (PhD/Master’s) as per the data, and no lab affiliations are specified beyond his personal website.

• Digital Watermarking
• Neural Representation
• Copyright Protection
• +۵ مورد دیگر

Renjie Wan is an Assistant Professor in the Department of Computer Science at Hong Kong Baptist University. He holds a BEng from the University of Electronic Science and Technology of China (2012) and a Ph.D. from Nanyang Technological University (2019). His research focuses on digital watermarking, neural representation, copyright protection, and AI security, with notable contributions in computational photography and image processing. He has received awards including the Microsoft CRSF Award and VCIP 2020 Best Paper Award. His academic journey includes a Wallenberg-NTU Presidential Postdoctoral Fellowship (2020–2022). He currently advises Ph.D. students in areas like neural radiance field watermarking and backdoor attack mitigation. Teaching responsibilities include courses on AI application development and Python for data analysis. Research Projects: Developing multispectral imaging algorithms for coastal surveillance Dynamic environment reflection separation techniques Face image reflection removal using neural radiance fields Awards: Meritorious Winner at Mathematical Contest in Modeling 2023 Silver Medal of 50th International Exhibition of Inventions Geneva His lab focuses on advancing AI security and 3D content protection through innovative techniques like neural radiance field watermarking and adversarial defense mechanisms.

Nils Thuereyمشاهده پروفایل

استاد

• Computer Graphics
• Fluid Dynamics
• Machine Learning
• +۳ مورد دیگر

Prof. Nils Thuerey is a Professor of Physically Based Simulation at the Technical University of Munich (TUM), within the TUM School of Computation, Information and Technology. He specializes in computer graphics, fluid dynamics, and machine learning applications in physics-based simulations. His work focuses on developing algorithms for fluid simulations, turbulence modeling, and differentiable physics solvers. He earned his doctorate in fluid simulations from the University of Erlangen-Nuremberg (2006) and held positions at ETH Zurich, ScanlineVFX, before joining TUM in 2013. Research Interests: Fluid Dynamics and Turbulence Modeling Machine Learning for Physics Simulations Deep Learning in Computer Graphics Differentiable Simulations and Inverse Problems Key Awards: Technical Oscar (2012) for contributions to fluid effects in films/games ERC Starting Grant (2014) for 'realFlow' research University of Erlangen Staedtler Graduation Award (2008) His recent work emphasizes integrating deep learning with physical models, such as differentiable solvers for fluid dynamics and probabilistic methods for weather forecasting. He leads projects like WeatherBench and develops tools like φ-ML and phiflow for scientific computing.

Aysegul Dundarمشاهده پروفایل

استادیار

• Deep Learning
• Computer Vision
• Generative Models
• +۳ مورد دیگر

Aysegul Dundar is an Assistant Professor of Computer Science at Bilkent University, Ankara, Turkey. She previously served as a senior research scientist at NVIDIA in Santa Clara, USA. Her research focuses on deep learning algorithms for computer vision, particularly generative models, 3D reconstruction, and image editing. She leads the Generative Deep Learning Research Lab at Bilkent. Education: Ph.D. in Electrical and Computer Engineering, Purdue University (2016), supervised by Eugenio Culurciello. B.Sc. in Electrical and Electronics Engineering, Bogazici University, Turkey (2011). Research Interests: Her work emphasizes generative deep learning, with applications in 3D head stylization, image editing via diffusion models, and neural network architectures for vision systems. She explores disentangled latent spaces, GAN inversion, and robust instance segmentation. Awards & Funding: 2024: Young Scientist Award (BAGEP), EuroHPC AI Award. 2021: TÜBİTAK 3501 Grant. 2020: Marie Skłodowska-Curie Fellowship. 2018: 1st Place in CVPR Domain Adaptation Challenge. Teaching & Labs: Teaches CS 490 (Research in Computer Engineering/Science). Leads projects on image synthesis, with a focus on selective student recruitment for lab contributions. Prioritizes undergraduates actively engaged in lab activities.