جست‌وجوی استاد و پژوهشگر

Erzhuo Cheمشاهده پروفایل

استادیار

• Geomatics
• 3D Point Cloud Processing
• Lidar Data Analysis
• +۵ مورد دیگر

Erzhuo "Ezra" Che is an Assistant Professor in the Department of Civil and Construction Engineering at Oregon State University's College of Engineering. His research focuses on 3D point cloud processing, geospatial data analysis, and infrastructure asset management. He teaches courses in 3D laser scanning, digital terrain modeling, and advanced point cloud programming. Education: Ph.D., Civil Engineering (Geomatics), Oregon State University, 2018 M.S., Photogrammetry and Remote Sensing, Wuhan University, 2015 B.Eng., Photogrammetry and Remote Sensing, Wuhan University, 2012 His research interests include lidar technology applications, automated infrastructure assessment, deformation monitoring, and error modeling. Recent work emphasizes ADA compliance evaluation using 3D point clouds and mobile lidar for road marking analysis. Dr. Che has received notable awards such as the 2022 Geo Week Achievement Award and the 2021 Martin Isenburg Best Paper Award. His projects include mapping historical structures at Silver Falls State Park and developing frameworks for efficient point cloud segmentation. His teaching and research bridge geomatics with civil engineering challenges, focusing on practical solutions for infrastructure maintenance and disaster resilience.

Xiang Sunمشاهده پروفایل

استادیار

• Mobile Edge Computing
• Internet of Things (IoT)
• Drone-assisted Mobile Access Networks
• +۵ مورد دیگر

Dr. Xiang Sun is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of New Mexico (UNM). He holds a Ph.D. in Electrical Engineering from New Jersey Institute of Technology (2018), and M.E. and B.E. degrees from Hebei University of Engineering (2011 and 2008). His research focuses on Mobile Edge Computing, IoT, Drone-assisted Networks, Green Computing, and Data Center Optimization. Dr. Sun has been recognized with awards such as the 2018 InterDigital Innovation Award and NJIT Hashimoto Prize. Education: Ph.D., Electrical Engineering, NJIT (2018) M.E., Computer Applications Technology, Hebei University (2011) B.E., Electronic Information, Hebei University (2008) Research Interests: His work emphasizes IoT resource caching, semantic discovery, green communications, and drone-based mobile access networks. He also explores machine learning applications in edge computing and cybersecurity. Publications & Contributions: Dr. Sun has authored over 40 journal/conference papers, including impactful work on cloudlet networks and IoT semantic mashup. His research has been published in IEEE Transactions, Communications Letters, and top-tier conferences like ICC and GLOBECOM. Awards: 2018 InterDigital Innovation Award 2018 NJIT Hashimoto Prize 2017 IEEE Communications Letters Exemplary Reviewer 2016 IEEE ICC Best Paper Award Professional Activities: He serves as a TPC member for IEEE CCNC and MobiEdge, and reviewer for top journals like IEEE Transactions on Cloud Computing and IEEE Internet of Things Journal. He co-chairs the Social Computing and Semantic Data Mining symposium at IEEE ICNC 2019. Labs & Teams: Active in UNM's Electrical & Computer Engineering labs, focusing on mobile edge computing and IoT innovation. Collaborates with industry partners like InterDigital Communications.

Malcolm Macdonaldمشاهده پروفایل

استاد

• Space Technology
• Astrodynamics
• Networked Systems
• +۳ مورد دیگر

Eur Ing Malcolm Macdonald is a Professor of Electronic and Electrical Engineering at the University of Strathclyde. He serves as Director of the Applied Space Technology Laboratory (ApSTL) and the Centre for Signal and Image Processing (CeSIP). Additionally, he holds Visiting Professor roles at University College Dublin's Centre for Space Research and is Vice-Chair of the UK Space Agency's Space Technology Advisory Committee. His expertise spans space mission design, networked systems, and sustainable space technologies, with a focus on democratizing space data accessibility. He contributed to Scotland's first CubeSat and led initiatives like the Scottish Centre of Excellence in Satellite Applications (SoXSA). Research interests include astrodynamics, swarm engineering, and Earth observation, leveraging systems engineering to address global challenges. Notable awards include the 2020 Copernicus Masters Transport Challenge and the 2024 CompleNet Best Poster Award. He advises on over 80 research projects, focusing on satellite constellations, offshore energy monitoring, and space debris mitigation. His work integrates multidisciplinary approaches, emphasizing resilience and innovation in space systems. Labs and teams include ApSTL and CeSIP, where he leads a team of researchers and postgraduate students. Equipment resources include specialized drones and control systems for experimental validation. Collaborations span academia, industry, and government, driving advancements in space technology and policy.

