جست‌وجوی استاد و پژوهشگر

Benjamin C.M. Kaoمشاهده پروفایل

استاد

• Database Management Systems
• Data Mining
• Real-time Systems
• +۱ مورد دیگر

Professor Benjamin C.M. Kao is a faculty member in the Department of Computer Science at The University of Hong Kong (HKU), affiliated with the School of Computing and Data Science. He holds a BSc from HKU (1989) and a PhD from Princeton University (1995). His career includes roles as a teaching/research assistant at Princeton (1989-1991) and a research fellow at Stanford University (1992-1995). His research focuses on Database Management Systems, Data Mining, Real-time Systems, and Information Retrieval Systems. Notable contributions include S-OLAP for sequence data analysis, collaborative resource discovery in social tagging systems, and algorithms for mining periodic patterns in sequences. He has led research grants such as the GRF-funded 'Online Analytical Processing on Sequence Data' (2008) and computational studies in uncertain data mining (2006). Professor Kao has served on program committees for major computer science conferences and reviewed for leading journals. His work bridges theoretical foundations with practical applications in data systems and information retrieval.

Ebrahim Bedeer Mohamedمشاهده پروفایل

استادیار

• Signal Processing
• Wireless Communications
• Artificial Intelligence
• +۳ مورد دیگر

Ebrahim Bedeer Mohamed is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Saskatchewan. He joined in July 2019, following roles as an Assistant Professor (Lecturer) at Ulster University, UK, and postdoctoral fellowships at Carleton University and the University of British Columbia. He holds a Ph.D. (Distinction) from Memorial University of Newfoundland (2014), with expertise in signal processing and wireless communications. His research focuses on optimizing communication systems through advanced signal processing techniques, including faster-than-Nyquist signaling, IoT network design, AI integration, and energy-efficient protocols. Key areas include next-generation communication networks, non-orthogonal modulation, and MIMO systems. Notable contributions include work on channel estimation for FTN signaling, RIS-aided wireless systems, and LR-FHSS protocols in IoT. His publications span spectral efficiency, interference minimization, and energy management in 5G/6G contexts. He actively seeks Ph.D. students with strong backgrounds in signal processing fundamentals. Awards and grants are not explicitly listed in the provided texts. His work emphasizes practical applications, such as UAV trajectory optimization for IoT data collection and energy-efficient caching strategies in dynamic networks.

Ben Halpernمشاهده پروفایل

استاد

• Marine Ecology
• Conservation Planning
• Climate Change Impacts
• +۳ مورد دیگر

Ben Halpern is a Professor at the Bren School of Environmental Science & Management and Director of the National Center for Ecological Analysis and Synthesis (NCEAS) at UC Santa Barbara. He holds a PhD in Ecology from UCSB and a BA in Biology from Carleton College. His research focuses on marine ecology and conservation planning, with expertise in cumulative impact assessments, marine reserves, and the Ocean Health Index. He has led global projects on ocean health, biodiversity threats, and sustainable aquaculture, collaborating with institutions worldwide. Notable roles include co-founding the Conservation Aquaculture Research Team (CART) and serving as a part-time Chair in Marine Conservation at Imperial College London (2013–2018). Research interests span marine biodiversity conservation, climate change impacts on ecosystems, and the integration of ecological and social data into policy. His work emphasizes interdisciplinary approaches to address environmental challenges, such as mapping wastewater impacts, evaluating aquaculture sustainability, and developing tools for marine spatial planning. Awards include the Smith Fellowship Program (sponsored by The Nature Conservancy) during his postdoctoral work. He teaches Bren School courses, mentors graduate students, and leads collaborative research teams. Current projects include analyzing climate change effects on aquaculture and advancing the Ocean Health Index framework to support global conservation efforts.

