جست‌وجوی استاد و پژوهشگر

Peter Steenkisteمشاهده پروفایل

استاد

• Distributed Systems
• Networking
• Security and Privacy
• +۲ مورد دیگر

Peter Steenkiste is a Professor of Computer Science and Electrical and Computer Engineering at Carnegie Mellon University, with appointments in the School of Computer Science and the Computer Science Department. His research focuses on distributed systems, networking, and wireless technologies, including future Internet architectures like XIA and applications in 5G networks. Steenkiste holds a Ph.D. in Electrical Engineering from Stanford University. His work integrates theoretical and applied approaches, often involving prototype development and real-world testing. Research interests include: Future Internet Architecture (XIA) Wireless network optimization Dynamic spectrum access Network telemetry His publications consistently address network efficiency and innovation, with recent works exploring low-latency video delivery, 5G virtualization, and programmable network infrastructure. Awards include IEEE and ACM Fellowships, Andrew Heiskell Honorable Mention, and University of Cantabria Research Award. He has advised students like Shawn Chen and secured grants for projects including REACH (Robust Content Delivery) and FLOYD (Vehicular Edge Computing). He leads research groups at CMU's Gates and Hillman Centers and collaborates with industry partners like Telefonica and ETH Zurich.

Yin Liمشاهده پروفایل

استادیار

• Computer Vision
• Healthcare Applications
• Mobile Health
• +۳ مورد دیگر

Yin Li is an Assistant Professor in the Department of Biostatistics and Medical Informatics at the University of Wisconsin–Madison, affiliated with the School of Medicine and Public Health. He holds additional faculty status in the Department of Computer Sciences (College of Letters and Science). His research focuses on computer vision applications in healthcare, mobile health technologies, and wearable computing systems, with an emphasis on medical imaging analysis, AI-driven clinical solutions, and edge computing for resource-constrained devices. Dr. Li's work bridges theoretical computer science and applied medical informatics, addressing challenges such as adaptive inference for large language models, real-time 3D vision systems, and automated analysis of neonatal care procedures. His projects often involve collaboration with clinical partners to ensure practical impact in areas like intubation guidance, tumor radiotherapy planning, and NICU activity monitoring. He maintains an active research lab with affiliations spanning multiple departments, and his work has been recognized through contributions to benchmarks like Biodrone and RICA2. His website ( https://www.biostat.wisc.edu/~yli/ ) provides further details on ongoing projects and collaborations.

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.

• Mobile Communications
• Wireless Sensor Networks
• Computer Vision
• +۴ مورد دیگر

Dr. Wafa Elmannai is an Associate Professor in the Department of Electrical and Computer Engineering at Manhattan College, where she has been since 2018. She holds a Ph.D. in Computer Science and Engineering from the University of Bridgeport, following M.S. and B.S. degrees in Computer Science from the University of Bridgeport and College of Electronic Technology in Libya. Her research focuses on mobile communications, wireless sensor networks, computer vision, health assistive technologies, and quantum computing. She has received numerous awards including the AAUW grant for assistive device research, and the Best Paper Award at the 2020 IEEE Canadian Conference on Electrical and Computer Engineering. Dr. Elmannai's educational background includes a Ph.D. (2018) from the University of Bridgeport, with earlier degrees from the same institution (M.S. 2015) and Libya (B.S. 2005). Her professional roles include leadership in academic societies such as IEEE and AAUEAA, and committee positions at Manhattan College including the Diversity Committee and ABET accreditation coordination. Her research interests emphasize practical applications of technology for accessibility and healthcare, including frameworks for visually impaired navigation, emergency response systems, and robust sensor networks. She has published extensively in journals like IEEE Transactions and conference proceedings, with a focus on interdisciplinary solutions merging computer engineering and biomedical systems. Award recognition highlights her contributions to assistive technologies, cybersecurity, and academic leadership, including the UPE Outstanding President Award (2018) and multiple engineering achievement awards from the University of Bridgeport. She actively contributes to academic governance and serves as a reviewer for journals such as IEEE Access and Transactions on Neural Systems & Rehabilitation Engineering.

