جست‌وجوی استاد و پژوهشگر

Yang Huaمشاهده پروفایل

مدرس

• Computer Vision
• Machine Learning
• Visual Recognition
• +۳ مورد دیگر

Dr. Yang Hua is a Lecturer in the School of Electronics, Electrical Engineering and Computer Science at Queen's University Belfast. His research focuses on computer vision, machine learning, and their practical applications, including visual recognition, robust learning with limited data, and hardware-aware systems. He has supervised multiple PhD students in areas like generative adversarial networks and domain adaptation. Affiliations: Institute of Electronics, Communications & Information Technology; Co-Investigator in multiple research projects (e.g., R5159ECS, R2733CPH). Teaching: Courses include 'How to do Research' and 'Database and Programming Fundamentals' for MSc and PhD students. Research Interests: Dr. Hua's work addresses challenges in visual recognition, domain adaptation, and federated learning. He emphasizes real-world applications and has contributed to competitions like PASCAL VOC Challenge and VOT-TIR2015. Awards: Recognized with Queen's University STAR award (2019), VOT-TIR2015 tracker win, and multiple PASCAL VOC Challenge wins. His research has been funded by Microsoft Research and European conferences. Grants & Projects: Includes 'Artificial Intelligence for Vision-Based Navigation' and collaborations on medical imaging (e.g., AMD diagnosis). He leads projects on federated learning and domain adaptation. Labs/Teams: Active in the Institute of Electronics, Communications & Information Technology, contributing to distributed AI and biomedical applications.

• Enterprise Competitiveness
• Internationalization of Enterprises
• Product Management
• +۳ مورد دیگر

Dr hab. Joanna Bednarz , Professor at the University of Gdańsk , serves as Head of the Division of International Trade within the Faculty of Economics' Department of International Business. She coordinates the Erasmus+ program and holds editorial roles, including membership in the University of Gdańsk Publishing House's editorial board. Chair of the Scientific Council of the Polish Economic Society (Gdańsk branch) Member of IESE Business School Alumni Association (University of Navarra) Active in Faculty Council and Economics/Finance Discipline Council Research focuses on enterprise competitiveness, internationalization of businesses, brand management, and consumer behavior. Her work explores: Age-inclusive business practices through silver entrepreneurship studies Digitalization's role in higher education and SME sustainability Cultural adaptation challenges in international markets Impact of nation branding on corporate global expansion Recent publications examine Generation Z's perception of digital surveillance, silver economy's influence on banking, and Industry 4.0's effects on labor mobility. She leads consultations in the Faculty of Economics (room A337) during summer exam sessions. Technical contributions include optimization studies of automated door production systems and economic analyses of value creation through transport management.

Tanveer Ziaمشاهده پروفایل

استاد

• Cybersecurity
• Wireless Sensor Networks
• Internet of Things (IoT) Security
• +۶ مورد دیگر

Professor Tanveer Zia at Charles Sturt University is a leading researcher in cybersecurity, focusing on wireless sensor networks, IoT security, and privacy-preserving data sharing. He leads the Privacy-Preserving Data Sharing in Hyperconnected World research theme and serves as CSU lead in the Cyber Security Cooperative Research Centre (CRC). PhD in Information Technology from the University of Sydney Active in cybersecurity research for over 15 years Extensive publications on wireless sensor network security, biometric security, and cloud security His work spans human-centric cybersecurity , machine self-control , and biomedical signal processing . Recent projects include developing frameworks for local differential privacy and security awareness programs for regional NSW youth. Key article themes include: advanced privacy mechanisms, IoT vulnerabilities, and deep learning applications in biometric systems. Notably, he explores user-driven privacy and cyber diversity metrics for resilient systems. Scientific Awards Emerging Researcher Award (2010) Research Excellence Awards (2010, 2011) Leadership Excellence Award (2013) Academic Excellence Award (2014) Prof Zia supervises doctoral students in digital forensics and contributes to cybersecurity education. His media engagements include appearances on identity theft, computer scams, and youth cybersecurity initiatives.