• Marine Food Science
• Marine Chemistry
• Blue Biorefining
• +۷ مورد دیگر

Professor Ingrid Undeland leads the Marine research group at the Division of Food and Nutrition Science, Department of Life Sciences at Chalmers University of Technology. She is a distinguished researcher with expertise spanning marine food science, lipid chemistry, and blue biorefining, having established herself as a leading figure in sustainable seafood research and marine biotechnology. Her educational background includes food science studies from Linnaeus University and a PhD in bioscience from Chalmers University of Technology and SIK (now RISE). Between 1999-2002, she was a post-doctoral fellow at University of Massachusetts Marine Station, which significantly shaped her research trajectory in marine food science. Professor Undeland's research focuses on pioneering next-generation seafood through innovative value chains from seaweed, small pelagic fish, fish side streams, mussels, and microalgae. Her specialized expertise lies in marine lipids and proteins, particularly their stabilization, isolation from complex sources, and nutritional properties including digestibility. She has extensive experience with antioxidant strategies using plant-derived side streams or extracts and fundamental studies of fish hemoglobins as pro-oxidants. Her work also encompasses innovative technologies for biomass fractionation and nutrient recycling to build blue biorefineries, along with in vitro digestion models and general seafood analytics. Beyond marine research, she explores filamentous fungi as sustainable alternative food protein sources. The trends in her recent publications reveal a strong emphasis on valorizing marine resources through advanced processing techniques. Her work increasingly focuses on sustainable extraction methods for seaweed proteins, particularly Ulva fenestrata, and developing antioxidant strategies using berry side streams to stabilize fish proteins. There's a growing interest in understanding the nutritional properties and digestibility of alternative marine proteins, along with environmental assessments of processing technologies. Her research consistently bridges fundamental science with practical applications for creating sustainable seafood value chains. Swedish representative in Nordic Lipidforum, WEFTA, and EuCheMS Editorial board member of Journal of the Aquatic Food Product Technology Member of the National Committee for Nutrition and Food Science at the Royal Swedish Academy of Sciences Co-founder of the startup company AquaFood H-index of 47 according to Google Scholar Professor Undeland has an extensive record of academic mentorship, having supervised or currently supervising 23 PhD students, 14 postdoctoral researchers, and examining over 25 MSc students. Her research is supported by numerous grants, including the WaSeaBi Project which focuses on valorizing seafood side-streams through holistic value chain design. She collaborates with various industry partners and academic institutions across Europe. Her laboratory includes technicians Dr. Karin Larsson and Dr. Rikard Fristedt, and she leads a dynamic research team working on multiple projects related to marine biorefining and sustainable seafood development. Her research group operates within well-equipped facilities at Chalmers University, with specialized laboratories for marine food analysis, protein extraction, lipid oxidation studies, and in vitro digestion modeling. The team also maintains cultivation systems for seaweed and filamentous fungi, enabling integrated research from raw material production to final product development.

Mark Crowleyمشاهده پروفایل

دانشیار

• Reinforcement Learning
• Deep Learning
• Ensemble Methods
• +۶ مورد دیگر

Mark Crowley is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo , with a cross-appointment in the Cheriton School of Computer Science . He is actively involved in the Waterloo Artificial Intelligence Institute (WAII) , the Waterloo Institute for Complexity and Innovation (WICI) , and serves as National Secretary for the Canadian Artificial Intelligence Association (CAIAC) , coordinating the Canadian Conference on AI . Research interests span the theoretical and applied aspects of Reinforcement Learning , Deep Learning , Manifold Learning , and Ensemble Methods . His work addresses challenges in domains with spatial dynamics, multi-agent systems, and uncertainty, particularly in Computational Sustainability (forest fire management, sustainable forestry), Autonomous Driving , Medical Imaging , and Material Design . Recent research focuses on integrating causal modeling with generative representation learning to improve out-of-distribution robustness in motion forecasting applications. Key publications include foundational work on ChemGymRL environments for safe chemical process reinforcement learning, Generative Causal Representation Learning for robust forecasting, and collaborative work on multi-advisor reinforcement learning in multi-agent settings. He co-authored a textbook Elements of Dimensionality Reduction and Manifold Learning (Springer, 2023) with Prof. Ali Ghodsi and Prof. Fakhri Karray. Teaching includes graduate and undergraduate courses in Algorithm Design , Computational Intelligence , Reinforcement Learning , and Data Modeling at the University of Waterloo since 2018. His research group has produced several notable graduates including Benyamin Ghojogh (2021), who continued as a postdoc until 2022.

