جست‌وجوی استاد و پژوهشگر

Khanh Luongمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Data Mining
• Multi-Aspect Data Clustering
• +۷ مورد دیگر

Dr. Khanh Luong is a Research Fellow at the School of Communication within the Faculty of Creative Industries, Education & Social Justice at Queensland University of Technology (QUT). She holds a PhD in Computer Science specializing in Data Science (2019) from QUT. Her research focuses on multi-aspect data, addressing challenges in high-dimensional, sparse datasets through innovative machine learning and data mining methods. She contributes to real-world applications in diverse domains like text, image, and bioinformatics data. Teaching roles include tutoring in Discrete Mathematics, Programming Principles, and Database Management for undergraduate/postgraduate students. She also designed the online unit 'Introduction to Programming' for the Master of IT program. Research interests span machine learning, data mining, multi-aspect data clustering, dimensionality reduction, and unsupervised learning. She works on the Applied Data Science project at QUT's Centre for Data Science, developing solutions for complex industry datasets. Publications emphasize multi-view clustering, manifold learning, and domain adaptation. Collaborations include roles in organizing the 2021 AusDM conference and reviewing for IEEE journals.

Hans-Joachim Egelhaafمشاهده پروفایل

مدرس ارشد

• Photovoltaics
• Materials Science
• Energy Technology
• +۳ مورد دیگر

PD Dr. Hans-Joachim Egelhaaf is part of the Chair of Materials for Electronics and Energy Technology at Friedrich-Alexander-Universität Erlangen-Nürnberg. He leads the 'Solar Factory of the Future' group, focusing on advancing printed photovoltaic technologies and scalable production processes. His work emphasizes roll-to-roll (R2R) manufacturing, ink formulation using green solvents, and high-efficiency solar module upscaling. He also explores laser ablation patterning, encapsulation techniques, and integration into building-integrated photovoltaics (BIPV). Research interests include optimizing perovskite and organic solar cells, improving outdoor durability, and developing industrially viable processes. His group collaborates on high-throughput platforms and material design for BIPV applications. Recent studies highlight innovations in electrode materials (e.g., silver electrodes via laser printing), process optimization (e.g., gas-quenching for perovskite films), and large-area module efficiency (14.5% certified record). His work bridges laboratory research and industrial scalability, aiming to minimize efficiency losses during upscaling. Key contributions include aerosol-jet-printed encapsulation, CO₂ snow jet cleaning for substrate deburring, and inkjet-printed organic solar cells on 3D objects. His lab emphasizes cross-disciplinary approaches to address challenges in energy alignment, moisture resistance, and mechanical stability.

Stefan Reifمشاهده پروفایل

پژوهشگر

• Energy-Aware Systems
• Parallel Systems
• Operating Systems
• +۳ مورد دیگر

Dr.-Ing. Stefan Reif is a Researcher at the Department of Computer Science 4 (Systems Software) at Friedrich-Alexander-Universität Erlangen-Nürnberg. His research focuses on Energy-Aware Systems and efficient, scalable Parallel Systems, with a particular emphasis on Operating Systems, Real-Time Systems, and Network Latency optimization. He is involved in projects such as LARN (Latency- and Resilience-Aware Networking) and PAX (Power-Aware Critical Sections), funded by the German Research Foundation (DFG). His academic activities include reviewing for top conferences like EMSOFT, EuroSys, and ISORC. Teaching contributions include courses on Concurrent Systems. Supervised theses include work on energy implications of security mitigations (Meltdown/Spectre), system-call aggregation, and energy-demand estimation for neural networks. Publications highlight innovations in energy-efficient OS configurations, cross-layer pacing for edge systems, and synchronization algorithms for real-time multi-core systems. Key research tools include the NEON middleware and ANTILLAS benchmarking framework.

Thanasis Korakisمشاهده پروفایل

عضو هیئت علمی

• Wireless Networks
• Access Layer Protocols
• Cooperative Networks
• +۷ مورد دیگر

