جست‌وجوی استاد و پژوهشگر

Wen-Chen Huمشاهده پروفایل

دانشیار

• Handheld/Mobile/Smartphone/Spatial Computing
• Location-Based Services
• Web-Enabled Information Systems
• +۶ مورد دیگر

Wen-Chen Hu is an Associate Professor in the Department of Computer Science at the University of North Dakota's School of Electrical Engineering and Computer Science. He has held academic positions at Auburn University (Assistant Professor, 1998–2002) and the University of North Dakota (Assistant/Associate Professor since 2002). His teaching spans courses like .NET/Web Programming, Computer Architecture, Electronic Commerce Systems, and Advanced Database Systems, with over 100 graduate students advised. Education PhD in Computer and Information Science and Engineering, University of Florida (1998) MS in Computer Science, University of Iowa (1993) ME in Information Science and Electronic Engineering, National Central University, Taiwan (1986) BE in Computer Science, Tamkang University, Taiwan (1984) Research Interests : Dr. Hu's work focuses on handheld/mobile/smartphone/spatial computing, location-based services (LBS), web-enabled information systems (e.g., search engines, web mining), database-driven systems (electronic/mobile commerce), and web technologies. His publications emphasize privacy-preserving LBS, spatial trajectory prediction, mobile security, and big data applications. Publication Trends : His recent work (2020–2023) explores pandemic response via mobile analytics, privacy in LBS, and smartphone computing. Earlier (2014–2017), he addressed geometric LBS algorithms, cognitive radio networks, and super-resolution image processing. Foundational work (1998–2005) includes XML search engines, handheld programming languages, and mobile commerce security. Scientific Awards : Best Paper Award, MICS 2015 Best Paper Award, ACM Southeast Conference 2003 Best Reviewer Awards Community Service Awards Advising & Academic Leadership : Dr. Hu has advised over 100 graduate students and served as General Chair for ICETA 2018 and Associate Editor for the Journal of Information Technology Research . He has organized editorial/review roles for over 100 journals and conferences.

CF Chouمشاهده پروفایل

استاد

• Distributed machine learning systems
• Smart healthcare
• Multimedia systems
• +۲ مورد دیگر

CF Chou is a Professor in the Department of Information Engineering at National Taiwan University and an Academician of Academia Sinica. His research is affiliated with the Communications and Multimedia Laboratory, where he explores distributed machine learning systems, smart healthcare, multimedia systems, wireless sensor networks, and performance analysis theory. Office hours for consultations can be arranged via email at ccf@csie.ntu.edu.tw , and further details about his work are available on his personal website . Research Interests: His work focuses on advancing distributed machine learning systems for scalable data processing, integrating smart healthcare technologies for medical innovation, optimizing multimedia systems for efficient content delivery, developing wireless sensor networks for IoT applications, and applying performance analysis theory to enhance system efficiency. These areas reflect a multidisciplinary approach bridging computer science, engineering, and healthcare. Laboratory Affiliation: Communications and Multimedia Laboratory

• Reinforcement Learning
• Military Simulation Technologies
• Medical Signal Processing
• +۳ مورد دیگر

Hüseyin Oktay Altun is an Assistant Professor at Bogazici University, serving as a full-time faculty member. His research focuses on advanced topics such as smart virtual entity design via reinforcement learning, multimedia security with convex optimization, medical/military signal processing, and time series prediction for environmental and financial data. His work bridges theoretical computer science with practical applications in healthcare, defense, environmental science, and energy systems. Notable research interests include the development of autonomous systems for military simulations, AI-driven medical diagnostics (e.g., hip dislocation detection in infants and epilepsy diagnosis), and environmental modeling for pollution prediction. His contributions also extend to cybersecurity, particularly in watermarking and steganography, as well as renewable energy grid management. His publication trends highlight a strong emphasis on reinforcement learning (RL) for multi-agent systems and tactical simulations, alongside deep learning applications in medical imaging, environmental monitoring, and maritime security. His work often integrates interdisciplinary approaches, combining machine learning with domain-specific challenges in defense, healthcare, and energy sectors. While no formal awards or grants are mentioned in the provided text, his extensive list of publications reflects significant contributions to both theoretical and applied computer science. No information on academic advising or lab affiliations is available here, but his research collaborations likely span multiple departments at Bogazici University and international partners.

