جست‌وجوی استاد و پژوهشگر

Mohit Mendirattaمشاهده پروفایل

پژوهشگر

• Computer Vision
• Machine Learning
• Computer Graphics
• +۳ مورد دیگر

Mohit Mendiratta is a PhD student in Computer Science at the Universität des Saarlandes and a Researcher at the Max-Planck-Institut für Informatik, Germany. He is part of the Visual Computing and Artificial Intelligence department (Department 6) under the Graphics, Vision & Video group led by Prof. Dr. Christian Theobalt. His research focuses on advancing computer vision, machine learning, and computer graphics, particularly in areas like 3D human avatars, text-driven editing, and video semantic segmentation. Education includes a Master's in Visual Computing from Universität des Saarlandes (2018–2021) and an undergraduate degree in Electronics and Electrical Engineering from KIIT, Bhubaneswar, India (2013–2017). He has held roles such as Research Assistant at the Max Planck Institute and Fraunhofer Institute, and industry experience as an Associate Software Engineer at Zentron Labs. His research interests span developing novel techniques for photorealistic 3D avatars, text-based editing systems, and zero-shot semantic segmentation using diffusion models. He collaborates on projects like AvatarStudio and TEDRA, advancing applications in virtual reality and human-computer interaction. Mohit contributes to the Saarbrücken Research Center for Visual Computing and is affiliated with the International Max Planck Research School on Trustworthy Computing. His work bridges theory and practical applications in AI-driven visual computing.

Victoria C. Ramenzoniمشاهده پروفایل

استادیار

• Ecological Anthropology
• Coastal Resource Management
• Socioecological Systems
• +۳ مورد دیگر

Victoria C. Ramenzoni is an Assistant Professor in Marine Policy and Social Science at Rutgers University, leading the Coastal Communities Adaptation Lab. Her research focuses on socioecological systems, adaptation strategies, and environmental policy, with fieldwork in the U.S., Cuba, and Indonesia. She investigates how households adapt to environmental and socioeconomic uncertainty, emphasizing resource governance and nutritional health. Ramenzoni has secured grants from the NSF and NOAA, including a 2021 Coast and People grant studying climate adaptation in Northeast U.S. marginalized communities. She previously served as Executive Secretary of the Interagency Working Group on Ocean Social Sciences (IOSSWG) and contributed to NOAA’s socioeconomic indicator frameworks. Her work bridges anthropology, ecology, and policy to address climate change impacts on coastal livelihoods. Her research spans multiple regions: in the Northeast U.S., she examines commercial fishing adaptations during the pandemic and urban development pressures. In Cuba, she collaborates with Universidad de La Habana on dietary health and hurricane resilience in Yaguajay. In Indonesia, her studies in Flores and Kalimantan explore overfishing, peatland degradation, and traditional ecological knowledge. She employs ethnographic methods, nutritional assessments, and institutional analyses to evaluate long-term adaptation pathways. Ramenzoni’s grants include a National Academies-funded study on offshore extractive activities’ impacts in the Gulf of Mexico and a Texas Commission-backed project on socioecological indicators. She advocates for co-governance models and has published extensively on adaptation frameworks, socioecological monitoring, and the paradoxes of development in oil-dependent regions.

• Computational Fluid Dynamics
• Turbomachinery
• Aerodynamics
• +۴ مورد دیگر

Dr. Kidambi Sreenivas is an Associate Professor in Mechanical Engineering at the University of Tennessee at Chattanooga (UTC), affiliated with the College of Engineering and Computer Science. He holds a PhD in Mechanical Engineering and specializes in computational fluid dynamics (CFD), with a focus on unstructured multi-physics flow solvers and applications in aerospace, environmental systems, and biomedical engineering. His research bridges academia and industry, collaborating with NASA, the U.S. Navy, Department of Energy, and private companies. Dr. Sreenivas' research interests include rotating machinery simulations, pre-conditioners for non-ideal fluids, and real-world applications such as submarine hydrodynamics, wind farm optimization, aerodynamic efficiency of vehicles, and contaminant dispersal modeling. He has pioneered methods for simulating complex geometries and physics, including high-fidelity simulations of hypersonic vehicles, weapons bay cavities, and shock-wave interactions. Recent work emphasizes advanced CFD methodologies for high-speed flows, thermal effects on turbulence, and aerothermal characteristics of hypersonic test articles. His collaborations have led to practical solutions for drag reduction on Class 8 trucks and improved accuracy in wind turbine modeling. Dr. Sreenivas also contributes to educational initiatives, such as developing PIV systems for undergraduate fluid mechanics labs. His advising and grants reflect partnerships with federal agencies and private sectors, focusing on projects like microplastic sampling devices for stormwater management. These projects highlight his interdisciplinary approach to solving real-world engineering challenges through cutting-edge computational methods.

