جست‌وجوی استاد و پژوهشگر

Gonzalo Besuievskyمشاهده پروفایل

دانشیار

• Computer graphics
• Global illumination
• Radiosity
• +۴ مورد دیگر

Gonzalo Besuievsky is Associate Professor at the Department of Computer Science and Applied Mathematics of the University of Girona , Spain. He leads research on physically-based rendering and global illumination, with particular emphasis on Monte-Carlo methods and dynamic radiosity environments. Education: PhD in Computer Science, Universitat Politècnica de Catalunya , 2001 — Dissertation: "A Monte Carlo Approach for Animated Radiosity Environments" Research Interests: His work spans several inter-related domains: Global Illumination & Radiosity: developing algorithms for realistic light transport in synthetic scenes. Monte Carlo Techniques: adaptive and hierarchical sampling to accelerate rendering. Dynamic Environments: efficient update schemes for animated lighting and moving light sources. Daylighting Simulation: integrating sunlight models into architectural 3-D workflows. Motion Blur & Temporal Coherence: novel methods to render motion-blurred radiosity images. Publication Trends: Across his 1993–2006 publications, a clear evolution is visible from foundational stochastic ray-tracing work toward sophisticated Monte-Carlo radiosity frameworks that handle dynamic lighting, daylighting, and frame-to-frame coherence for animations. Labs & Groups: He is affiliated with the Girona Graphics Group , a research team devoted to advanced graphics and visualization technologies.

• Model-Based Design Methods
• Design Automation
• Optimization
• +۵ مورد دیگر

Marc Geilen is an Associate Professor at the Electronic Systems group of Eindhoven University of Technology (TU/e) . He leads the Model-Based Design Lab within the CompSOC Lab and High Tech Systems Center .

Jennyمشاهده پروفایل

استاد

• Turbulent Combustion Modeling
• Computational Fluid Dynamics
• Rarefied Gas Kinetics
• +۴ مورد دیگر

Professor Jenny leads the Jenny Research Group at ETH Zürich, specializing in turbulent reactive flows, rarefied gas kinetics, and biomedical fluid dynamics. Her work bridges fundamental research with industrial applications in energy systems and fluid mechanics. Develops advanced turbulence models (TDDM, hybrid LES/RANS) for multi-scale flows Pioneers data assimilation frameworks for RANS simulations using adjoint methods Advances particle-based stochastic algorithms for fractured porous media transport Her recent publications emphasize adaptive time integration techniques, probabilistic modeling of non-linear transport phenomena, and optimized simulation tools for hydrogen storage systems. The group's methodological innovations focus on reducing computational costs while maintaining physical accuracy through novel regularization strategies. Key applications include combustion device optimization, high-pressure tank filling analysis, and fractured reservoir simulations. Current projects integrate machine learning with traditional CFD methods to address challenges in droplet clustering, flame surface density propagation, and supersonic spray dynamics. The research framework spans from direct numerical simulations of fundamental flow physics to industrial-scale hybrid modeling implementations.

• Machine Learning
• Non-parametric Methods
• Computational Methods
• +۶ مورد دیگر

Yifan Chen is an Assistant Professor in the Department of Computer Science and affiliate faculty in the Department of Mathematics at Hong Kong Baptist University's Faculty of Science. He joined HKBU in Fall 2023 after completing his PhD in Statistics from the University of Illinois Urbana-Champaign in 2023 under the guidance of Prof. Yun Yang. His educational background includes: B.S. in Statistics from Fudan University (2018), advised by Prof. Juan Shen and Prof. Chenghong Zhang Ph.D. in Statistics from University of Illinois Urbana-Champaign (2023), advised by Prof. Yun Yang Dr. Chen's research focuses on developing efficient algorithms for machine learning, with particular emphasis on non-parametric models and neural networks featuring intensive matrix operations. His work bridges statistical theory with practical computational challenges in modern machine learning systems, especially those involving Transformers (language models) and Graph Neural Networks (GNNs). He approaches machine learning from both theoretical and applied perspectives, seeking to understand statistical structures while addressing real-world computational constraints. His publication record shows consistent output in top-tier venues including ICML, NeurIPS, KDD, and EMNLP, with recent work spanning graph coarsening, optimal transport, efficient language model fine-tuning, and causal inference. His research demonstrates strong mathematical foundations combined with practical applications in AI systems. Among his notable achievements: NSFC Young Scientists Fund (2025) GDSTC General Program funding (2024) RGC Early Career Scheme proposal grant (2024) ICML 2023 Grant Award ($1,500) Dr. Chen actively mentors students through his research group, supervising PhD students and visiting research assistants. He has successfully guided students who have gone on to PhD programs at institutions including Institute of Science Tokyo, HKU, Fudan, and NUS. His teaching includes COMP 7070 Advanced Topics in Artificial Intelligence and Machine Learning, which covers core machine learning concepts for AI application research, and COMP 2027 Applied Linear Algebra for Computing. His research group focuses on efficient machine learning algorithms, with current projects spanning graph neural networks, optimal transport, language model efficiency, and causal inference. He collaborates with researchers from institutions including UIUC, Fudan University, and industry labs like Amazon Alexa AI.