• Accessibility
• Deaf Studies
• Human-Computer Interaction
• +۴ مورد دیگر

Abraham Glasser serves as an Assistant Professor in the Department of Accessible Human-Centered Computing within Gallaudet University's School of Science, Technology, Accessibility, Mathematics, and Public Health. His teaching portfolio includes graduate courses such as AHC-604 Applied Information Accessibility, AHC-691 Thesis Accessibility Project Planning, and specialized topics in accessibility standards and data visualization, reflecting his commitment to advancing accessible technology education. Professor Glasser's research centers on dismantling digital barriers for deaf and hard of hearing communities through innovative human-computer interaction solutions. His work pioneers sign language interfaces for personal assistants, investigates captioning system optimization, and explores AI-driven accessibility enhancements. Methodologically, he combines empirical user studies with technical development to create genuinely inclusive technologies that address real-world communication challenges faced by deaf users in digital environments. Analysis of his recent publications reveals a strong trajectory toward integrating artificial intelligence with accessibility needs, particularly through large language models for caption customization and robust sign language recognition systems. His research consistently prioritizes deaf user perspectives in technology design, with increasing focus on ethical AI implementation and workplace accessibility solutions as evidenced by his 2025 publications on employment barriers and AI action planning. Professor Glasser actively mentors graduate students, currently advising five master's candidates in accessibility-focused research. His professional service includes leadership roles as Chair for the ASSETS 2023 Student Research Competition and Associate Chair for ACM CHI 2024, demonstrating significant contributions to the accessibility research community. He has secured internal funding through Gallaudet's Faculty Development Committee grant to advance his accessibility initiatives.

• Computer Networking
• Internet Video Streaming
• Quality of Service
• +۴ مورد دیگر

Hui Zhang is a Professor in the School of Computer Science at Carnegie Mellon University, where he has made significant contributions to networking research for over two decades. He received his PhD from the University of California, Berkeley in 1993 and has maintained a prominent research career focusing on internet protocols, video streaming, and network management. His research interests span computer networking, internet video streaming, quality of service, content delivery networks, network protocols, multimedia communication, and network management. Professor Zhang's work has been particularly influential in developing adaptive video streaming technologies and content delivery mechanisms that power much of today's internet video infrastructure. His recent publications demonstrate continued innovation in networked systems, with a focus on improving video quality of experience through machine learning techniques and advanced network control mechanisms. The research trends show an evolution from foundational network protocol design to more application-focused solutions for video delivery and user experience optimization. Professor Zhang has mentored numerous successful researchers who have gone on to make their own significant contributions to the field. His collaborative work spans multiple institutions including Carnegie Mellon University, University of California, and various industry research labs. His research has been supported by substantial grants from NSF, industry partnerships, and has resulted in technologies that have been widely adopted in commercial video streaming services. Professor Zhang maintains an active research laboratory focusing on next-generation networked multimedia systems.

• Multimedia Content Adaptation
• Service-Oriented Systems
• Bioenergy
• +۵ مورد دیگر

Mohd Farhan Md Fudzee is an academic researcher with a focus on interdisciplinary computational research spanning multimedia systems, bioinformatics, and network engineering. His work emphasizes service-oriented architectures, data fusion techniques, and optimization of complex systems. Key contributions include advancements in content adaptation policies for distributed multimedia, machine learning methods for disease gene prediction, and disaster management protocols in mobile ad-hoc networks (MANET). He has collaborated extensively with institutions on projects involving fuzzy logic applications, healthcare informatics, and safety-critical system development. Research interests are driven by practical applications in: Multimedia Adaptation: Developing QoS-aware service selection frameworks and dynamic path determination policies for content delivery networks. Health Informatics: Leveraging machine learning for disease module identification and medical systems reliability assessment. Data Science: Innovating classification methods using fuzzy soft set theory and multi-agent systems for data fusion challenges. Recent work (2022-2024) highlights trends in bioinformatics pathway analysis, social network prediction algorithms, and hybrid routing approaches for disaster response systems. His publications consistently address real-world system optimization across domains like transportation, healthcare, and energy sectors.