• Human-Computer Interaction
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Dr. Philipp Mock serves as a Research Fellow at the Leibniz Institute for Knowledge Media (IWM) in Tübingen, Germany, where he has been a core member of the Media Development Group since 2014. His technical expertise centers on developing machine learning algorithms and AI systems for human-machine interaction, with current responsibilities including software development and methodological consulting for ML applications. Education: PhD in Computer Science, University of Tübingen (2017) Diploma in Computer Science, University of Tübingen (2004-2011) Mock's research integrates Human-Computer Interaction with machine learning to analyze behavioral patterns through interaction data. His work spans multimodal interfaces, educational technology, and cognitive assessment systems, with particular focus on translating touch interaction metrics into predictors of cognitive states (ADHD risk, workload) and developing novel collaborative interfaces for tabletop displays. This interdisciplinary approach bridges computer science, cognitive psychology, and educational design to create adaptive systems that respond to user behavior in real-time. His publication trajectory reveals a clear evolution from foundational work on interactive surface technologies (2012-2015) toward sophisticated ML applications for behavioral analysis (2016-2018). Current projects like the longitudinal human-AI interaction study (2024-2026) demonstrate continued innovation in understanding long-term dynamics between users and intelligent systems, with strong emphasis on real-world educational and clinical applications. Mock actively contributes to multiple IWM research labs including Multimodal Interaction, Everyday Media, Perception and Action, and Knowledge Construction. His collaborative projects such as the human-AI interaction study span these labs, reflecting an integrated approach to studying how people interact with increasingly sophisticated AI systems across diverse contexts from museums to educational settings.

• Robotics
• Artificial Intelligence
• Human-Robot Interaction
• +۳ مورد دیگر

Jim Tørresen is a senior researcher at the Department of Informatics , University of Oslo , with a focus on Robotics , Artificial Intelligence , and Human-Robot Interaction . His work spans autonomous systems, machine learning applications, and ethical considerations in AI. Current Affiliation : University of Oslo, Norway Research Interests : Robotics for elderly healthcare and assistive technologies Machine learning in multimodal sensing and personalization Explainable AI and ethical user modeling Adaptive control systems and motion planning Embodied intelligence in creative domains like dance Recent Article Trends include AI-driven healthcare monitoring, social robotics for senior engagement, reinforcement learning in constrained environments, and computational creativity applications. His work emphasizes privacy preservation , real-time interaction , and human-centered design . Collaborations : Frequent collaborations with researchers like Kai Olav Ellefsen , Diana Saplacan Lindblom , and Charles Martin across EU projects and robotics conferences.

Mahdi Boloursaz Mashhadiمشاهده پروفایل

پژوهشگر

• Signal Processing
• Wireless Communications
• Machine Learning
• +۳ مورد دیگر

Mahdi Boloursaz Mashhadi is a researcher at Imperial College London's Department of Electrical and Electronic Engineering, affiliated with the Information Processing and Communications Lab. He holds a Ph.D. in Electrical Engineering from Sharif University of Technology (2018), with prior research roles at the University of Central Florida and Queen's University. His expertise spans signal processing, wireless communications, machine learning applications in communication systems, and biomedical signal processing. Dr. Mashhadi's research focuses on massive MIMO channel state acquisition , deep learning-driven pilot design , and semantic communication frameworks . His recent work explores token-domain multiple access, generative AI integration in communication systems, and federated learning optimizations. He has contributed to foundational studies in sparse signal reconstruction (e.g., iterative adaptive thresholding methods) and wearable health monitoring via PPG signals. Key achievements : Best Paper Award at EWDTS 2012, multiple grants (IEEE, national/regional), and patents (e.g., US Patent 9729160). Current projects include semantic-aware power allocation in generative communications and latency optimizations in distributed deep learning frameworks. Labs/Teams : Member of the Intelligent Systems and Networks (ISN) group at Imperial, collaborating on AI-driven communication systems and edge computing solutions. His work bridges theoretical signal processing with practical implementations in 5G/6G networks, biomedical devices, and distributed machine learning ecosystems.

