جست‌وجوی استاد و پژوهشگر

Sezen Arslanمشاهده پروفایل

دانشیار

• Educational Sciences
• English Language Teaching
• Foreign Language Education
• +۶ مورد دیگر

Sezen Arslan is an Associate Professor at Bandirma Onyedi Eylul University, holding roles in the Department of English Translation and Interpreting (Faculty of Humanities and Social Sciences) and the Department of Foreign Languages. She previously served at Van Yuzuncu Yil University as a Doctor Lecturer and Research Assistant. Her academic leadership includes positions as Department Head and Erasmus Coordinator. Her research focuses on sustainable education, EFL pedagogy, teacher training, AI integration, and inclusive practices. Key contributions include work on dialogic teaching, EMI sustainability, and intercultural communication. She has authored over 20 books and 88 articles, with a TÜBİTAK Science Award recognition. Her projects involve national initiatives like TÜBİTAK-funded dialogical teaching workshops and language policy studies. Educationally, she teaches courses like 'Measurement and Evaluation in Foreign Language Teaching' and 'Pedagogical Grammar.' She advises one master’s thesis and has organized conferences like GLOBELT. Her administrative roles include coordinating Erasmus programs and managing academic research projects. Collaborations with institutions like Hacettepe University highlight her network. Her research spans topics from AI in EFL classrooms to sustainable curriculum reforms, reflecting a commitment to innovative and equitable education models.

• Food Safety
• Meat Technology
• Food Waste Management
• +۴ مورد دیگر

Nataša Kilibarda serves as Professor at Singidunum University's Faculty of Tourism and Hospitality Management in Belgrade, Serbia. Her academic career spans over two decades with specialized expertise in food safety, meat technology, and sustainable food systems. She holds doctoral qualifications in Food Hygiene and Technology from the University of Belgrade's Faculty of Veterinary Medicine. Her research focuses on critical food industry challenges including food waste reduction, pandemic-era food safety protocols, sustainable meat production, and hospitality sector food handling practices. Kilibarda's work bridges academic research with practical industry applications, particularly in Serbian and Balkan contexts. Her recent publications demonstrate growing emphasis on sustainable food systems, biogas production from organic waste, and the intersection of tourism with traditional food quality. Her 15 most recent publications reveal consistent contributions to food safety literature with particular expertise in: Meat technology and quality control Microbiological safety of processed foods Food waste management strategies Pandemic impact on food systems Sustainable resource utilization Kilibarda maintains active collaboration with Serbian food industry stakeholders and contributes to national food safety standards development. Her work appears in prominent regional journals including Meat Technology, Journal of Food and Nutrition Research, and Tehnologija mesa.

• Distributed Systems
• Cloud Computing
• Edge Computing
• +۴ مورد دیگر

Thomas Werner Pusztai is a Researcher at the Department of Distributed Systems, TU Wien. His work focuses on cloud-edge continuum systems, serverless computing, and service-level objective (SLO) management. He contributes to projects like RapidREC, TEADAL, and the EU-funded RAINBOW initiative. His research spans distributed scheduling algorithms, edge-cloud resource allocation, and SLO-aware middleware frameworks like Polaris and HyperDrive. Education: Completed a Diploma in Computer Science at TU Wien with a thesis on Model-based design and architecture of fog computing applications (2019). Active in academic conferences, presenting at IEEE/ACM Edge Computing, Cloud, and Fog/Edge events. Research interests include edge computing, cloud-native systems, IoT applications, and optimizing SLO compliance through novel scheduling techniques. His work emphasizes practical frameworks for real-world distributed systems challenges. Projects include developing HyperDrive for serverless function scheduling in 3D edge-cloud spaces, Polaris for SLO-aware microservices orchestration, and SLO Script for complex elasticity-driven SLO implementations.

• Distributed Systems
• Edge Computing
• Serverless Computing
• +۴ مورد دیگر

Stefan Nastic is an Assistant Professor at the Technische Universität Wien (TU Wien), affiliated with the Faculty of Informatics and the Distributed Systems department. He serves as Curriculum Coordinator for the Master’s program in Distributed and Next Generation Computing, and is a Substitute Member of the Curriculum Commission for Informatics. His research focuses on distributed systems, edge computing, serverless computing, IoT, and smart cities. He holds a PhD in IoT cloud systems (2016) and a BSc (not explicitly stated). Key research contributions include frameworks for serverless edge-cloud continuum (e.g., HyperDrive, GoldFish), federated learning applications (e.g., adaptive human activity recognition), and IoT infrastructure governance (e.g., Polaris Scheduler). He leads projects like RapidREC (2023–2025) on supply chain optimization and participates in initiatives like TEADAL (2022–2025) for edge-cloud workflows. Publications span 30+ peer-reviewed articles in top venues like IEEE IoT, ACM, and IEEE Cloud. He supervises graduate students on stateful serverless functions, federated learning, and edge-cloud scheduling. His work addresses challenges in resource management, latency reduction, and scalable distributed systems.