• Computer Science
• Human-Computer Interaction
• Information and Communication Technologies for Development (ICTD)
• +۳ مورد دیگر

Richard J. Anderson is a Professor at the University of Washington, with a PhD from Stanford University (1985). His career spans computer science, human-computer interaction, and information technology for development (ICTD). Research Focus: His work integrates mobile technologies for health and education in low-resource settings parallel algorithms and data structures security and privacy challenges in developing regions gender-inclusive digital systems context-aware educational tools Article Trends: Recent publications (2022-2025) emphasize mHealth , mobile financial services , and privacy frameworks in Sub-Saharan Africa and South Asia. Earlier works (1985-1999) focused on theoretical computer science, including parallel list ranking and N-body simulation algorithms.

• Nanoelectronics
• Analog and Digital Circuits
• Signal Processing
• +۳ مورد دیگر

Jørgen Andreas Michaelsen is an Associate Professor at the Department of Informatics, University of Oslo. He is affiliated with the Nanoelectronics (NANO) research group. His research focuses on nanoelectronic systems, analog and digital circuit design, radar systems, wireless sensor networks, and multimedia networking. He holds a Cand.Scient. (Master's equivalent) in Informatics from the University of Oslo, as evidenced by his 2006 thesis titled Suppression of ΔΣ DAC Quantisation Noise by Bandwidth Adaptation . His recent work (2017) includes low-power radar SoC designs for non-contact vital signs detection. Earlier contributions span topics like VCO linearization for ADCs (2013), low-power sensor interfacing (2011), and multimedia streaming optimization (2006–2007). His publications often appear in top-tier conferences such as IEEE ISSCC, NEWCAS, and Norchip, reflecting expertise in both hardware and system-level design. Michaelsen collaborates extensively with industry partners and colleagues on interdisciplinary projects, bridging nanoelectronics with practical applications in healthcare monitoring and wireless communication. His work emphasizes energy-efficient, high-performance circuit solutions for emerging technologies.

Nishanth Sastryمشاهده پروفایل

استاد

• Internet Data Science
• Social Networks
• Computational Social Science
• +۹ مورد دیگر

Professor Nishanth Sastry is a distinguished academic in the Department of Computer Science at the University of Surrey , serving as Associate Head of Research and Innovation. He holds a PhD from the University of Cambridge and has extensive industry experience at Cisco Systems, IBM, and MIT. His research focuses on social networks, computer networks, online harms, edge computing, and privacy , with notable projects analyzing hate speech on Twitter, optimizing LEO satellite networks, and developing privacy-preserving technologies. He has received multiple awards including a SIGCOMM Best Paper Award and nine US patents. Education: Bachelor’s (Distinction) – RV College of Engineering Master’s – University of Texas at Austin PhD – University of Cambridge Research Interests: Nishanth’s work bridges computer networks and social dynamics , applying Internet Data Science to improve system efficiency. Key areas include: Peer-assisted content delivery and edge caching Hate speech detection and mitigation Blockchain-based pervasive systems Satellite network optimization Privacy in social platforms Articles & Impact: His recent work explores conversation kernels for context analysis , LEO satellite gateway placement , and emotion-aware speech synthesis . These studies address real-world challenges like reducing video traffic load and enhancing decentralized web accessibility. Awards & Recognition: Best Paper Award (SIGCOMM 2017) Yunus Innovation Challenge Award (MIT 2016) Multiple IBM and industry accolades Advising & Grants: Supervises PhD students in distributed systems and cybersecurity. Active in securing grants for projects like Transition Guardian (vulnerable user privacy) and EdgeMart (edge network economies). Labs & Collaborations: Leads the Distributed and Networked Systems Group and co-leads the Surrey Security Network . Collaborates with organizations like the Alan Turing Institute, BBC R&D, and Wikimedia Foundation.