• Signal Processing
• Financial Signal Analysis
• Machine Learning
• +۵ مورد دیگر

Ali Akansu is a Professor in the Department of Electrical and Computer Engineering at NJIT. His academic career spans multiple decades, with significant contributions to signal processing, financial engineering, and multimedia communications. He has led or co-led four major NSF-funded projects, including the Center for Digital Video & Media Research and the Laboratory for Multimedia Signal Processing and Communication. His research focuses on topics such as eigenanalysis for financial portfolios, machine learning in network analysis, and multimodal affective state assessment using EEG and fNIRS. Key research areas include financial signal processing, portfolio optimization, eigensubspace applications, and data hiding techniques. Notable projects involve FPGA-based real-time risk analysis systems and GPU implementations for eigenportfolio analysis. He has published over 190 peer-reviewed articles, with impactful work in journals like Journal of Investment Strategies and Brain Sciences . His recent work combines machine learning with signal processing to address challenges in network traffic forecasting and financial market dynamics. He has also contributed to biomedical signal processing through studies on affective state assessment using neuroimaging techniques. Awards and recognitions include a h-index of 27 and over 2,694 citations. Grants: National Science Foundation (1991-1993, 1997-2002): Real-Time Color Video Workstation, Multimedia Signal Processing Lab, and Digital Video Research Center Labs/Teams: Leadership in NJIT's Laboratory for Multimedia Signal Processing and Financial Signal Processing groups

Marco António Oliveiraمشاهده پروفایل

پژوهشگر

• Multimedia Communications
• Electronics Engineering
• Communications Engineering
• +۱ مورد دیگر

Marco António Oliveira serves as a Researcher at Lisbon Business School, ISCTE - Lisbon University Institute, specializing in Executive Education programs. His academic foundation includes an MSc in Electronics, Communications and Computers Engineering with a focus on Multimedia Communications from the Faculty of Engineering, University of Porto. Education: MSc in Electronics, Communications and Computers Engineering (Specialization: Multimedia Communications) - Faculty of Engineering, University of Porto Research Profile: Dr. Oliveira's work centers on Multimedia Communications , examining real-time data transmission systems, network optimization for streaming applications, and cross-platform media integration. His expertise bridges Electronics Engineering and Communications Engineering , with practical applications in hardware-software interface design and communication protocol development. Current projects emphasize adaptive multimedia delivery systems for business education contexts. Professional Background: Complementing his academic role, he brings industry experience in Web Management and Hardware Technical Assistance, providing applied perspective to his research in communication technologies.

• Deep Learning
• Audio/Video Content Analysis
• Biomedical Data Analysis
• +۳ مورد دیگر

Dr. Markus Mühling is a Research Fellow in the Department of Mathematics and Computer Science at Philipps-Universität Marburg, working under Prof. Bernd Freisleben. His research focuses on deep learning applications for audio/video content analysis and biomedical data interpretation. He joined the group in 2015 and has contributed to projects involving wildlife monitoring, medical imaging, and heritage digitization. His work spans sensor networks, neural network architectures, and edge computing solutions for real-world challenges. Key research areas include: Deep learning for bioacoustic and visual species recognition Automated analysis of biomedical and histological images Edge-based AI systems for resource-constrained environments Content-based retrieval in video and image archives Publications highlight advancements in biodiversity monitoring (e.g., acoustic sensor networks), medical imaging (e.g., blood cell counting), and cultural heritage (e.g., organ tablature transcription). His work bridges theoretical machine learning with practical ecological and biomedical applications.

• Systems
• Networking
• Security
• +۳ مورد دیگر

Matthew Lentz is an Assistant Professor in the Department of Computer Science at Duke University, where he joined in Fall 2021. Prior to his faculty position at Duke, he was a Postdoctoral Researcher at VMware Research Group and continues to collaborate with them as an Affiliated Researcher. His academic journey includes a PhD in Computer Science from the University of Maryland, where he was advised by Bobby Bhattacharjee. Dr. Lentz's research focuses broadly at the intersection of systems, networking, and security. His current research directions include: (1) introducing new abstractions and tools for building secure, trustworthy software systems, and (2) building systems that improve performance for modern networking and machine learning applications. His work spans diverse areas including network performance measurement, security threat analytics, and privacy-preserving systems. His research often addresses practical challenges in real-world systems while maintaining strong theoretical foundations. As an educator, Dr. Lentz teaches courses including Operating Systems (CPS 510), Introduction to Operating Systems (CPS 310), and Secure Software Systems (CPS 585). He is actively involved in mentoring graduate students, currently advising three PhD candidates: Alexander Du (with Danyang Zhuo), Chenyang Liu (with Kartik Nayak), and Luka Duranovic. His recently graduated students include Yongji Wu (now a postdoc at UC Berkeley), Yalu Cai (at CertiK), Nathan Ostrowski (at Octane Security), and Andres Montoya-Aristizabal (at Two Sigma). Dr. Lentz has served on numerous program committees for top-tier conferences including IEEE S&P (2024-2026), MobiSys (2023-2024), MobiCom (2023-2024), CCS (2021-2022), EuroSys (2021), and HotMobile (2021). He also served as Proceedings Chair for SOSP 2023, one of the most prestigious conferences in systems research.