• Internet of Things (IoT)
• Industry 4.0
• Digital Healthcare
• +۵ مورد دیگر

Christian Jandl is a Researcher and Head of the Digital Technologies Research Group at the Institute of Creative Media/Technologies, University of Applied Sciences St. Pölten. He holds a Master's in Media Technology (specializing in Mobile Internet) from FH St. Pölten (2010–2016) and has been a researcher there since 2016. His work focuses on IoT, Industry 4.0, digital healthcare, and usability. Research & Projects: Leading 20+ projects including DPP4Food (digital supply chain), SensiTrack (privacy-aware IoT tracking), and IoT4LAC (community IoT solutions) Explores tracking systems in manufacturing, healthcare usability, and industrial asset management Develops privacy-by-design frameworks for industrial IoT applications Publications & Impact: Over 15 peer-reviewed articles on topics like privacy in tracking systems, industrial quality control, and AR in production Key contributions to Bluetooth-based asset tracking (BlueDAT framework) and auditory process monitoring Labs & Collaboration: Immersive Media Lab for VR/AR applications Focus on Industry 4.0 initiatives and enterprise asset tracking solutions

Ali Makhdoumiمشاهده پروفایل

دانشیار

• Optimization
• Game Theory
• Networks
• +۷ مورد دیگر

Ali Makhdoumi is an Associate Professor in the Decision Sciences area at Duke University's Fuqua School of Business, with a secondary appointment in the Computer Science Department. He holds a BSc in Electrical Engineering and Mathematics from Sharif University of Technology and a PhD from MIT's Laboratory for Information and Decision Systems, advised by Professors Asuman Ozdaglar and Daron Acemoglu. His research focuses on optimization, game theory, networks, and learning theory, with applications to data markets, privacy, market design, and mechanism design. Key contributions include analyzing inefficiencies in data markets due to privacy externalities, designing privacy-preserving mechanisms, and exploring behavioral manipulation in data-driven systems. He teaches courses such as Decision Models (MBA/WEMBA), Applied Probability and Statistics (MQM program), Convex Optimization (PhD program), and Modeling and Decision Analysis (MMS program). His work has been published in top journals like Operations Research, Management Science, and Econometrica, and recognized in venues like EC, NeurIPS, and WINE. Makhdoumi's research also addresses challenges in epidemics, dynamic pricing, and network effects. He holds patents on utility-aware privacy-preserving techniques and collaborates extensively with industry and academia to bridge theoretical insights with real-world applications.

• Data Engineering
• Data Science
• Indoor Location-Based Services
• +۳ مورد دیگر

Tiantian Liu is an Assistant Professor in the Department of Computer Science at Aalborg University, under the Technical Faculty of IT and Design. Her research focuses on data engineering and systems, particularly in the context of indoor location-based services and data science. Research Interests: Her work spans data management, indoor positioning, spatiotemporal databases, and scalable systems. She applies techniques from data science and computer science to solve challenges in real-time data processing, data quality, and context-aware applications. The publication trend from 2020 to 2024 shows a consistent focus on data engineering, with topics including indoor LBS, query optimization, distributed systems, and data integration. Her research combines theoretical database principles with practical system implementations. Scientific Awards: Prize (1) Advising and Grants: While no formal students are listed, she has participated in externally funded research projects. She was a project participant in Data Management Foundations for Indoor LBS (2019–2021), contributing to foundational work in indoor data systems. Labs and Teams: She is a member of the Data Engineering, Science and Systems research group at Aalborg University, collaborating on data-intensive systems and applications.

Fatemeh Sadjadiمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Data Privacy
• Graph Theory
• +۳ مورد دیگر

Fatemeh Sadjadi is a Research Fellow at the Department of Computing Science, Umeå University. Her work focuses on privacy-preserving machine learning and robust computational methods for dynamic systems. Research Interests: Machine Learning Data Privacy Graph Theory Computational Intelligence Publications: Recent work includes privacy-enhanced community detection in dynamic networks and improved spectral clustering techniques for industrial applications. Research Group: Member of NAUSICA (Privacy-Aware Transparent Decisions group).