• Visual Perception
• Display and Lighting Systems
• Image Quality Assessment
• +۳ مورد دیگر

Ingrid E.J. Heynderickx is a Professor in Applied Visual Perception at the Human-Technology Interaction group within the Faculty of Industrial Engineering and Innovation Sciences at Eindhoven University of Technology (TU/e), where she also serves as Dean of the Department. She holds a part-time Visiting Research Professor role at Southeast University (China) since 2005. Her research focuses on optimizing display and lighting systems through understanding human visual perception, emphasizing both fidelity and preference in design, with attention to age and cultural variability. Academically, she earned her PhD in Physics from the University of Antwerp (1986) and spent 18 years at Philips Research, leading visual perception research. She became a Philips Research Fellow in 2005 before joining TU/e as Full Professor in 2013. She holds Fellow status with the Society for Information Displays (SID) and received the Otto Shade Prize (2015). Her recent work explores lighting solutions for office environments, roadway safety systems, and LED artifact mitigation. Notable projects include the Brainbridge initiative (2015–2016) on spectral lighting effects. Over 236 publications and 4 datasets reflect her contributions to lighting science and human-centric design. She advises on sustainable lighting technologies and collaborates globally, with recent media engagements discussing departmental leadership and smart lighting trends. Key research themes include visual attention modeling, illuminance preferences, and dynamic viewing behavior—issues critical for next-generation human-technology interfaces.

Yuntian Dengمشاهده پروفایل

استادیار

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Yuntian Deng is an Assistant Professor at the University of Waterloo and a Visiting Professor at NVIDIA. He holds affiliations with Harvard SEAS as an Associate and the Vector Institute as a Faculty Affiliate. He completed his PhD in Computer Science at Harvard under Professors Alexander Rush and Stuart Shieber, followed by a postdoc under Yejin Choi. His research focuses on Natural Language Processing and Machine Learning, with notable contributions in chatbot interaction analysis (WildChat), implicit reasoning models, and markup-to-image generation. He has developed influential tools like OpenNMT and WildVis, and his work has been featured in outlets like the Washington Post and used by OpenAI and Anthropic. Education: PhD in CS (Harvard), Postdoctoral Research (University of Washington). Key achievements include the ACM Gordon Bell Prize for GenSLMs, Best Demo Runner-up at ACL 2017, and Best Paper at DAC 2020. His research emphasizes scalable datasets, efficient reasoning techniques, and real-world applications of AI models. Research interests span NLP, machine learning algorithms, and their applications in areas like dialogue systems, generative models, and ethical AI evaluation. Notable projects include WildChat (1M ChatGPT interactions), implicit chain-of-thought reasoning, and neural steganography for text-based information hiding. His articles explore topics ranging from knowledge distillation to diffusion models, with a focus on bridging theoretical advancements and practical implementations. He actively collaborates with industry partners like NVIDIA and maintains open-source tools to advance AI research accessibility.

• Natural Language Processing
• Speech Recognition
• Multilingual Systems
• +۳ مورد دیگر

David Palmer is an Affiliate Associate Professor in the Department of Astronomy and Astrophysics. He is affiliated with Los Alamos National Laboratory (LANL). His research focuses on speech recognition, natural language processing, and multilingual systems, with particular emphasis on information extraction from audio and speech data. His work bridges computational linguistics and machine learning, addressing challenges in automated systems for audio comprehension and cross-language processing. Key research interests include robust information extraction from speech transcriptions, error detection in speech recognition, and multilingual processing for operational users. He has contributed to advancements in speaker identification, text preprocessing techniques, and domain adaptation in speech processing systems. His publications span over two decades, reflecting a consistent focus on improving automated systems for handling audio and text data in dynamic environments. While no specific awards or grants are listed, his extensive publication record highlights sustained contributions to the fields of speech technology and computational linguistics. His work at LANL likely involves collaborative research in applied computational sciences, though specific lab affiliations or teams are not explicitly mentioned.