• Energy Efficiency in Software
• Multicore Memory Systems
• Hardware/Software Co-Design
• +۳ مورد دیگر

Arrvindh Shriraman is an Associate Professor and Program Director of Software Systems at Simon Fraser University's School of Computing Science in Surrey. His research focuses on energy-efficient software, multicore memory systems, and optimizing hardware/software interfaces for parallel programming. He holds a Ph.D. (2010) and M.S. (2006) in Computer Science from the University of Rochester, and a B.Eng. (2004) from the University of Madras. He teaches courses on parallel programming and energy-conscious software design. His research interests include synchronization mechanisms for domain-specific architectures, cache optimization, and FPGA-based acceleration. He has contributed to frameworks like Mu-grind for HLS-generated RTL instrumentation and TAPAS for parallel accelerator generation. Notable projects include RANGE-BLOCKS for synchronization in domain-specific systems and TapeFlow for gradient computation in neural networks. His work emphasizes real-time verification of autonomous systems and safety-critical trajectory planning for underwater vehicles. Shriraman collaborates closely with the Tangent Lab, exploring cutting-edge solutions in hardware-software co-design and embedded systems. His teaching and research bridge theoretical computer science with applied engineering challenges, addressing scalability, efficiency, and safety in modern computing systems.

Dorte Hammershøiمشاهده پروفایل

استاد

• Acoustics
• Hearing Science
• Audio Engineering
• +۵ مورد دیگر

Dorte Hammershøi is a Professor in the Department of Electronic Systems at The Technical Faculty of IT and Design, Aalborg University, Denmark. Her research focuses on acoustics, sound engineering, and hearing science with significant contributions to human hearing, ear canal acoustics, and audio technology applications. Her research interests include: Temporary Threshold Shift and frequency resolution in human hearing Ear canal acoustics and sound pressure level measurement Distortion Product Otoacoustic Emission (DPOAE) analysis Impulse response and acoustic impedance studies Hearing aid technology and rehabilitation methodologies Virtual reality audio interfaces and accessibility applications Professor Hammershøi's recent publications demonstrate a strong clinical-engineering interdisciplinary approach, bridging theoretical acoustics with practical hearing rehabilitation applications. Her work on hearing aid fitting methodologies, occupational noise exposure effects, and virtual reality audio interfaces shows consistent innovation in translating engineering principles to clinical practice. The research shows particular attention to individualized hearing solutions and accessibility technologies. Her scientific contributions have been recognized with: Dansk Lydpris 2020 (awarded November 17, 2021) Ambassadør for Aalborg (awarded September 15, 2004) Professor Hammershøi has supervised 5 PhD students and led numerous research projects including the ongoing "Audio Only VR for Blind Gamers" project (2024-2028) funded by the Independent Research Foundation of Denmark, and the completed "BEAR: Better Hearing Rehabilitation" project (2016-2022). Her research has attracted significant media attention with 110 press/media appearances discussing hearing damage prevention, tinnitus, and public health implications of noise exposure. She maintains active professional engagement through committee memberships (46 documented activities), international collaborations, and contributions to clinical practice guidelines. Her work continues to influence both academic research and practical applications in hearing science and audio engineering.

Walid G. Arefمشاهده پروفایل

استاد

• Databases
• Data Mining
• Spatial Databases
• +۶ مورد دیگر

Walid G. Aref is a Professor of Computer Science at Purdue University since Fall 1999. His research focuses on database systems, spatial and spatio-temporal data management, query processing, and indexing. He has led projects funded by NSF, NIH, and industry partners. Aref is a Fellow of the IEEE and has received awards including the NSF CAREER Award (2001) and VLDB’s Ten-Year Best Paper Award (2016). He serves as Editor-in-Chief of ACM Transactions on Spatial Algorithms and Systems and has authored numerous influential papers. Education: BSc/MSc from Alexandria University (Egypt), PhD from University of Maryland (1993). Research Interests: Extending database functionality for emerging applications like spatial, graph, and sensor databases. Notable contributions include the Chameleon project, AQWA system for big spatial data, and privacy-preserving Casper framework. Selected Projects: NSF-funded work on multi-predicate spatial queries, in-memory graph relational systems, and adaptive spatio-textual processing. Systems like Tornado (spatio-textual streams) and LocationSpark (distributed spatial data) exemplify his contributions. Awards: Multiple best paper awards, IEEE Fellow, and leadership roles in ACM SIGSPATIAL.