Thanasis Korakis is a Research Assistant Professor in the Electrical and Computer Engineering Department at NYU Tandon School of Engineering, affiliated with the Center for Advanced Technology in Telecommunications (CATT). He holds a Ph.D. in Computer and Communication Engineering from the University of Thessaly and has been involved in visiting research roles at UC Riverside and CATT. His research focuses on wireless networks, with an emphasis on access layer protocols, cooperative networks, directional antennas, and QoS provisioning. Education: Bachelor of Technology in Informatics, University of Athens (1994) M.S. in Data Networks and Telecommunications, University of Athens (1997) Ph.D. in Computer & Communication Engineering, University of Thessaly (2005) Research Interests: Dr. Korakis’ work spans experimental testbeds (e.g., Witest Lab), 802.11/802.16 standardization, and implementation of cooperative MAC protocols. His contributions include frameworks for cooperative handoff in wireless mesh networks, MAC protocols leveraging directional antennas, and dynamic rate adaptation for video multicast. Recent work explores 5G V-RAN reliability, AI-driven security systems, and IoT testbeds. Publications: His articles cover topics like 5G network optimization, blockchain applications in telecom, and AI in forensic investigations. Notable trends include experimental validation of network functions, security-enhanced systems, and cross-layer protocol design. Scientific Awards: Ericsson Award of Excellence in Telecommunications (2006) Advising & Grants: He leads the Witest Lab and has served on technical committees for ICC, WCNC, and SECON. His work includes grants related to wireless testbeds and standardization efforts. Collaborations involve institutions like CATT and NYU’s Tandon School. Labs & Teams: He directs the Wireless Implementation Testbed Laboratory (Witest Lab), focusing on real-world experimentation with wireless protocols and technologies.

Shih-Chun Linمشاهده پروفایل

دانشیار

• Networking
• Machine Learning and AI
• Communications
• +۷ مورد دیگر

Dr. Shih-Chun Lin is an Associate Professor in the Department of Electrical and Computer Engineering at North Carolina State University, part of the College of Engineering. His research focuses on wireless software-defined networking systems, IoT, cyber-physical systems, and communications technologies. He holds a Ph.D. in Electrical and Computer Engineering from Georgia Institute of Technology (2017). His research interests include machine learning applications in networking, network function virtualization, and wireless communication in challenging environments such as underground and underwater systems. He has contributed to advancements in edge computing, vehicular networks, and satellite communication protocols. Dr. Lin has been recognized with awards including the 2020 Distinguished TPC Member Award at IEEE INFOCOM and the 2016 Best Student Paper Award Runner-up at IEEE SCC. His work emphasizes practical implementations alongside theoretical analysis, addressing challenges in next-generation cellular networks and 6G technologies. His publications span topics such as satellite swarm dynamics, federated learning in edge networks, and optical cross-connect architectures. Collaborations focus on integrating AI-driven solutions for network optimization and resilience.

• Cryptology
• Intrusion Detection Systems
• Wireless Communication Security

Slobodan Petrovic is a Professor at the Norwegian University of Science and Technology (NTNU) in the Department of Information Security and Communication Technology (IIK), part of the Faculty of Information Technology and Electrical Engineering. His research focuses on Cryptology, Intrusion Detection Systems, and Wireless Communication Security. He teaches Cryptology and Intrusion Detection and Prevention in NTNU's Master in Information Security (MIS) and PhD programs. He is a member of the Cryptology Research Group (Norwegian Applied Crypto Lab - NaCl Lab). His research interests span cryptographic algorithm design, cybersecurity threats in autonomous systems and 5G networks, and secure communication protocols. Recent work includes frameworks for nonlinear combiners in ternary logic, dynamic LFSR analysis, and physical-layer security in MIMO OFDM systems. Publications highlight trends in cybersecurity applications of computational intelligence, intrusion detection systems, and cryptographic analysis. Notable contributions include countermeasures for unmanned vehicles and secure guidance systems. He has been actively involved in developing algorithms for efficient data analysis in digital forensics and cybersecurity analytics. His lab, the NaCl Lab at NTNU, focuses on applied cryptographic solutions. He collaborates on projects related to secure network communication, biometric security, and true random number generation.

Jim Jiمشاهده پروفایل

استاد

• Magnetic Resonance Imaging (MRI)
• Biomedical Image Processing
• Constrained Imaging
• +۷ مورد دیگر

Jim Ji is a Professor in the Department of Electrical and Computer Engineering at Texas A&M University, part of the College of Engineering. His research focuses on advanced MRI and biomedical image processing, including constrained imaging, reconstruction algorithms, cardiac and cancer imaging, and image analysis techniques. He leads the Magnetic Resonance Systems Lab, developing 3D real-time imaging capabilities and automated analysis methods. Education: PhD from University of Illinois at Urbana-Champaign (2003), M.S. and B.S. from Tsinghua University (1997/1993). Active in teaching courses like Signals and Systems, Medical Imaging, and Digital Signal Processing. Supervised over 12 graduate students, including notable alumni like Jong Bum Son and Yuttapong Jiraraksopakun. Developed open-source tools: PULSAR (parallel imaging toolbox) and SID-MRI (dynamic MRI simulation) Received NSF CAREER Award (2008) and Texas A&M travel grants Organized sessions at IEEE EMBS conferences (2003-2005) Recent publications emphasize numerical methods for radiation transport, including diffusion asymptotics, model reduction, and parallel computing solutions. His work bridges computational physics with medical imaging, addressing challenges in dynamic biological imaging and radiation-hydrodynamics coupling.