Olga Vitekمشاهده پروفایل

استاد

• Statistical Science
• Machine Learning
• Mass Spectrometry
• +۵ مورد دیگر

Olga Vitek is a Professor at Northeastern University's Khoury College of Computer Sciences, with affiliated faculty status in the Department of Chemistry and Chemical Biology. Her research bridges statistical science and machine learning with mass spectrometry-based proteomics and systems biology, focusing on developing open-source software tools like MSstats and Cardinal for quantitative proteomic analyses and imaging. Education: PhD in Statistics (Purdue University), Postdoc at the Ruedi Aebersold Lab (Institute for Systems Biology) Leadership: Director of the Barnett Institute for Chemical and Biological Analysis Her work emphasizes: Statistical experimental design Signal detection in complex mass spectrometry data Causal inference in biomolecular networks Reproducible computational infrastructure Recent publications highlight advancements in quantitative proteomics , mass spectrometry imaging , and causal modeling , with applications spanning cancer research, immunology, and clinical diagnostics. Notable trends include deep learning integration for image analysis and open-source tool development for scalable, transparent workflows. Scientific accolades: Elected Fellow of the American Statistical Association 2021 Gilbert S. Omenn Computational Proteomics Award NSF CAREER award Chan-Zuckerberg Essential Open-source Software award Senior Member, International Society for Computational Biology

Chet C. Sherwoodمشاهده پروفایل

استاد

• Evolutionary Neuroscience
• Comparative Neuroanatomy
• Primate Brain Evolution
• +۳ مورد دیگر

Chet C. Sherwood is a Professor of Anthropology at George Washington University (GW) and a core faculty member of the Center for the Advanced Study of Human Paleobiology (CASHP). He also directs the National Chimpanzee Brain Resource and is affiliated with the GW Mind-Brain Institute. His research focuses on evolutionary neuroscience, particularly brain evolution in primates and other mammals, emphasizing how brain structure relates to behavior, development, and genetics. Education: Ph.D. (2003), M.A. (1998, 1996), and B.A. (1995) from Columbia University, with an additional M.A. from New York University (1996). Teaches courses such as ANTH 1001: Biological Anthropology and ANTH 3413: Evolution of the Human Brain. Research interests include comparative neuroanatomy of the cerebral cortex, human brain evolution relative to other primates, and the molecular and cellular mechanisms underlying cognitive evolution. He explores how brain differences across species correlate with ecological and behavioral traits, leveraging neuroimaging, transcriptomics, and fossil reconstruction techniques. Recent work investigates aging-related brain changes in primates and elephants. Notable achievements include membership in the National Academy of Sciences (2021) and the AAAS Fellowship (2022). His lab’s studies on chimpanzee brain plasticity and the genetic basis of primate cognition have advanced understanding of human uniqueness and shared evolutionary traits. Chet’s interdisciplinary collaborations span paleontology, genomics, and neuroscience, with a focus on bridging evolutionary and medical insights. His leadership in the National Chimpanzee Brain Resource underscores his commitment to advancing comparative neurobiology through resource development and ethical research practices.

• Data Visualization
• Visual Analytics
• Computer Science
• +۴ مورد دیگر

Jonathan Roberts is a researcher at Bangor University, UK, with a focus on data visualization, visual analytics, and educational technology. His work bridges computer science and creative design, particularly in data art exhibitions and authentic learning. Key research areas: Data Visualization, Visual Analytics, Educational Technology, Digital Art Recent publications explore generative AI in visualization design, multiple-view patterns for time series data, and frameworks for creative learning. His collaborations span institutions like QUT, University of Manchester, and University of Cambridge. Notable awards include VAST 2012 Honorable Mention and VAST 2010 Analytic Process Recognition. He contributes to visualization pedagogy and has co-authored works on haptic interfaces, immersive analytics, and coastal data modeling.