• Numerical Analysis
• Scientific Computing
• Partial Differential Equations
• +۳ مورد دیگر

Herbert Egger is a Professor of Numerical Analysis and Scientific Computing at Johannes Kepler University (JKU) Linz and heads the Institute of Numerical Mathematics. He is also a Group Leader at RICAM (Johann Radon Institute for Computational and Applied Mathematics) and Scientific Director at the Austrian Academy of Sciences. His research focuses on advanced numerical methods for partial differential equations, including structure-preserving discretizations, inverse problems, and computational electromagnetics. Current projects include SFB F90-N (CREATOR) for electric machine co-simulation, SPP 2256 for phase-field modeling in additive manufacturing, and TRR 146 on multiscale soft matter systems. Key research areas: mixed/hybrid finite element methods, energy-based modeling, model order reduction, radiative transfer, and inverse problem stabilization. His recent work emphasizes nonlinear magnetostatics, phase separation models, and efficient solvers for time-dependent systems. Egger collaborates internationally with institutions like TU Eindhoven and TU Darmstadt.

Daniel Wichsمشاهده پروفایل

استاد

• Cryptography
• Computer Security
• Algorithms
• +۷ مورد دیگر

Daniel Wichs is a tenured Professor at the Khoury College of Computer Sciences at Northeastern University in Boston. He is a prominent researcher in the field of cryptography and serves as a Senior Scientist at NTT Research. His academic journey includes a PhD from New York University under Yevgeniy Dodis, a postdoctoral fellowship at IBM Research T.J. Watson, and degrees from Stanford University. Current Position: Professor at Northeastern University Prior Positions: IBM Josef Raviv Memorial Postdoctoral Fellow (2011-2013) Education: PhD NYU (2011), BS/MS Stanford (2005) Professor Wichs specializes in cryptography with research interests spanning computing on encrypted data, program obfuscation, lattice-based cryptography, information-theoretic cryptography, and foundational aspects of cryptography. He also maintains broad interests in computer security, algorithms, complexity theory, coding theory, and information theory. His research group includes current PhD students Manu Kondapaneni, LaKyah Tyner, and Ethan Mook, along with numerous successful alumni who have become professors at institutions worldwide. His recent publications demonstrate a strong focus on advanced cryptographic primitives including homomorphic encryption, zero-knowledge proofs, private information retrieval, and functional encryption. These works frequently appear at top-tier conferences like STOC, FOCS, CRYPTO, and EUROCRYPT, with several receiving best paper awards. His research often bridges theoretical foundations with practical applications in privacy-preserving computation. Best Paper at STOC 2023 Alfred P. Sloan Research Fellowship (2018) NSF CAREER Award (2018) J.P. Morgan Faculty Research Award (2022) IBM Postdoctoral Fellowship (2011-2013) Professor Wichs actively contributes to the academic community through service as Area Chair for CRYPTO 2025 and EUROCRYPT 2024, Program Chair for ITC 2020, General Chair for STOC 2016, and membership on numerous program committees. He teaches advanced courses including Foundations of Cryptography (CS 7810) and Theory of Computation (CS 3800), and has organized events like the Charles River Crypto Day and the Simons Summer Program in Cryptography 2025. His research group operates at the forefront of cryptographic theory, addressing fundamental questions about secure computation on encrypted data while developing practical cryptographic tools for real-world applications.