Xue Linمشاهده پروفایل

دانشیار

• Robust and Secure Machine Learning
• Deep Learning on the Edge
• Cyber-Physical Systems
• +۳ مورد دیگر

Xue Lin is an Associate Professor in the Department of Electrical and Computer Engineering at Northeastern University, with a courtesy appointment in Khoury College of Computer Science. She joined Northeastern in 2017 and holds a PhD from the University of Southern California (2016) and a bachelor’s from Tsinghua University. Her research focuses on robust and secure machine learning, deep learning on edge devices, and cyber-physical systems. She leads the High Energy-Efficiency & Performance System Lab, which develops efficient algorithms and systems for applications like autonomous vehicles and medical AI. Dr. Lin’s work is supported by NSF, DARPA, and the U.S. Department of Transportation, among others. Notable achievements include a $1M DARPA grant for adversarial diagnosis systems, a 1st Place ISLPED 2020 Design Contest win, and multiple best paper awards. She has advised students such as Kaidi Xu (PhD’21), Mengshu, and Siyue, who have contributed to impactful projects like adversarial T-shirt attacks and FPGA-based DNN accelerators. Her research also addresses security in autonomous systems and inclusive design challenges for older and visually impaired passengers. Key grants include NSF CPS Small Awards, SaTC Medium Awards, and collaborations with institutions like the University of Maine and Michigan State University. Awards include the 2024 Faculty Fellow Award and recognition in Stanford’s top 2% cited scientists. Her lab’s projects span secure autonomous systems, energy-efficient inference frameworks (e.g., GRIM), and robust neural network verification techniques.

Katherine Flaniganمشاهده پروفایل

استادیار

• Cyber-Physical Systems (CPS)
• Digital Twins
• Infrastructure Resilience
• +۶ مورد دیگر

Katherine Flanigan is an Assistant Professor in the Department of Civil and Environmental Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in the Department of Electrical and Computer Engineering. She holds a Ph.D. in Civil Engineering from the University of Michigan (2020) and earlier degrees from the same institution (M.S.E. in Electrical and Computer Engineering, 2018, and M.S.E. in Civil Engineering, 2016) and a B.S.E. in Civil and Environmental Engineering from Princeton University (2014). Her research focuses on transforming civil infrastructure and urban systems into intelligent cyber-physical systems (CPS) by integrating sensing, computing, and actuation technologies. Key areas include developing wireless sensor networks for smart cities, modeling infrastructure resilience, and leveraging digital twins for data-driven decision-making. She extends this work to cyber-physical-social systems (CPSS), emphasizing human-infrastructure interactions and equity in policy-making through community-driven data. Flanigan is particularly noted for projects combining technical and social dimensions, such as human-in-the-loop control solutions and privacy-preserving urban sensing technologies. Flanigan has received prestigious awards including the NSF Graduate Research Fellowship, the Towner Prize for Outstanding PhD Research, and the Wimmer Faculty Fellow award for teaching innovation. She advises PhD student Lindsay Graff, whose work addresses transportation equity and multimodal networks. Her research also involves collaborations with industry leaders via the Manufacturing Futures Institute, and she leads the Autonomous Infrastructure Systems Lab at CMU. Her teaching contributions include course redesigns focused on hands-on projects, such as constructing habitats for pollinators and Little Free Libraries to blend engineering with community impact. She emphasizes preparing students for real-world challenges through project courses that teach sensing, data analysis, and infrastructure system design under constraints like risk and resource limitations.

Ashwin Aravindakshan Nairمشاهده پروفایل

دانشیار

• Marketing Analytics
• Advertising Allocation
• Customer Behavior Dynamics
• +۳ مورد دیگر

Dr. Ashwin Aravindakshan Nair is an Associate Professor at the UC Davis Graduate School of Management, where he serves as Director of the Master of Science in Business Analytics program. His research examines how brands can optimize advertising resource allocation across regions and media channels, while investigating customer behavior dynamics to improve marketing strategies. Nair teaches courses in Customer Relationship Management, New Product Development, and Business Analytics. Nair's research encompasses advertising allocation models, direct-to-consumer marketing, mobile commerce platforms, and digital marketing analytics. Recent work explores chatbot language translation effects on mobile commerce, quantum-inspired machine learning for disease screening, and data-driven evaluation of pandemic interventions. His publications appear in leading journals including Marketing Science, Operations Research, and Journal of Marketing Research. Analyses of his publications reveal strong emphases on marketing analytics applied to healthcare, public policy, and technology sectors. The research employs advanced methodologies including randomized field experiments, machine learning techniques, and time-series analysis to address real-world marketing challenges. Recent work demonstrates increasing focus on AI applications in marketing and healthcare analytics.