Csaba Zoltán KERTÉSZمشاهده پروفایل

مدرس

• Embedded Systems
• Microcontroller Applications
• Graphical User Interfaces
• +۷ مورد دیگر

Csaba Zoltán KERTÉSZ is a Lecturer at the Department of Electronic and Computers, Faculty of Electrical Engineering and Computer Science, Technical University of Brașov. His research focuses on embedded systems, microcontroller applications, graphical user interfaces, digital signal processing, and real-time operating systems. He has contributed to IoT/M2M communication, wireless sensor networks, and SDR platforms. He has also explored the use of GitHub in collaborative learning and automotive industry-supported curriculum design. Key research interests include: Embedded GUI development frameworks IoT gateway systems using SDR Real-time monitoring and control systems HbbTV architecture performance analysis His recent work (2021-2024) emphasizes: AI-driven programming assessment tools SIMD extension optimization Wireless sensor networks for water distribution Reconfigurable IoT infrastructure Publications span over 15 years, showing sustained contributions in embedded systems, telecommunications, and educational technology. No specific awards mentioned. Labs/Teams: Actively involved in the University's embedded systems and IoT research groups.

Anastasia Ailamakiمشاهده پروفایل

دانشیار مدعو

• Database Systems
• Computer Architecture
• Scientific Data Management
• +۴ مورد دیگر

Anastasia Ailamaki is an Adjunct Associate Professor at Carnegie Mellon University's School of Computer Science, Department of Computer Science. Since 2008, she leads the Data-Intensive Applications and Systems (DIAS) laboratory at Ecole Polytechnique Fédérale de Lausanne (EPFL). Her research focuses on database systems, computer architecture, and scientific data management. She is a co-founder of CMU's Database Group and a member of the Parallel Data Lab. Research Interests: Staged Database Systems Architecture-Conscious Query Processing Automated Database Design for Scientific Data Performance Optimization for Deep Memory Hierarchies Workflow Management and I/O Traffic Modeling Professional Activities: Program Chair, Workshop on Data Management on New Hardware (2006) General Chair, Workshop on Data Management on New Hardware (2005) Editorial roles for IEEE Data Engineering and ACM SIGMOD Teaching: Taught courses like Database Applications, Database Management Systems, and Hot Topics in Database Systems at CMU from 2001-2006. Students: Advised over a dozen PhD and Master’s students, including graduates at Intel, Google, and MIT.

• Cybersecurity
• Machine Learning
• Web Development
• +۳ مورد دیگر

Nikola Savanović is a researcher and academic at Singidunum University, specializing in cybersecurity, machine learning, and web technologies. He holds a PhD in Advanced Security Systems (2024) from Singidunum University, following a Master's in Contemporary Information Technologies (2016) and a Bachelor's in Informatics and Computing (2013), both from the same institution. He also completed high school in Computer-Aided Design at Politehnika School for New Technologies (2003-2007). His research focuses on intrusion detection systems, machine learning optimization for cybersecurity applications, and adaptive web technologies. He has contributed to educational technology through virtual learning environments and game-based learning. His mathematical work includes fixed point theory in b-metric spaces. He has authored/co-authored multiple books on web design, multimedia systems, and digital marketing. Publications highlight interdisciplinary work: hybrid CNN-XGBoost models for medical diagnostics, metaheuristic algorithms for software defect detection, and cybersecurity innovations in healthcare IoT systems. His articles span computer science, mathematics, and data science, emphasizing practical applications in education and healthcare. Despite no listed awards, his extensive publication record and teaching roles reflect significant academic contributions. He actively collaborates on university projects and advises students in informatics and computing disciplines, though no formal student list is provided.