Pia Frickerمشاهده پروفایل

دانشیار

• Computational Methodologies
• Urban Design
• Landscape Architecture
• +۸ مورد دیگر

Prof. Pia Fricker is an Associate Professor and Vice Head of the Department of Architecture at Aalto University's School of Arts, Design and Architecture in Finland. She holds the Professorship of Computational Methodologies in Landscape Architecture and Urbanism, directing the Urban Studies and Planning Programme. Her research integrates urban design, landscape architecture, and digital design culture, focusing on data-driven methods, immersive environments, and adaptive urban development. Collaborations include ETH Zurich, Singapore University of Technology and Design, and Hafencity University Hamburg. Key projects include the Metaversity and Future Smart Cities initiatives. Fricker has led over 80 publications and exhibitions globally, including at the Venice Biennale and National Design Centre Singapore. She is an editorial board member for the Journal of Digital Landscape Architecture and peer reviewer for multiple journals. Awards include the Digital Landscape Architecture Award (2018) and DLA Scientific Merit Award (2021). Her teaching emphasizes computational pedagogy and digital innovation in design education. Education: PhD in Architecture (ETH Zurich, 2021) Postgraduate in Didactics (ETH Zurich, 2011) MAS in Computer Aided Architectural Design (ETH Zurich, 2003) MSc Arch in Urban Design & Landscape Architecture (Technical University of Karlsruhe, 2001) Research Interests: Computational design, parametric modeling, mixed reality, climate-adaptive ecosystems, generative AI, and sustainable urban development. Her work bridges emerging technologies with ecological and urban challenges, emphasizing interdisciplinary collaboration. Grants & Projects: Metaversity (2023–2025, Principal Investigator) Future Smart Cities Sasakawa (2023–2024, Principal Investigator) ABRA (2020–2023, Project Member) Awards: DLA Awards (2018, 2021) DLA Review Committee Awards (2020–2022) Exhibition Recognitions (Venice Biennale, National Design Centre Singapore) Labs/Teams: Leads the Urban Studies and Planning Programme and collaborates with interdisciplinary teams on projects like the RAILCORRIDOR Singapore initiative. Active in digital twin development and AI-driven design tools.

Constantin A. Rothkopfمشاهده پروفایل

استاد

• Perception and Action
• Computational Neuroscience
• Machine Learning
• +۳ مورد دیگر

Prof. Constantin A. Rothkopf is a W3 Professor at the Department of Psychology, Technische Universität Darmstadt, and a secondary member of the Department of Computer Science. He serves as Founding Director of the Centre for Cognitive Science and founding member of the Hessisches Zentrum für Künstliche Intelligenz (hessian.ai). He is also part of the European Laboratory for Learning and Intelligent Systems (ELLIS) and the DAAD Konrad Zuse Schools of Excellence in Artificial Intelligence (ELIZA). His research focuses on the interplay between perception and action, using computational models and experimental studies in humans. Current work includes eye-tracking studies in naturalistic environments, inverse optimal control models, and developing algorithms for virtual agents. Education: Ph.D. in Neuroscience and Informatics from the University of Rochester, followed by postdoctoral research at Frankfurt Institute for Advanced Studies (FIAS). He has held visiting professorships at Central European University (2017) and Columbia University (2023). Awards include an ERC Consolidator Grant (2022) and SCENE Project Funding (2025). Research Interests: Active vision, decision-making under uncertainty, sensorimotor control, and computational modeling. Key themes include how humans use sensory input to form beliefs, make decisions, and act in dynamic environments. Grants/Awards: ERC Consolidator Grant (2022), SCENE Funding (2025) Labs/Teams: Centre for Cognitive Science, hessian.ai, ELLIS Unit Darmstadt

Paul Hendersonمشاهده پروفایل

مدرس

• Generative AI
• Probabilistic Machine Learning
• 3D Computer Vision
• +۳ مورد دیگر

Dr. Paul Henderson is a Lecturer in Machine Learning at the School of Computing Science, University of Glasgow. He holds a BA in Mathematics (University of Cambridge, 2009), an MSc in Informatics (University of Edinburgh, 2010), and a PhD in Computer Vision (University of Edinburgh, 2018). His research focuses on generative AI, probabilistic machine learning, and minimally-supervised approaches to 3D computer vision, with applications in healthcare, computer graphics, and physical sciences. Education: PhD in Computer Vision (University of Edinburgh, 2018) MSc in Informatics (University of Edinburgh, 2010) BA in Mathematics (University of Cambridge, 2009) His work spans generative models, medical imaging, and robotics. Notable contributions include datasets like Flat’n’Fold and techniques in diffusion models for text-to-image retrieval. He has received grants including the Royal Society Research Grant (2022-2023) and the Vesuvius Challenge Autosegmentation Prize (2025). He supervises PhD students in topics such as medical image segmentation and generative AI. Teaching: CS5002 Advanced Programming, CS4061/CS5014 Machine Learning.