Diala Naboulsiمشاهده پروفایل

استاد

• Mobile networks
• Wireless networks
• Network virtualization
• +۷ مورد دیگر

Diala Naboulsi is a Professor at the École de technologie supérieure (ÉTS) in the Department of Software Engineering and IT. Her research focuses on mobile networks, wireless systems, and cybersecurity, with a strong emphasis on machine learning applications in network optimization. She holds an M.Eng. from the Lebanese University and M.Sc. and Ph.D. degrees from INSA Lyon. Research Units: Summit Tech Research Chair, LASI Lab, Imagin Lab Expertise: Network virtualization, resource allocation, mobility management, UAV-based computing Her work spans resilience in wireless backhaul networks, energy-efficient frameworks in RAN slicing, and federated learning for privacy-aware traffic forecasting. She has advised numerous doctoral students, including Ahmed Abdelmoaty, Hnin Pann Phyu, and Philippe Lavoie. Key contributions include deep reinforcement learning approaches for network topology optimization and UAV-assisted MEC systems for Industry 5.0. Recent publications highlight advancements in 6G networks, network slicing, and edge computing. Her research aligns with strategic initiatives in sustainable and secure communication systems.

• Conceptual Modeling
• Ontology
• Domain Modeling
• +۷ مورد دیگر

Tiago Prince Sales is an Assistant Professor in the field of Semantics, Cybersecurity & Services, actively contributing to foundational research in conceptual modeling, ontology, and information systems. His work bridges formal methods with practical applications in digital platforms, cybersecurity, and knowledge representation. Assistant Professor, Semantics, Cybersecurity & Services Active in international research communities (FOIS, ER, BPMDS, RCIS) Key focus: Ontology, Domain Modeling, Interoperability, Digital Platforms Recognized with multiple best paper awards His research centers on the development and application of formal conceptual models using frameworks such as OntoUML and the Unified Foundational Ontology (UFO). He investigates how domain models can enhance system design, improve interoperability, and support risk analysis in complex information systems. His work often integrates empirical insights with theoretical rigor, aiming to address real-world challenges in modeling. The recent publications highlight a strong trend toward ontological engineering in cybersecurity (e.g., phishing attack modeling), digital platform taxonomy, and FAIR data planning. These works demonstrate a consistent focus on creating reusable, semantically rich models that support both human understanding and machine processing across domains. The integration of modeling with data science and security indicates a forward-looking research agenda. Best paper award at FOIS 2023 Best paper award at ER 2022 EMMSAD 2025 Best paper award Tiago Prince Sales actively mentors and collaborates with researchers, though no formal students are listed. He has secured recognition through competitive awards and leads significant research outputs, including datasets and open models. His involvement in organizing top-tier conferences such as FOIS 2024 reflects leadership in the academic community. While specific grants are not listed, his productivity suggests external funding support. He contributes to open science through Zenodo-hosted datasets like the OntoUML Vocabulary and GO-Plan method, and participates in collaborative teams focused on knowledge graphs, FAIRification, and model-driven engineering. His role in organizing the FOIS 2024 conference underscores his integration within leading research networks in formal ontology and conceptual modeling.

• Artificial Intelligence in Medicine
• Rhinology
• Ear Surgery
• +۵ مورد دیگر

Rhea Darbari Kaul serves as an Ears, Nose and Throat Registrar at Macquarie University Clinical Associates (MUCA) while pursuing her Doctor of Philosophy through the Faculty of Medicine, Health and Human Sciences at Macquarie University. With an h-index of 19, she demonstrates significant research impact in her field. Dr. Darbari Kaul's research focuses at the intersection of artificial intelligence and otolaryngology, with particular emphasis on rhinology and ear surgery applications. Her work bridges clinical practice with technological innovation, developing practical AI solutions for medical imaging analysis, surgical procedures, and prosthetic development. She has established herself as a specialist in applying computational methods to paranasal sinus radiology and endoscopic ear surgery video analysis. Her publication record reveals a clear trajectory toward integrating artificial intelligence with traditional ENT practices. The pattern shows increasing sophistication in AI applications, moving from systematic reviews of existing literature to developing novel algorithms and practical clinical tools. Her research demonstrates strong collaboration with multidisciplinary teams including clinicians, computer scientists, and engineers. As an active researcher with multiple publications in 2023 and 2025, Dr. Darbari Kaul contributes significantly to advancing the application of artificial intelligence in otolaryngology. Her work on open-source algorithms and cost-effective digital solutions suggests a commitment to making advanced medical technologies more accessible across different healthcare settings.