Laura Pozziمشاهده پروفایل

استاد

• Embedded Systems
• Compiler Techniques
• Coarse-Grain Reconfigurable Architectures
• +۳ مورد دیگر

Laura Pozzi is a Full Professor at the Faculty of Informatics, Università della Svizzera italiana (USI), Switzerland, since 2015. She previously held positions as Associate Professor (2011–2015) and Assistant Professor (2005–2011) at USI. Prior to joining USI, she was a postdoctoral researcher at EPFL's Processor Architecture Laboratory (2001–2005), a research engineer at STMicroelectronics (2000), and an Industrial Visitor at UC Berkeley (2000). Education: MS and PhD in Computer Engineering from Politecnico di Milano, Italy (1996–2000). Her research focuses on the interaction between compiler and architecture design, particularly in embedded systems , with key areas including approximate computing , coarse-grained reconfigurable arrays (CGRAs) , high-level synthesis (HLS) , and fuzz testing . She has led projects on automated design space exploration, compiler optimizations for reconfigurable architectures, and error estimation in approximate circuits. Recent Publications span topics like SAT-based mapping for CGRAs , grammar-based fuzzing of shell interpreters , and approximate logic synthesis , reflecting her interdisciplinary work bridging hardware/software co-design and software verification. Scientific Awards: Credit Swiss Best Teaching Award IEEE DAC Best Paper Award Leadership Roles: Co-Program Chair, IEEE Symposium on Application Specific Processors (SASP) Editorial Board Member, IEEE Design and Test Students: Current: Rodrigo Otoni (Postdoc), Morteza Rezaalipour (PhD), Riccardo Felici (PhD), Cristian Tirelli (PhD) Alumni: Ilaria Scarabottolo (PhD/Postdoc), Lorenzo Ferretti (PhD/Postdoc), Georgios Zacharopoulos (PhD), Giovanni Ansaloni (PhD/Postdoc), Paolo Bonzini (PhD)

Wenwu Zhuمشاهده پروفایل

استاد

• Big data analysis
• Multimedia communication and networking
• Multimedia computing
• +۵ مورد دیگر

Wenwu Zhu is a Professor and Vice Chair of the Department of Computer Science and Technology at Tsinghua University. He has held prominent positions at Microsoft Research Asia, Intel Research China, and Bell Labs, establishing himself as a leading figure in multimedia computing and networking with international recognition as a FOREIGN member of the Academy of Europe (elected 2018). His educational background includes: Ph.D. in Electrical and Computer Engineering from New York University (1996) Professor Zhu's research focuses on the intersection of multimedia systems, networking, and big data. His work has pioneered advancements in internet video streaming, multimedia cloud computing, and social-aware content distribution. He has made significant contributions to understanding how multimedia content can be efficiently delivered across diverse network environments, from traditional wired networks to modern mobile and social platforms. His research bridges theoretical computer science with practical applications, with his work on social-aware video content distribution being transferred to Tencent company. His publication record shows a clear evolution from foundational work on internet video streaming in the early 2000s, through multimedia cloud computing in the early 2010s, to more recent work on social-aware multimedia and network embedding using deep learning approaches. This progression reflects the changing landscape of multimedia computing from infrastructure-focused to socially-aware and AI-driven systems. Professor Zhu has received numerous prestigious honors: AAAS Fellow (2016) SPIE Fellow (2013) IEEE Fellow (2010) Minister of Education's Natural Science Award, 1st prize (2017) Chinese Institution of Electronics's Natural Science Award, 1st prize (2015, 2012) National Natural Science Award, 2nd prize (2012) Chief Scientist for NSFC Major Project (2016) Chief Scientist for Ministry of Science and Technology's 973 Project (2014) Multiple Best Paper Awards including ACM Multimedia 2012 As Editor-in-Chief of IEEE Transactions on Multimedia since 2017 and through leadership roles as General Co-Chair for ACM CIKM 2019 and ACM Multimedia 2018, Professor Zhu has significantly shaped the multimedia research community. His research has been supported by major grants including NSFC Major Projects and Ministry of Science and Technology's 973 Projects, demonstrating both academic and national strategic importance. He has published over 300 referred papers with an H-Index of 55, including 6 Best Paper Awards and 7 books or book chapters. Professor Zhu leads a research group at Tsinghua University focused on multimedia big data computing, with strong industry connections. His team has made pioneering contributions to structural network embedding using deep learning and social contextual recommendation systems, bridging theoretical advances with practical applications in social media platforms.