Marten van Dijkمشاهده پروفایل

استاد

• Computer Security
• Cryptography
• Secure Processor Design
• +۷ مورد دیگر

Dr. Marten van Dijk is a Full Professor in the Computer Security department at Vrije Universiteit Amsterdam (VU) since 2022 and a Group Leader for Computer Security at CWI since 2020. He also holds a Gratis Full Research Professor position at the University of Connecticut's ECE Department since 2020. Previously, he served as Associate and Full Professor at the University of Connecticut and held research roles at MIT CSAIL, RSA Laboratories, and Philips Research. PhD in Mathematics (1997, Eindhoven University of Technology) M.S. in Mathematics (Cum Laude, 1993) M.S. in Computer Science (Cum Laude, 1991) His research focuses on foundational computer security problems using cryptographic principles, including secure processor design, oblivious computation, and privacy-preserving machine learning. Notable contributions span Physical Unclonable Functions (PUFs), Aegis secure processor architecture, and oblivious RAM protocols. 15+ publications in 2023-2025 address topics like PUF cryptanalysis, differential privacy in federated learning, and Byzantine fault tolerance Key journals: IEEE Transactions on Computers, Journal of Cryptology, ACM CCS Conference Award highlights include: IEEE Fellow (2022) for secure processor design and encrypted computation IEEE Technical Achievement Award (2023) Intel Test of Time Award (2022) ACM CCS Best Paper (2013) A. Richard Newton Technical Impact Award (2015) His technical leadership spans hardware security (blu-ray error correction codes), cryptographic protocol design, and machine learning privacy frameworks. Current projects focus on secure processors with hardware-enforced isolation and differential privacy optimization.

Philip Brownمشاهده پروفایل

دانشیار

• Game Theory
• Multi-Agent Systems
• Cyber-Physical Systems
• +۹ مورد دیگر

Philip Brown is an Associate Professor in the Department of Computer Science at the University of Colorado at Colorado Springs. He received his PhD in Electrical and Computer Engineering from the University of California, Santa Barbara in 2018 under the supervision of Jason R. Marden. His research focuses on the intersection of technology and society, utilizing game theory, optimization, and multiagent systems to study incentive mechanisms, cybersecurity, and smart infrastructure. Current Projects: CAREER: Endogenous Information Design for smart transportation networks AFOSR YIP: Robust multiagent coordination with randomized algorithms Deriving satellite maneuver intent via game theory Past Projects: Socially Networked Autonomy: Autonomous vehicle routing COVID-19 Policy Optimization: Localized decision frameworks Value-Based Access Control: Path security mechanisms Dynamic Aviation Routing: Weather-aware path selection Research Areas: Dr. Brown's work spans game theory applications in cyber-social systems, robust network games, and strategic security modeling. He explores how financial/informational incentives shape crowd behavior in smart cities, cybersecurity vulnerabilities from mis-modeled attackers, and the paradoxes of altruism in transportation networks. Publication Trends: His recent articles focus on endogenous Bayesian games for information design, altruism dynamics in congestion games, security modeling for autonomous systems, and pandemic policy analysis. Key subfields include network robustness, incentive mechanisms, and human-machine interaction in infrastructure systems. Scientific Awards: NSF CAREER award (2025) UCCS Outstanding Teacher Award (2024) AFOSR Young Investigator Award (2022) CCDC Best PhD Thesis Award (2018) Best Paper awards at EAI GameNets, IEEE conferences Advising: Dr. Brown has advised 2 PhD graduates (Joshua Seaton & Brandon Collins) and multiple Master's/undergraduate researchers. His lab (DeSCon) investigates decision-making mathematics in infrastructure, epidemiology, and multiagent systems.

• Artificial Intelligence
• Natural Language Processing
• Knowledge Management
• +۷ مورد دیگر