Hui Guanمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Programming Systems
• +۳ مورد دیگر

Hui Guan is an Assistant Professor at the Manning College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst. Currently on leave, she works at Amazon AWS developing LLM systems. She holds a PhD in Electrical Engineering from North Carolina State University (2020) and is a member of the PLASMA lab at UMass. Education: PhD in Electrical Engineering, North Carolina State University, 2020 Research Interests: Focuses on machine learning systems, optimizing deep multitask and graph learning. Aims to improve efficiency, scalability, and reliability of ML through system innovations. Leverages principles like composability and locality awareness to democratize ML applications. Awards: NSF CAREER Award (2024) Amazon Research Award (2022) NCSU ECE Distinguished Dissertation Award (2020) IBM PhD Fellowship (2015-2018) Grants and Projects: Includes NSF support for projects like Adaptive Deep Learning Systems and Memory-Driven Collaboration for Embedded Systems. Received grants from Adobe and Dolby. Students and Advising: Advises PhD students including Lijun Zhang, Kunjal Panchal, and Qizheng Yang. Collaborates with students from other groups like Sohaib Ahmad. Labs and Teams: Active member of the PLASMA lab, focusing on programming languages and systems research.

Niklas Carlssonمشاهده پروفایل

استاد

• Distributed Systems
• Network Security
• Streaming Media Technologies
• +۴ مورد دیگر

Niklas Carlsson is a Professor at Linköping University's Department of Computer and Information Science (IDA), where he leads research in distributed systems, network security, and multimedia streaming. He holds a M.Sc. in Engineering Physics from Umeå University and a Ph.D. in Computer Science from the University of Saskatchewan, with postdoctoral experience in Canada. His research spans adaptive streaming technologies, privacy-preserving systems, and sports analytics. Notable projects include the ASTECC initiative on edge-cloud systems and collaborations with Linköping Ice Hockey Club on strategy analysis. He has authored over 150 publications, including works on video fingerprinting, homomorphic encryption, and social media dynamics. Carlsson actively serves on editorial boards and conference committees (e.g., ACM SIGMETRICS, MASCOTS) and has received awards for best papers (2022, 2023) and innovative frameworks like AnonFACES. His lab focuses on real-world applications of theoretical insights, emphasizing measurable performance improvements.

Bang Tranمشاهده پروفایل

استادیار

• Machine Learning
• Internet of Things (IoT) Security
• Cybersecurity
• +۳ مورد دیگر

Bang Tran is an Assistant Professor of Computer Science at Assumption University’s D’Amour College of Liberal Arts and Sciences. Previously, he served as a Senior Lecturer at the University of Transport and Communications (UTC), Vietnam (2003–2018), receiving multiple UTC Excellent Teaching Awards (2013–2017). He earned his Ph.D. in Computer Science from the University of Massachusetts Boston (2023) under Prof. Xiaohui Liang, with prior degrees from Hanoi National University (BSc, 2001), Hochiminh National University (MSe, 2009), and additional research experience at Sonde Health Inc. His research focuses on machine learning applications for IoT privacy/security, voice assistant security, and cognitive health measurement. Notable achievements include the 2021 IEEE ICC Best Paper Award for work on mitigating voice assistant replay attacks, and the 2023 SOUPS poster award for VPASS, a voice privacy monitoring system. He teaches courses like Machine Learning, Data Structures, and Large Datasets. Recent grants include the 2025 Assumption Faculty Development Grant and a 2025 Summer Scholar Fellowship mentoring student Keegan Concannon on AI-driven network intrusion detection. He actively contributes to conferences like ICASSP, ICC, and SOUPS, and has supervised student projects in cybersecurity and AI. Education: Ph.D. UMass Boston (2023); MSe Hochiminh National University (2009); BSc Hanoi National University (2001) Awards: 3 UTC Teaching Awards, ICC2021 Best Paper, Erasmus Mundus Fellowship Labs/Teams: Assumption Cybersecurity Research Group, collaborations with Sonde Health Inc