• Innovative Materials
• Support to SMEs
• Sensory Design
• +۴ مورد دیگر

Beatrice Lerma is an Associate Professor at the Polytechnic University of Turin , affiliated with the Department of Architecture and Design and serving as Deputy Coordinator of the Doctoral School of Design and Technology: People, Environment, Systems . Research focuses on Innovative Materials , Sensory Design , and Design for Cultural Heritage Key skills in Environmental Engineering , Industrial Design , and Circular Economy Her recent work explores the intersection of Artificial Intelligence and Material Innovation , particularly in sustainable polymer systems and transparent wood technology. She leads the BIOMAPS (2025-2028) and AI-TRANSPWOOD (2024-2026) projects. 2025: AI applications in biobased materials 2024: Cultural heritage signage solutions 2024: Circular material taxonomic frameworks Scientific recognitions include ADI Design Index Selection Award (2015) and Young & Design (2013). She supervises PhD candidates Noemi Emidi and Eva Vanessa Bruno , and serves on the OFFICINA Scientific Committee since 2014.

Sainyam Galhotraمشاهده پروفایل

استادیار

• Databases
• Data Management
• Responsible Data Science
• +۷ مورد دیگر

Sainyam Galhotra is an Assistant Professor in the Department of Computer Science at Cornell University. His research focuses on developing data science tools for effective and responsible analytics, leveraging techniques from causal inference, data management, theoretical computer science, machine learning, and human-computer interaction to address challenges in trustworthy system design including robustness, explainability, and fairness. Education: Postdoc: University of Chicago PhD: University of Massachusetts Amherst (supervised by Barna Saha) BTech: Indian Institute of Technology Delhi (IIT Delhi) (supervised by Prof. Amitabha Bagchi) Research Interests: Dr. Galhotra's research spans several interconnected areas in data science and artificial intelligence. His work primarily focuses on Responsible Data Science , where he develops methods to ensure that data-driven systems operate fairly and transparently. Within this broad area, his specific interests include: Causal Inference techniques for understanding cause-effect relationships in complex data Algorithmic Fairness approaches to mitigate bias in machine learning systems Explainable AI methods that make black-box models more interpretable Data Management systems for efficient and reliable data processing Entity Resolution techniques for integrating data from multiple sources Trustworthy System Design that addresses robustness, explainability, and fairness His recent publications demonstrate a clear trend toward developing frameworks that combine causal reasoning with practical data management systems, particularly focusing on how to make data-driven decisions more transparent and equitable. The intersection of database systems with fairness considerations appears to be a particularly active area of his research. Scientific Awards: Rising Star in Data Science at the Data Science Institute, UChicago (Oct 2021) Computing Innovation Fellowship Award Recipient (by CRA, CCC and NSF) (Apr 2021) DAAD AInet Fellow (Feb 2021) ACM SIGMOD Entity Resolution Programming Contest – Top 5 finalist (May 2020) Most reproducible paper award in SIGMOD 2018 and 2019 (Jun 2019) First recipient of Krithi Ramamritham Computer Science Scholarship (Jun 2019) Best paper award in SIGSOFT FSE 2017 (May 2017) Dr. Galhotra is actively seeking students to collaborate with on his research projects. His work has been supported by various fellowships and awards, including the prestigious Computing Innovation Fellowship. He has mentored several students through his research projects, with a focus on developing the next generation of data scientists who can build responsible and trustworthy systems. His research group appears to focus on the intersection of database systems and responsible AI, developing tools like HypeR for causal reasoning, Ver for view discovery, and Nexus for correlation discovery in spatio-temporal data. This work suggests a cohesive research agenda centered around making data systems more transparent, fair, and user-friendly.