Niall McGoldrickمشاهده پروفایل

عضو هیئت علمی

• Dental Public Health
• Oral Health Improvement
• Vulnerable Populations and Oral Health
• +۵ مورد دیگر

Niall McGoldrick serves as a Clinical Lecturer and Honorary Consultant in Dental Public Health at the University of Dundee's School of Dentistry. His academic appointments reflect a strong integration of clinical practice, public health, and academic research in the dental field. Dr. McGoldrick's educational background includes a Bachelor of Dental Surgery (2013), Master of Public Health (2019), and Fellowship in Dental Surgery (Dental Public Health) (2021), all from the University of Dundee. His professional trajectory demonstrates a clear progression from clinical dental training to specialized expertise in public health applications for dentistry. His research interests focus on critical areas of dental public health including oral health improvement for vulnerable populations, particularly people experiencing homelessness and those with drug use experiences. He investigates healthcare pathways for people with conditions like Osteogenesis Imperfecta, develops co-design methods for health education materials, and examines infectious disease transmission patterns in dental settings. His work on the 'Lessons Learned from Contact Tracing COVID-19 cases in Dental Settings in East Scotland' study provided important evidence that transmission was confined to non-clinical areas, influencing pandemic planning for dental practices. Dr. McGoldrick maintains an active research portfolio with 31 research outputs between 2017-2025, showing increasing publication activity in recent years. His work spans multiple formats including original research articles, reviews, conference presentations, and media engagement on dental public health issues. His notable recognitions include: Saltire Society 40 under 40 award (2023) Scottish Health Awards: Young Achiever (2017) Tattersall PhD Fellowship (2020) The Ben Walton Trust Award (2013) Postgraduate Award for Best voluntary scheme to promote oral health improvements (2015) Dr. McGoldrick currently leads or collaborates on multiple funded projects including 'Improving Healthcare Pathways for People with Osteogenesis Imperfecta,' 'Let's Talk About Mouth Cancer,' and initiatives focused on sustainable patient and public involvement in dental research. His work demonstrates strong connections between academic research, clinical practice, and public health policy development in the dental field. His research group actively engages with community organizations, NHS services, and international partners to address dental public health challenges, particularly focusing on reducing health inequalities and improving access to quality dental care for marginalized populations across Scotland.

Francois Xavier COUDOUXمشاهده پروفایل

استاد

• Digital video communications
• Multimedia transmissions
• End-to-end optimization
• +۷ مورد دیگر

Francois Xavier COUDOUX is a Professor in the Digital Communications group at IEMN DOAE and currently serves as Director of the Electronics Department at INSA Hauts-de-France since 2020. His academic career has been primarily associated with institutions in the Hauts-de-France region, including significant roles at the University of Valenciennes and now INSA Hauts-de-France. Within IEMN, he has held leadership positions including Deputy Director of IEMN-DOAE (2010-2018), member of the IEMN Laboratory Council (2001-2011), and current member of the Scientific Council of the IEMN (2019-present). His educational background includes a Doctorate in Electronics from the University of Valenciennes (1994), Magistère in Image Engineering (1991), DEA in Electronics: imaging and ultrasound (1991), Master's in Audiovisual Communication (1990), and DEUG in Sciences (1988). Professor COUDOUX's research focuses on four main areas: end-to-end optimization strategies for multimedia transmissions over wired or wireless networks; robust MIMO-OFDM transmission of video streams; video pre- and post-processing systems; and data transmission over electrical networks. His work integrates expertise in image/video processing with telecommunications to optimize quality of service in video communication systems. He has contributed significantly to the reduction of blocking artifacts in DCT-coded images and videos, developing perceptual approaches to enhance visual quality in compressed video. His scientific contributions have been recognized through numerous publications since the early 1990s, with consistent output in prestigious journals and conferences. His research shows a clear evolution from foundational work on blocking artifact reduction to more complex systems involving MIMO-OFDM transmission and cross-layer optimization approaches. The publications demonstrate expertise spanning signal processing, image/video coding, telecommunications, and perceptual quality assessment. Among his notable achievements are leadership of the ANR TOSCANE project (2007-2010), participation in the CPER 2009-2013 CISIT research program, and two research contracts with Philips Electronics Laboratories. He has also served as a scientific expert for the ANR, AERES, and for both Walloon and Flemish regions of Belgium. Professor COUDOUX has supervised 8 PhD theses throughout his career and has been actively involved in academic service, including organizing conferences like ISIVC 2012, serving on program committees for CISST and ITST conferences, and reviewing for journals including IEEE Communications Letters and IEEE Transactions on Broadcasting. His teaching responsibilities focus on telecommunication systems, digital communications, and signal processing, particularly in image and video domains.