• Machine Learning
• Computer Vision
• Embedded Systems
• +۳ مورد دیگر

Xiaojun Zhai is a Lecturer in Computing at the Department of Electronics, Computing and Mathematics. His research focuses on machine learning, computer vision, FPGA design, and cybersecurity, with applications in biomedical engineering, embedded systems, and space exploration. He has collaborated extensively on projects involving real-time image processing, sensor networks, and hardware-accelerated solutions. His work emphasizes practical implementations on platforms like Zynq SoC and FPGAs. Zhai's research interests include privacy verification in multimedia systems, deep learning for visual content analysis, and efficient algorithms for planetary exploration. He has contributed to advancements in ECG encryption, gas classification systems, and automated number plate recognition. His publications span journals such as IEEE Access, Journal of Computational Science, and Future Generation Computer Systems. Zhai has co-authored over 25 papers, with topics ranging from biomedical signal processing to service-oriented architectures. His work on multi-sensor data fusion and heterogeneous system design highlights his expertise in interdisciplinary engineering solutions.

Hailu Xuمشاهده پروفایل

استادیار

• Big Data Processing
• Stream Processing Systems
• Edge/Cloud Computing Security
• +۴ مورد دیگر

Dr. Hailu Xu is an Assistant Professor in the Department of Computer Engineering & Computer Science at California State University, Long Beach (CSULB). He holds a Ph.D. in Computer Science from Florida International University (2020), M.S. from University of Toledo (2016), and B.S. from North China Electric Power University (2014). His research focuses on systems design with emphasis on big data processing, stream processing, edge/cloud computing security, and AI integration. He designs systems for social stream data analysis, failure recovery in distributed systems, and combating misinformation in social networks. Research interests include: AI-driven system optimization Edge-cloud collaboration for real-time processing Security in distributed environments Federated learning frameworks Anti-spam mechanisms for social platforms Recent work highlights trends in federated learning efficiency, fault recovery in stream systems, and scalable misinformation detection. His 2023 Neurocomputing paper introduced WSSGCN, while 2024's StraightLine scheduler addresses ML workload optimization. Received NSF Panel Reviewer role (2023) PC member for IEEE Big Data 2024 and ACM Multimedia 2022 Advising undergraduate/graduate students in CS/CE fields. Current projects involve federated learning optimization and edge computing security. His lab develops systems like COS2 for pandemic misinformation detection and Xunified for GPU memory management.

Jürgen Schönwälderمشاهده پروفایل

استاد

• Computer Networks
• Distributed Systems
• Embedded Systems
• +۱ مورد دیگر

Prof. Jürgen Schönwälder is a Professor of Computer Science at the School of Computer Science and Engineering, Constructor University Bremen gGmbH. His research focuses on computer networks, distributed systems, embedded systems, and computer security. He has held positions at TU Braunschweig, University of Twente, and Bell Labs. He leads the Computer Networks and Distributed Systems research group, which addresses challenges in robust network infrastructure and distributed systems resilience. Education: Doctoral Degree in Computer Science, Technical University Braunschweig (1996) Diploma in Computer Science, Technical University Braunschweig (1990) Research Interests: Design of scalable and resilient network services Security in distributed systems Measurement of network performance and behavior IoT and constrained device management Standardization of network protocols (e.g., NETCONF, YANG) Funded Projects: EU Horizon 2020 Concordia (2019-2023) EU FP7 Flamingo (2012-2016) Industry-funded projects in network management and security Key Contributions: Over 100 publications in top venues (IEEE/ACM Transactions, SIGCOMM) and co-chair roles in IETF working groups (NETMOD, ISMS). His work on network configuration (NETCONF), flow analysis, and IPv6 transition mechanisms has shaped modern network management practices.