Jorjeta Jetcheva is an Assistant Professor in the Computer Engineering Department at San José State University, part of the Charles W. Davidson College of Engineering. She brings extensive industry experience from leadership roles at Accenture, Fujitsu Laboratories of America, Itron, and Firetide, where she led innovations in AI, smart grids, and wireless networking. Her research focuses on Artificial Intelligence-based Personal Assistants, Natural Language Processing, and Knowledge Management . Her work bridges human-centered AI and enterprise applications, with emphasis on intelligent agents, knowledge platforms, and ethical AI systems. She explores how AI can enhance user productivity, decision-making, and system security across domains such as healthcare, energy, and customer service. The recent publications highlight a strong trend in Natural Language Processing applied to real-world problems like fake health news detection, agent assist systems, and knowledge graph integration. Her research also spans Smart Grid analytics, cybersecurity, and AI ethics , reflecting a multidisciplinary approach grounded in both theoretical rigor and practical deployment. Scientific Awards: Best Application Paper Award at IEEE Big Data Service 2022 Best Paper Award at SmartGridComm 2014 Top 10 Finalist, Fujitsu Next Generation Product Idea Contest 2016 ('Robo Butler') CSU STEM-NET Faculty Fellow (2023) Advising and Grants: Professor Jetcheva is the Principal Investigator of a $2.5 million NSF S-STEM grant titled 'Empowering Students to Succeed in Engineering and Computer Science'. She actively mentors graduate students, including Master’s student Garima Chaphekar, with whom she co-authored an award-winning paper on fake health news detection. She serves on the SJSU AI Advisory Committee and leads the AI Research Cluster, fostering interdisciplinary collaboration and student success. Labs and Teams: She leads the AI Research Cluster at SJSU, promoting innovation in artificial intelligence across departments. Her work involves close collaboration with students, industry partners, and interdisciplinary teams focused on deploying scalable, ethical AI solutions.

Simon Steuerمشاهده پروفایل

پژوهشگر

• Hybrid Location Models
• Internet of Things
• Data Quality of Environmental Sensors
• +۳ مورد دیگر

Simon Steuer, M.Sc., is a Research and Teaching Assistant (Wissenschaftlicher Mitarbeiter) at the Chair of Mobile Systems within the Faculty of Information Systems and Applied Computer Sciences at the University of Bamberg, Germany. Since 2016, he has been actively contributing to research and teaching in the areas of hybrid location models, Internet of Things (IoT), and data quality of environmental sensors. Education 2014–2016: Master of Science in Applied Computer Science, University of Bamberg 2010–2014: Bachelor of Science in Media Informatics, Hochschule Hof 2004–2007: Vocational Training as IT Systems Electronics Technician, Deutsche Telekom AG Research Interests Simon Steuer's research is centered around the development of hybrid location models that integrate symbolic and geometric location information. He is particularly focused on applications in smart agriculture, such as the WeideInsight project, where he works on energy-efficient localization systems for cattle using Bluetooth Low Energy (BLE) and Mioty (LPWAN) technologies. His work also encompasses the improvement of data quality from environmental sensors, especially in citizen science contexts, and the design of privacy-preserving architectures for smart city labs. Research Projects & Theses Supervision Steuer actively supervises student theses and projects, including: Development of semantic models for hybrid cow location techniques Data generators for smart spaces and agriculture simulations Filtering and evaluation of beacon-based indoor positioning data Literature surveys on map matching and information visualization in smart agriculture Code refactoring for LPWAN-based environmental sensors Design of location data players and visualization tools Labs and Teams He is a member of the Chair of Mobile Systems research group led by Prof. Dr. Daniela Nicklas. The group collaborates on projects such as Explanym , Crowdanym , FutureIOT , Living Lab Bamberg , SIMUTOOL , and WeideInsight , fostering interdisciplinary research in mobile systems, IoT, and smart environments.

Leyla Dogruelمشاهده پروفایل

استاد

• Communication Science
• Digitalization
• Automation
• +۶ مورد دیگر

Leyla Dogruel is a Professor of Communication Science with a focus on Social Communication at the University of Erfurt's Faculty of Philosophy. She serves as Deputy Faculty Equal Opportunities Officer and is a member of the ErfurtLab and the Institute for Planetary Health Behavior. Research spans digitalization, automation, media economics, and algorithm literacy Leads BMBF-funded project AlLiS on algorithm literacy and sourcing competence in extracurricular education Active in Media Structures Network and local journalism expert reports Her academic career includes: Junior Professor for Media Systems and Media Services at Johannes Gutenberg University Mainz PhD in Media Innovations from Free University of Berlin (2012) Current research trends focus on digital skills promotion in extracurricular settings, algorithm understanding in online environments, and source evaluation competence. She develops interventions for critical digital participation with young people. Key affiliations: Media Structures Network Institute for Planetary Health Behavior ErfurtLab research group