• Embedded Systems
• Embedded Autonomous Systems
• Wireless Communications
• +۵ مورد دیگر

Karim El Sharkawy is a Full Professor in the Department of Electrical and Computer Engineering at Purdue School of Engineering and Technology, Indianapolis. He is also the Director of the Internet of Things (IoT) Collaboratory and has held leadership roles such as Vice President for Research at Egypt Japan University of Science and Technology (E-JUST) from 2009–2012. Ph.D. in Electrical Engineering (Southern Methodist University, 1985) M.S. and B.S. in Electrical Engineering (Alexandria University, 1979 and 1974) His research spans Embedded Systems , IoT , Wireless Communications , and Digital Signal Processing , with recent work focusing on lightweight neural networks, sensor fusion for autonomous vehicles, and real-time AI deployment on embedded platforms. Articles highlight trends in computer vision , edge computing , and low-power IoT applications . He has received prestigious awards including the U.S. Fulbright Scholar Award , Abraham M. Max Distinguished Professor Award , and multiple Best Paper/Presentation Awards at conferences. His grants include millions from Motorola , FreeScale , and NXP , and he has advised over 150 graduate students. Dr. El-Sharkawy established the IoT Laboratory at Purdue and contributed to curriculum innovation in Electric Vehicle Technology and Embedded Systems .

Zdravko Kunićمشاهده پروفایل

استادیار

• Data Science
• Artificial Intelligence
• Decision Support Systems
• +۷ مورد دیگر

Dr. Zdravko Kunić is an Assistant Professor at the University of Algebra, Department of Information Systems and Business Analytics, and a Senior Lecturer at the University of Zadar's Department of Tourism and Communication Sciences. He leads projects at AlgebraLAB, the university's research institution, focusing on data science, AI, and decision support systems. His work spans high-performance computing architectures, cybersecurity honeypots, wind forecasting algorithms, and automated video editing systems. He collaborates with the Jožef Stefan Institute in Slovenia and participates in EU initiatives like the Pan-European Network of Digital Innovation Centers. His research emphasizes visual business analytics, integrating data science into economic and educational progress. Notable projects include developing scientific web applications using Python, traffic management systems with weather forecasting corrections, and TLS security analyses for Croatian websites. He actively contributes to international conferences and the Erasmus+ program, enhancing his expertise in global academic networks. Dr. Kunić's teaching spans undergraduate and graduate courses in information systems, digital communication, and data-driven decision making. His applied work includes designing systems for insurance, telecoms, and public administration. Despite no explicitly listed awards, his extensive project portfolio underscores his impact in both academia and industry.

Ben Wymoreمشاهده پروفایل

استادیار بالینی

• Machine Learning
• Speech Recognition Systems
• Embedded Systems
• +۳ مورد دیگر

Ben Wymore is a Clinical Assistant Professor of Computer Science at Yeshiva University. His professional career includes roles at Intel Corporation, where he contributed to speech recognition and natural grammars for residential productivity applications, and at Crestron Electronics, where he led software development for touchpanels and mobile applications. Wymore holds patents in speech recognition, electronic program guides, and tactile sensory surfaces. His research interests span machine learning, speech interfaces, embedded systems, and residential technologies. Education: BA in Mathematics-Computer Science Interdisciplinary and MS in Computer Science. His industry contributions include innovations in user interface design, multimodal input systems, and embedded hardware-software integration. Wymore’s work bridges academic research and practical applications in consumer technology and enterprise software solutions.

Yun Raymond Fuمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۴ مورد دیگر

Yun Raymond Fu is the COE Distinguished Professor of Electrical and Computer Engineering at Northeastern University, with a joint appointment in the Khoury College of Computer Sciences. His research focuses on Artificial Intelligence, Machine Learning, Computer Vision, and Big Data Analytics, leading the SMILE Lab. He holds a PhD from the University of Illinois at Urbana-Champaign and joined Northeastern in 2012. His work spans anomaly detection, video analysis, and multimodal learning, with over 200 publications in top journals and conferences. Education: PhD in Electrical and Computer Engineering, University of Illinois, 2008. Research Interests: Machine Learning, Computer Vision, Pattern Recognition, Deep Learning, and Cyber-Physical Systems. His lab develops algorithms for video anomaly detection, social media analytics, and domain adaptation. Awards: Includes 7 Young Investigator Awards, 12 Best Paper Awards, and fellowships from IEEE, IAPR, AAAS. Recently recognized as a AAAI Fellow and recipient of the Edward J. McCluskey Technical Achievement Award (2024). Labs & Entrepreneurship: Founded AI startup Giaran (acquired by Shiseido in 2017). SMILE Lab explores cutting-edge AI applications in healthcare, autonomous systems, and multimedia.