Peter Horakمشاهده پروفایل

دانشیار

• Nonlinear Optics
• Quantum Optics
• Photonics
• +۴ مورد دیگر

Dr Peter Horak is an Associate Professor at the Optoelectronics Research Centre (ORC) of the University of Southampton. With expertise in theoretical and computational photonics, his research spans nonlinear optics, quantum technology, and fiber optics. He obtained his MSc in Theoretical Physics (1993) and PhD in Theoretical Quantum Optics (1997) from the University of Innsbruck, followed by postdoctoral positions in Paris and Glasgow before joining the ORC in 2001. Current roles: ORC Exam Officer Admissions Tutor, EPSRC CDT in Quantum Technology Engineering Dr Horak leads the Computational Nonlinear Optics group, focusing on theoretical and numerical modeling of photonics systems across scales—from single photons to gigawatt laser pulses. His work addresses fundamental physics and device optimization in hollow-core fibers, quantum devices, and high-harmonic generation. Recent publications highlight hollow-core fiber gas dynamics, nonlinear optical sensing, and microresonator alignment challenges. Collaborations include the UK National Quantum Technology Programme and EPSRC-funded projects like QCI3 and HiPPo. External roles: Editorial Board, Physical Review A (2017–2022) Peer reviewer for EPSRC (since 2012) and ESF (since 2017) He supervises PhD students in nonlinear and quantum optics, and teaches optical fiber and computational modeling topics.

Tri Setiyonoمشاهده پروفایل

استادیار

• Precision Agriculture
• Remote Sensing
• Artificial Intelligence
• +۳ مورد دیگر

Tri Setiyono is an Assistant Professor in the School of Plant, Environmental, and Soil Sciences at Louisiana State University (LSU). Previously, he served as a Scientist at the Sustainable Impact Platform of the International Rice Research Institute (IRRI), Los Baños, Philippines (2011–2021), and as a Postdoctoral Research Associate in the Department of Agronomy and Horticulture at the University of Nebraska-Lincoln (2007–2011). He is affiliated with the LSU AgCenter and the LSU College of Agriculture, contributing to research and extension services in precision agriculture and crop resilience. Education: PhD in Agronomy, University of Nebraska-Lincoln (2007) MS in Agronomy, Kansas State University (2003) BS in Agronomy, Bogor Agricultural University (1998) Research interests focus on precision agriculture, remote sensing, and AI applications to enhance crop production resilience against climate change. He specializes in GIS for agronomic research, crop growth models (e.g., ORYZA, SoySim), and integrating SAR and MODIS satellite data for yield estimation. His work emphasizes sustainable practices and technology-driven solutions for row crops in dynamic environments. Publications highlight advancements in rice monitoring systems, soybean and maize modeling, and decision tools for nutrient management. These contributions bridge technological innovation with practical agricultural challenges in Asia and the US. Scientific awards: None explicitly mentioned in the text. Advising and grants: No formal advisees/students are listed. Professional experience includes roles at IRRI and UNL, suggesting involvement in grant-funded research projects, but specific grant details are not provided. Labs/Teams: Associated with Louisiana State University AgCenter research stations and collaborative projects like the RIICE initiative, but no specific lab names or teams are detailed in the text.

Sebastian Hennمشاهده پروفایل

استاد

• Economic Geography
• Regional Development
• Transnational Entrepreneurship
• +۷ مورد دیگر

Sebastian Henn is a Professor of Economic Geography at the Institute of Geography, Friedrich Schiller University Jena, where he has held the Chair since 2014. He serves as Dean of Studies for the Faculty of Chemistry and Geosciences (since 2020) and Deputy Director of the Leibniz ScienceCampus "Eastern Europe - Global Area". His research spans transnational entrepreneurship, knowledge-based regional development, cluster dynamics, polarization/peripheralization, and migration studies . Education: Dipl.-Geogr. (University of Mannheim, 2001); Dr. rer. nat. (University of Halle, 2006); Habilitation (University of Halle, 2014) Key research areas include spatial perception, mobilities, health geography, and global-local interactions in sectors like pharmaceuticals, medical technology, and the diamond industry. Publications (2013-2024) focus on global production patterns, cluster evolution, regional embitterment, and the role of transnational entrepreneurs in industries from Gujarat to Antwerp. His 2023 work explores populist resentments in rural regions and health infrastructure disparities in Thuringia. Awards include the 2017 Journal of Economic Geography Best Referee Award. He co-edits the Springer series "Perspectives in Human Geography" and holds leadership roles in academic societies like the Schumpeter Centre for Social and Economic Change. Editorial and Review Activities : Active on boards of the Journal of Economic Geography and ZFW journal. Regular reviewer for 20+ journals and funding bodies including DFG and DAAD. Leads research on BRIC investments, Southern multinationals, and spatialization processes under globalization .