Heiko Bornholdtمشاهده پروفایل

پژوهشگر

• Distributed Communication Middleware
• Overlay Networking
• P2P Networks
• +۳ مورد دیگر

Dr. Heiko Bornholdt is a Researcher in the Computer Networks group at the Department of Informatics, University of Hamburg. He is affiliated with the Faculty of Mathematics, Informatics, and Natural Sciences. His research focuses on distributed communication middleware, overlay networking, and edge computing. He holds a doctoral degree and has been with the university since 2016. Position: Research Associate / Postdoc Office: Room F-622, Vogt-Kölln-Str. 30 Contact: heiko.bornholdt@uni-hamburg.de | +49 40 42883-2332 Research Interests Dr. Bornholdt’s work emphasizes distributed systems , particularly in the context of smart cities and IoT. Key areas include: Overlay networks for edge computing Decentralized privacy-preserving systems Efficient data discovery in IoT Latency-aware network protocols Publications Overview His recent work spans 20+ publications, with significant contributions to: Edge computing middleware (e.g., software-defined overlay networks) Secure communication in untrusted environments Smart urban data spaces Awards & Grants No specific awards mentioned, but active in funded projects including the EU-GDPR compliant blockchain research. Labs & Teams Part of the Computer Networks Team led by Prof. Mathias Fischer, collaborating with researchers like Kevin Röbert and Jeetesh Gupta.

• Quantum Computing
• Quantum Algorithms
• Quantum Error Mitigation
• +۳ مورد دیگر

Yunseong Nam is an Adjunct Assistant Professor at the University of Maryland. His research focuses on advancing quantum computing through innovations in trapped-ion systems, quantum algorithms, and error mitigation techniques. He is particularly known for developing methods to enhance gate fidelity, optimize quantum circuits, and improve fermionic simulations for quantum chemistry applications. Research Interests: Nam’s work spans quantum hardware optimization, entangling gate implementation, and hybrid quantum-classical computing architectures. He emphasizes practical applications like materials science simulations and fault-tolerant protocols, leveraging symmetries and resource-efficient algorithms to address computational challenges. His contributions include breakthroughs in pulse engineering, SPAM error handling, and the design of robust quantum circuits. Key Research Trends: Recent articles highlight advancements in trapped-ion gate optimization (e.g., small-angle Mølmer-Sørensen gates), error mitigation strategies, and quantum circuit compilers. His work frequently intersects with experimental quantum systems, emphasizing real-world implementations over purely theoretical models. Awards & Grants: No specific awards or grants are mentioned in the provided texts. Labs & Teams: While specific lab affiliations are not detailed, his collaborations likely involve quantum computing hardware groups and theoretical teams focused on algorithm optimization.

• Resource Optimization
• Telecommunication Networks
• VLSI Circuit Design
• +۵ مورد دیگر

Professor Arunabha Sen is a faculty member at Arizona State University (ASU), affiliated with the School of Computing and Augmented Intelligence and the College of Health Solutions as a Health Solutions Ambassador. He joined ASU in 1987 and holds a Ph.D. in Computer Science from the University of South Carolina (1987). His research focuses on resource optimization in telecommunication networks, VLSI circuits, hardware-software co-design, and network security. Key areas include algorithm design, combinatorial optimization, and network processor systems. His work spans wireless, optical, and sensor networks, with contributions to video transmission over mobile ad-hoc networks and interference-aware channel assignment. Notable projects include robust network design against WMD attacks and tools for resilient communication networks. He has served on multiple technical committees for conferences like IEEE and IFIP, and contributed to academic initiatives such as capstone courses on network processors. Grants include NSF, DOD-DTRA, and Motorola Labs funding, emphasizing interdisciplinary research in network science and communications. Teaching responsibilities include courses on algorithms, game theory, and network design. His service roles include Associate Editor for IEEE Transactions on Mobile Computing and leadership in graduate program committees. Research outputs include over 30 peer-reviewed publications, with recent work in algorithmic network design and social computing data mining.