Yao Yinuoمشاهده پروفایل

استادیار

• Computational fluid dynamics
• Numerical methods
• Wastewater treatment
• +۵ مورد دیگر

Dr. Yao Yinuo is an Assistant Professor in the Department of Civil & Environmental Engineering at Texas A&M University, with an affiliation in Mechanical Engineering. Her research focuses on computational fluid dynamics, numerical methods, and environmental biotechnology. She leads the MSCE Lab, which integrates modeling, simulations, and experiments to address challenges in water treatment, energy storage, and resource recovery. The lab emphasizes transitioning technologies from lab-scale to commercial applications and fosters a collaborative research environment. Education: Ph.D., Civil & Environmental Engineering, Stanford University (2021) M.S., Institute for Computational and Mathematical Engineering, Stanford University (2021) M.S., Civil & Environmental Engineering, Stanford University (2017) B.Eng., Civil & Environmental Engineering, National University of Singapore (2015) Research Interests: Dr. Yinuo’s work spans multiscale modeling of fluid dynamics, porous medium flow, and energy storage systems. She develops hybrid numerical schemes and advanced simulation techniques to study thermal runaway in batteries, reactive transport in porous media, and membrane distillation for desalination. Her lab also explores wastewater treatment innovations and microfluidics applications. Lab Activities: The MSCE Lab actively recruits motivated students for Ph.D. programs starting Fall 2025. Recent lab activities include group outings and presentations at conferences like AWWA WQTC. Notable publications include studies on non-intrusive hybrid schemes for heat transfer and level-set methods for reactive transport.

• Weaving Technologies
• 3D Woven Structures
• Technical Textiles
• +۴ مورد دیگر

Dr Lindsey Waterton Taylor is a Lecturer in Weaving Technologies & Design at the School of Design, University of Leeds. She holds a PhD in 3D Woven Structures for Advanced Textile Composites (2005) and a First Class Honors degree in multilayer-multilevel wovens. Her research focuses on pushing boundaries in conventional weaving technologies, particularly in shaping 2D-to-3D woven forms on loom and integrating biomimetic principles. She led a Knowledge Transfer Partnership (KTP) with the University of Manchester and a SME, developing thermoplastic 3D wovens for automotive applications. Her work bridges design, engineering, and manufacturing to solve complex textile challenges. Her academic background includes industrial experience and specialization in technical textiles, with a focus on automotive, aerospace, and architectural applications. Current teaching responsibilities include leading the BA Fashion Technology program. Research interests span 3D woven preforms, biomimetic design, and digital anthropometry integration into weaving processes. She supervises postgraduate researcher Siyuan (Cyan) Zhao. Key research themes include optimizing textile construction for performance, aesthetics, and sustainability. Her recent work explores Scan2Weave technology linking digital body scanning with 3D weaving for customized apparel, and biomimetic approaches for protective composites. She collaborates across disciplines to advance textile applications in emerging industries. Education: PhD (2005), First Class Honors (2002) Awards: None explicitly listed Grants: KTP project with University of Manchester (2016-2017) Labs/Teams: Active in Leeds School of Design’s textile innovation facilities, collaborating with industry partners on advanced textile projects.

Stavros Toumpisمشاهده پروفایل

دانشیار

• Wireless Networks
• Delay-Tolerant Networks
• Sensor Networks
• +۷ مورد دیگر

Stavros Toumpis is an Associate Professor at the Department of Informatics, Athens University of Economics and Business (AUEB). He previously held positions as a Lecturer at the University of Cyprus (2005–2009) and Senior Researcher at Telecommunications Research Center Vienna (2003–2005). He earned his Diploma in Electrical and Computer Engineering from the National Technical University of Athens (1997) and M.S./Ph.D. degrees in Electrical Engineering and Mathematics from Stanford University (1999–2003). His research focuses on wireless networks, including capacity bounds, cross-layer design, routing protocols, and emerging technologies like delay-tolerant networks, vehicular networks, and sensor networks. He employs tools from probability and optimization theory. Notable projects include the MMLAB (Mobile and Multimedia Lab) and FogSpot, a framework for edge/fog computing pricing. His work spans theoretical and experimental studies, with contributions to network performance analysis, interference modeling, and protocol optimization. Recent research emphasizes delay-tolerant networks, network capacity estimation via digital twins, and hybrid IP-ICN architectures. Key Areas: Multihop wireless networks, DTNs, sensor networks, network economics. Labs/Teams: Member of the MMLAB at AUEB.