Hui Luanمشاهده پروفایل

استادیار

• Spatial Epidemiology
• Bayesian Spatiotemporal Statistics
• Geographical Information Science (GIS)
• +۴ مورد دیگر

Hui Luan is an Assistant Professor in the Department of Public Health at the Peter O’Donnell Jr. School of Public Health, UT Southwestern Medical Center. He joined UT Southwestern in 2024 after serving as an Associate Professor (tenured) at the University of Oregon (2018–2024). His research focuses on spatial epidemiology, Bayesian spatiotemporal statistics, and GIS applications to address health disparities and environmental determinants of disease. Education: Ph.D. in Planning, University of Waterloo, 2017 M.S. in Cartography and GIS, Wuhan University, 2011 B.S. in GIS, Wuhan University, 2009 Research Interests: Dr. Luan investigates spatial and temporal variations in health outcomes, particularly HIV incidence, and the role of social, physical, and built environments. He develops Bayesian models and spatial analytics to inform geographically tailored interventions. Current projects include optimizing PrEP accessibility, analyzing food environment equity, and leveraging spatial data science for public health policy. Key Achievements: Lead investigator of an NIH-funded R01 project on reducing HIV incidence via spatial data science Editorial board member of Spatial and Spatiotemporal Epidemiology Recipient of the Vu Fellowship (2021–22) Teaching: Teaches courses on GIS in Public Health, Spatial Analysis, and Big Data applications in geography. Recent courses include GIS and Public Health and Spatial and Spatiotemporal Analysis at the University of Oregon. Labs/Teams: Leads the Spatial Data Science Lab focused on advancing Bayesian methods for health data analysis and promoting GIS applications in public health practice.

Don Lafreniereمشاهده پروفایل

استاد

• Historical GIS
• Deep Mapping
• Public Participatory GIS
• +۹ مورد دیگر

Don Lafreniere is Professor of Geography and GIS at Michigan Technological University, where he also serves as Graduate Director and Director of the Geospatial Research Facility. He is affiliated with the Department of Social Sciences in the College of Sciences and Arts. His interdisciplinary research integrates GIS, historical data, and community engagement to study urban environments, population health, and postindustrial landscapes. PhD, Geography, University of Western Ontario BS, History, Eastern Michigan University BS, Geography, Eastern Michigan University His research interests include Historical GIS, Deep Mapping, Public Participatory GIS, children's health and lifecourse epidemiology, deindustrialization, and urban health. He leads the Keweenaw Time Traveler and Historical Environments Spatial Analytics Lab (HESAL), focusing on creating spatiotemporal models of historical urban change. His recent publications (2016–2023) reflect a strong trend in integrating GIS with historical, archaeological, and public health data, particularly in industrial and postindustrial cities. Themes include environmental justice, cumulative hazards, community heritage, and spatial narratives, often using deep mapping and historical spatial data infrastructures. He has received major funding from the National Endowment for the Humanities (NEH), National Science Foundation (NSF), and Social Sciences and Humanities Research Council (SSHRC), serving as Principal Investigator or Co-PI on projects such as the Keweenaw Time Traveler, GRACE, and Three Centuries of Francophone Migration. These grants support transdisciplinary, community-engaged, and public-facing scholarship in the spatial humanities. Labs and initiatives include the Geospatial Research Facility, HESAL, and the Keweenaw Time Traveler, which combine geospatial technologies with historical research and public education.