Shuvra S. Bhattacharyyaمشاهده پروفایل

استاد

• Signal Processing
• Embedded Systems
• Biomedical Engineering
• +۳ مورد دیگر

Shuvra S. Bhattacharyya is a Professor at the University of Maryland, College Park (UMD), Department of Electrical and Computer Engineering, with a joint appointment in UMIACS. He is also a part-time visiting professor at Tampere University (Finland) and INSA Rennes (France). His research focuses on signal processing systems, embedded systems, biomedical engineering, and machine learning. He has authored 7 books and over 300 papers, and directs the Maryland DSPCAD Research Group. He holds an NSF Career Award and is an IEEE Fellow. His honors include the Fulbright Senior Specialist and FiDiPro Professorship. He advises graduate students and leads projects in neural decoding, cyber-physical systems, and criminal justice AI. Education: B.S., University of Wisconsin-Madison Ph.D., University of California, Berkeley Research Interests: Signal processing architectures, biomedical circuits, embedded software, hardware/software co-design, and AI for healthcare and criminal justice. His work emphasizes real-time systems, energy efficiency, and interdisciplinary applications. Grants & Awards: NIH Grant for real-time neural decoding (2023) IEEE Fellow (2011) Jimmy Lin Entrepreneurship Award (2012) Labs & Teams: Maryland DSPCAD Research Group, collaborating on dynamic data-driven systems, neural interface technologies, and AI ethics in criminal justice. His work integrates academic and industrial partnerships, including roles at Hitachi America and Kuck & Associates.

Ivan De Oliveira Nunesمشاهده پروفایل

استادیار

• Security & Privacy
• Computer Networking
• Embedded Systems
• +۶ مورد دیگر

Prof. Ivan De Oliveira Nunes is an Assistant Professor of Cybersecurity at the University of Zurich (UZH), affiliated with the Department of Informatics (IfI) and the Digital Society Initiative (DSI). Previously, he held a similar position at the Rochester Institute of Technology (2021–2025). He earned his Ph.D. from the University of California, Irvine (UCI) in 2021, advised by Prof. Gene Tsudik, and was part of the Sprout Lab. His academic journey includes a B.S. in Computer Engineering from the Federal University of Espirito Santo (Brazil) and an M.Sc. in Computer Science from the Federal University of Minas Gerais (Brazil). His research focuses on Security & Privacy, Computer Networking, Embedded Systems, and Applied Cryptography. Key areas include IoT/CPS Security, System Security, and Provable Execution in resource-constrained systems. Notable contributions include work on remote attestation, secure software updates, and formally verified security protocols. Prof. Nunes advises multiple Ph.D., M.Sc., and undergraduate students, including current Ph.D. candidates Antonio Joia Neto, Liam Tyler, and Alexandra Lengert. Former advisees include Adam Caulfield (now at U. of Waterloo) and Spencer Roth (M.Sc. 2023). He leads the SPINS Research Group, exploring secure systems design, and has secured grants such as the CRII: SaTC grant (2023). His work bridges theoretical foundations and practical implementations, emphasizing real-world applicability in embedded and IoT systems.

Nabil J. Sarhanمشاهده پروفایل

دانشیار

• Computer Systems
• Deep Learning
• Video Streaming
• +۵ مورد دیگر

Dr. Nabil J. Sarhan is an Associate Professor of Electrical and Computer Engineering at Wayne State University , where he directs the Computer Systems and Deep Learning Research Laboratory and the interdisciplinary M.S. Program in Artificial Intelligence (Systems and Hardware Track) . He previously served as Graduate Program Director and College of Engineering Faculty Assembly Chair. Education : Ph.D. and M.S. in Computer Science and Engineering from Pennsylvania State University (GPA 4.0), B.S. in Electrical Engineering from Jordan University of Science and Technology Internationally recognized for expertise in computer systems , deep learning , video streaming , and AI hardware accelerators , Dr. Sarhan's research bridges theoretical and applied domains in automated video surveillance and medical AI systems . His work includes novel approaches to epileptic seizure prediction , energy-efficient neural network accelerators , and mixed-signal circuit design for edge computing. Recent grant highlights include a $418,907 National Science Foundation award for reconfigurable AI accelerator development. His patent (US Patent 9,313,463) on automated video surveillance systems demonstrates practical technology impact. Scientific Awards IEEE SEM Outstanding Professional of the Year Wayne State President's Excellence in Teaching Award College of Engineering Excellence in Teaching Award WSU Academy of Teachers (2022) IEEE Senior Member (2016) As an educational reform leader , he has chaired over 20 ABET accreditation panels in Saudi Arabia and Palestine, evaluating programs in electrical engineering, computer science, and software engineering. His intellectual property expertise spans significant patent infringement cases including ACQIS v. ASUSTek and VideoShare v. Google .