Jiannan Wangمشاهده پروفایل

دانشیار

• Database Systems
• Data Management
• Data Cleaning
• +۵ مورد دیگر

Jiannan Wang is an Associate Professor in the School of Computing Science at Simon Fraser University (SFU). He holds a Ph.D. from Tsinghua University (2013) and a B.Sc. from Harbin Institute of Technology (2008). His research focuses on database systems, data management, and data science, with particular emphasis on data cleaning, crowdsourcing, and big data technologies. He leads the SFU Data Science Research Group, aiming to accelerate data science workflows through innovative tools like DataPrep and ConnectorX. Education: Ph.D. in Computer Science and Technology, Tsinghua University, China (2013) B.Sc. in Computer Science and Technology, Harbin Institute of Technology, China (2008) Research Interests: Dr. Wang's work spans database systems, data cleaning, crowdsourcing, and big data education. He develops open-source tools for data scientists to streamline data preparation and analysis. His lab's mission is to make data science more efficient through technologies like DataPrep and ConnectorX . Awards: IEEE TCDE Rising Star Award (2018) CS-Can|Info-Can Outstanding Early Career Researcher Award (2020) VLDB Best Experiments, Analysis & Benchmark Paper Award (2021) PVLDB Distinguished Review Board Member Award (2020) Advising & Leadership: Director of SFU's Professional Master's Program in Big Data and Visual Computing. Supervised over 20 graduate and undergraduate students, many of whom have gone on to roles at top companies like Google, Amazon, and Huawei. Lab & Teams: Part of the SFU Data Science Research Group and the SFU Big Data Academic Advisory Committee. His lab collaborates with industry partners and contributes to open-source projects in data management and machine learning.

Lawrence Kimمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Tangible User Interfaces
• Human-Robot Interaction
• +۲ مورد دیگر

Lawrence Kim is an Assistant Professor at the School of Computing Science, Simon Fraser University. His research focuses on Human-Computer Interaction, Tangible User Interfaces, and Human-Robot Interaction, with teaching interests in Physical Computing and Human-Centered Computing. Education: PhD in Mechanical Engineering (Stanford University, 2020), MS in Mechanical Engineering (Stanford, 2015), and BS in Mechanical Engineering (University of Illinois at Urbana-Champaign, 2013). Research interests emphasize tangible interaction design, swarm robotics, and assistive technologies for special needs populations. His work includes developing interfaces like Woogu for child education and DiminishAR for cognitive enhancement. He directs the Tangent Lab (https://tangent.cs.sfu.ca/), exploring embodied and robotic interaction. Teaching includes courses such as CMPT 263 (Introduction to Human-Centered Computing) and CMPT 415/416 (Special Research Projects). His recent articles address topics like head posture correction in VR, programmable fidgeting with swarm robots, and stress prediction via mouse movements.

Elmira Djafarovaمشاهده پروفایل

استاد

• Digital Influencers
• Consumer Behavior
• Social Media Engagement
• +۵ مورد دیگر

Elmira Djafarova serves as the Head of the Marketing Subject Group in the Department of Marketing, Operations, and Systems at Northumbria University's Faculty of Business and Law. She holds a PhD in Tourism and is a Senior Fellow of the Higher Education Academy. Her academic leadership includes roles as Programme Director for Top-Up and Postgraduate Business programmes, focusing on enhancing international student experiences through initiatives like the International Mentoring Scheme. Her research spans digital influencers, social media engagement, consumer behavior, and tourism marketing. Notable contributions include studies on influencer credibility, crisis resilience via digital technology, and Generation Z's ethical consumption patterns. She has authored over 30 journal articles in outlets like *Computers in Human Behavior* and *Tourism Analysis*, and actively reviews for *Tourism Management* and *Journal of Advertising Research*. Research Interests: Electronic Word of Mouth, Social Media Analytics, Crisis Communication, Digital Marketing Professional Roles: Associate Editor for *Journal of Marketing Management*, Programme Chair at the Academy of Marketing Conference (2016) Recent work explores the impact of data usage patterns in Africa and the effectiveness of mindfulness interventions against fake news. She supervises PhD candidates researching cancel culture, showrooming behavior, and university search experiences. Djafarova has presented keynotes at the Operational Research Society and participates in international conferences on marketing innovation and digital transformation.