Anantaa Kotalمشاهده پروفایل

استادیار

• Generative AI
• Privacy-Preserving Data Sharing
• Cybersecurity
• +۲ مورد دیگر

Anantaa Kotal is an Assistant Professor of Computer Science at The University of Texas at El Paso (UTEP), commencing her position in Fall 2024. Previously, she completed her PhD at the University of Maryland, Baltimore County (UMBC) and gained industry experience at Amazon and IBM. Her academic credentials include: PhD in Computer Science, University of Maryland Baltimore County (UMBC), 2024 B.E. in Computer Science and Engineering, Jadavpur University, 2017 Dr. Kotal's research centers on Generative AI applications for privacy and security, with emphasis on privacy-preserving data sharing, synthetic data generation, and policy compliance verification. She integrates knowledge graphs, reinforcement learning, and neurosymbolic approaches to develop frameworks for secure data synthesis in healthcare, agriculture, and cybersecurity domains. Her work addresses critical challenges like policy ambiguity resolution and trustworthy AI code generation. Analysis of her 15 most recent publications (2021-2025) reveals a strong trajectory toward knowledge-infused generative models for privacy preservation, with increasing focus on large language models (LLMs) and real-world applications in distributed systems. Key thematic clusters include policy-aware data synthesis (12 publications), healthcare data security (7 publications), and knowledge-graph-enhanced cybersecurity (5 publications). Dr. Kotal is actively recruiting graduate students for her research lab at UTEP and currently teaches Data Mining (CS 5362/6362) in Fall 2024. She maintains active research collaborations with her doctoral advisor Dr. Anupam Joshi at UMBC and industry partners including IBM. She leads a research laboratory at UTEP focused on developing next-generation privacy-preserving AI systems, with current projects spanning healthcare data anonymization, agricultural data sharing frameworks, and policy-compliant synthetic data generation for cybersecurity applications.

• Business Analytics
• Decision Support Systems
• Artificial Intelligence in Business
• +۵ مورد دیگر

Vanja Bevanda is a Full Professor at the Faculty of Economics and Tourism, University of Primorska in Pula. She holds a PhD from 2002 and has been employed at the institution since 2005, contributing to the Department of Quantitative Methods. Her educational background includes a BSc (1989), MSc (1995), and PhD (2002). Research Interests : Her work focuses on decision analytics, business intelligence, artificial intelligence applications in SMEs, data mining for customer behavior analysis, tourism development strategies, and the integration of technology in education. She explores topics like AI-driven managerial journeys, microchip implant adoption, and post-pandemic technology use trends. Publications : Recent articles highlight her contributions to AI transformation in SMEs, sentiment analysis during the pandemic, and mobile BI adoption in SMEs. Her research spans both theoretical frameworks and practical case studies across Croatia and beyond. Teaching : She teaches courses including Business Decision-Making, IT Project Management, and Database Systems. She emphasizes bridging theoretical knowledge with practical skills in information systems education.

• Computer Science
• Networking Systems
• Software Engineering
• +۵ مورد دیگر

Xin Wang is a Professor at Fudan University's School of Computer Science, specifically within the Department of Communication Science and Engineering and affiliated with the State Key Laboratory of ASIC and System in Shanghai, China. With 185 publications spanning two decades (2003-2025), Wang maintains an exceptionally active research profile, particularly evident in recent high-output years including 22 publications in 2019, 19 in 2021, and 13 in 2024. The research portfolio demonstrates deep collaboration networks, most notably with Yang Chen (45 co-authored papers), Yangfan Zhou, and Qingyuan Gong. Wang's research spans multiple critical areas in computer science, with significant contributions to networking systems (particularly CDN optimization, HTTP/3 implementation, and IPv6 infrastructure), software engineering (focusing on work rhythms, testing methodologies, and GUI analysis), mobile applications (including healthcare implementations and accessibility features), and security (especially account security and fraud detection in e-commerce). The interdisciplinary nature of the work is evident through applications in healthcare, e-commerce, campus safety, and IoT systems. Analysis of recent publications (2023-2025) reveals a strong trend toward practical system implementations addressing real-world challenges. The research demonstrates a consistent pattern of moving from theoretical foundations to deployable solutions, with particular emphasis on optimizing performance in networking systems, enhancing security in digital platforms, and improving user experience across diverse application domains. The work frequently incorporates machine learning techniques to solve complex system problems while maintaining practical applicability. While specific grant information isn't detailed in the publication records, the extensive collaboration network spanning multiple institutions in China and internationally suggests substantial research funding support. The consistent publication output across top venues including IEEE/ACM Transactions, INFOCOM, SIGCOMM, and ICSE indicates sustained research productivity and impact.

Francis L. Huangمشاهده پروفایل

استاد

• Quantitative Methods
• Multilevel Modeling
• School Climate
• +۴ مورد دیگر

Dr. Francis L. Huang is a Professor in the Department of Educational, School, and Counseling Psychology at the University of Missouri-Columbia 's College of Education and Human Development. An applied quantitative methodologist , he teaches courses in program evaluation, multilevel modeling, and data management while researching school climate, bullying prevention, and large-scale educational data analysis. PhD in Research, Statistics, and Evaluation (University of Virginia) MA in Instructional Technology and Media (Teachers College, Columbia University) BS in Legal Management (Ateneo de Manila University) His methodological expertise spans clustered data analysis , plausible values modeling , and robust standard error estimation . He develops tools like the MLMusingR package for multilevel modeling in education research. Recent work focuses on 2025 grant-funded studies about data weighting in international assessments and 2024 open-access replication frameworks for nonexperimental datasets. He advocates for rigorous causal inference and equitable discipline policy analysis through projects like the National Center for Rural School Mental Health (funded by Institute of Education Sciences). Dr. Huang contributes to Missouri Prevention Science Institute as Methodology Co-Director and collaborates with interdisciplinary teams on school violence prevention and behavioral threat assessment systems. His 2023-2025 publications demonstrate technical innovations in three-level cluster-robust errors and missing data handling for large-scale assessments.

• Database Systems
• Data Analytics
• Machine Learning in Databases
• +۳ مورد دیگر

Jignesh M. Patel is a Professor at the University of Wisconsin, Madison, WI, USA , with over 25 years of contributions to database systems, data analytics, and hardware-aware query processing. His work bridges theoretical advancements with practical systems engineering. Research Interests span: Database systems optimization (query processing, transaction management) Hardware acceleration for analytics (eBPF, PIM, GPUs) Machine learning integration in databases (feature selection, model optimization) Efficient data structures (hashing, encoding, indexing) Multi-tenant and cloud database management Recent Work focuses on kernel-embedded databases (BPF-DB, 2025), memory-efficient dataframe processing (SplitDF, 2024), and algorithmic-hardware co-design for dense retrieval (DReX, 2025). He has pioneered techniques for adapting to data skew (VIP Hashing, 2022), leveraging static analysis in R optimization (ROSA, 2017), and rethinking benchmarking paradigms. Collaborations include key partnerships with: Systems researchers (Andrew Pavlo, José F. Martínez) Machine learning experts (Arun Kumar, Kevin Skadron) Education-focused colleagues (Adalbert Gerald Soosai Raj, Richard Halverson) Industry leaders (David J. DeWitt, Microsoft Research)

Jana Gonnermann-Müllerمشاهده پروفایل

پژوهشگر

• Human-Machine Interaction
• Educational Technology
• Cognitive Load Theory
• +۴ مورد دیگر

Jana Gonnermann-Müller is a research assistant at the Chair of Business Information Systems, Processes and Systems at the University of Potsdam . Holding an M.Sc. in Psychology from Humboldt University of Berlin, her work focuses on human-machine interaction, particularly examining learning, decision-making, and trust in technological collaborations. Degree: Master of Science (M.Sc.) in Psychology Alumni: Humboldt University of Berlin Current Role: Scientific Associate at University of Potsdam Research explores cognitive factors in augmented reality and AI assistance systems , employing experimental designs and eye tracking methodologies. Key projects include investigating visual guidance in AR, comparing AR display types, and developing frameworks for generative AI in education. Publications (2023-2025) demonstrate expertise in digital education , cognitive load optimization , and technology-enhanced learning . Collaborations span institutions like Hong Kong Polytechnic University , University of California, Davis , and Weizenbaum Institute , with corporate consulting on learning technology implementation. Technical focus areas include: Human-System Design Optimization Eye Tracking & Usability Studies AI Recommender Systems Industry 4.0 Implementation Research applications extend to: Secondary Education Technology Assembly Line AR Integration Change Management Systems Maintenance AR Visualization

Sergey Arkhipovمشاهده پروفایل

دانشیار

• Geometric representation theory
• DG categories
• Homological algebra
• +۸ مورد دیگر

Sergey Arkhipov is an Associate Professor in the Department of Mathematics at Aarhus University. His primary research focuses on homotopy theory of DG-categories, homotopy descent, categorical braid group actions, matrix factorizations, derived algebraic geometry, chiral algebras, and semiinfinite cohomology. He has taught undergraduate and Master's courses such as Complex Analysis and Advanced Algebra, organized graduate seminars on DG Categories and Homotopical Algebra, and supervised PhD students. Research Interests Geometric representation theory DG categories Homological algebra Algebraic homotopy theory Algebraic operads Homotopy descent Categorical braid group actions Matrix factorizations Derived algebraic geometry Chiral algebras Semiinfinite cohomology Publications Trends Arkhipov's publications center on advanced topics in category theory, homotopy theory, and geometric representation theory, with a strong emphasis on DG-categories, matrix factorizations, and categorical structures in algebraic geometry. His work often bridges abstract categorical frameworks with concrete applications in algebra and topology.

• Information Systems
• E-business
• E-government
• +۷ مورد دیگر

Professor Angelika Kokkinaki is Dean of the School of Business and MBA Director at the University of Nicosia. With a PhD in Computer Science from the University of Louisiana at Lafayette (1995), a M.Sc. from Northeastern University (1991), and a Diploma from Patras University (1987), her academic credentials are rooted in Information Systems and Computer Science. PhD in Computer Science (1995), University of Louisiana at Lafayette M.Sc. in Computer Science (1991), Northeastern University Diploma in Computer Engineering and Informatics (1987), University of Patras Her research spans e-business, e-government, e-learning, and smart city technologies, focusing on semantic search engines, distributed systems, and circular economy applications. Recent work emphasizes Smart Cities through projects like OpenDCO, CRISIS, and DEVOPS. Key article trends include smart city resilience, AI applications in education, e-learning adoption, marine sensor networks, and open data workforce development. Her scholarly output aligns with 6 UN Sustainable Development Goals , particularly in education, sustainability, and urban innovation. Scientific Awards : Innovation award by the Republic of Cyprus (for quality management system) She leads over 30 EU/national projects and contributes to the Center of Equality, Diversity, and Inclusion (CEDI) and OECD policy monitoring. Her work integrates Petri Net modeling , software agent systems, and 100+ publications in information systems.

• Computer Architecture
• Embedded Systems
• Machine Learning Accelerators
• +۵ مورد دیگر

Marina Zapater Sancho is a researcher at the Embedded Systems Laboratory (ESL) within the School of Engineering at École Polytechnique Fédérale de Lausanne (EPFL) . She specializes in computer architecture, with a focus on energy-efficient systems, AI accelerators, and memory-centric computing paradigms. Research Interests: Compute-Near-Memory (CnM) : Pioneering architectures like SideDRAM and processing-near-bank designs to reduce energy consumption and latency in DRAM systems. AI Accelerators : Frameworks such as LIONHEART for analog-digital hybrid systems, and Gem5-AcceSys for exploring interconnects in ML accelerators. System Simulation : Contributions to RISC-V full-system simulation validation (gXR5) and component-level calibration methodologies. Her work bridges software and hardware, addressing challenges in heterogeneous systems, thermal management in 2.5D/3D packages, and virtual memory optimization for cache-intensive workloads. Recent trends emphasize energy-proportional computing and edge AI deployment . Grants & Collaborations: Funded by EU H2020 programs and the ACCESS-AI Chip Center (Hong Kong), her research is conducted within the ESL team led by Prof. David Atienza Alonso.