Venkat Arunمشاهده پروفایل

استادیار

• Computer Networking
• Congestion Control
• Formal Verification
• +۶ مورد دیگر

Venkat Arun is an Assistant Professor in the Department of Electrical and Computer Engineering at The University of Texas at Austin, within the Cockrell School of Engineering. He previously completed his PhD at MIT under the supervision of Hari Balakrishnan and Mohammad Alizadeh, focusing on networking, systems, and formal methods. Education: Bachelor's Degree, IIT Guwahati PhD, Massachusetts Institute of Technology (MIT) Research Interests: Dr. Arun's research bridges the gap between practical heuristics in computer systems and formal proofs of their performance. He specializes in congestion control , formal verification of network protocols , privacy-preserving systems , and wireless networking . His work develops tools to mathematically prove the behavior of real-world algorithms under real-world conditions, ensuring robustness and fairness. Publication Trends: His recent publications, appearing in venues like ACM SIGCOMM, USENIX NSDI, and NDSS, focus on formally analyzing and improving congestion control (e.g., BBR, Copa), developing verification frameworks (CCAC, CCmatic), designing privacy-preserving reporting systems (SAE), and optimizing real-time communication. A recurring theme is using formal methods to uncover hidden flaws in widely deployed heuristics and designing better alternatives. Scientific Awards: Best Student Paper Award, ACM SIGCOMM 2022 Best Paper Award, NDSS 2020 Advising and Grants: As a new faculty member, Dr. Arun is beginning to build his research group and advise graduate students. While specific grant details are not listed in the provided text, his impactful research and industrial adoption (e.g., by Facebook) suggest strong potential for securing research funding in networking and systems. Labs and Teams: During his PhD at MIT, he was part of a prominent networking research group led by Hari Balakrishnan and Mohammad Alizadeh. At UT Austin, he is establishing his own research lab focused on formal methods for systems, likely continuing collaborations with researchers from MIT, CMU, UT Austin, and industry labs like Facebook and Microsoft Research.

• Offshore Engineering
• Marine Hydrodynamics
• Renewable Energy Systems
• +۳ مورد دیگر

S. Schreier is a researcher affiliated with the Department of Ship Hydromechanics and Structures at Delft University of Technology. Their primary research focuses on offshore engineering, marine hydrodynamics, and sustainable urban development solutions. Schreier has contributed significantly to understanding floating offshore wind turbine systems, particularly in mooring dynamics and structural behavior under damaged conditions. They are also involved in innovative applications of end-of-life ships for coastal protection and urban development. Research interests include experimental investigations of wave-structure interactions, hydroelastic deformation of flexible structures, and the integration of circular economy principles in marine engineering. Schreier has co-authored over 15 peer-reviewed articles and contributed datasets to open repositories, emphasizing reproducibility and collaborative science. Their work spans from fundamental fluid dynamics to applied engineering solutions for renewable energy and urban sustainability challenges.

Vojtěch Hornýمشاهده پروفایل

پژوهشگر

• Plasma Physics
• Laser-Matter Interaction
• Ion Acceleration
• +۵ مورد دیگر

Ing. Vojtěch Horný, Ph.D., is a plasma physicist specializing in laser-plasma interactions and advanced accelerator physics. He is currently a Research Scientist III at the Extreme Light Infrastructure – Nuclear Physics (ELI-NP) in Romania, where he works on the world's most powerful laser systems. His research focuses on ion acceleration, neutron beam generation, laser wakefield acceleration, and secondary radiation sources (terahertz to X-rays). Education: Ph.D. in Physical Electronics (2018) from the Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University, Prague. M.Sc. and B.Sc. in related physics fields from the same institution. Research Interests: Horný's work emphasizes high-intensity laser applications, including proton/neutron acceleration for nuclear astrophysics and advanced diagnostics. He explores novel injection schemes for wakefield accelerators and optimizes plasma-based radiation sources. Recent Work Trends: His articles highlight advancements in multi-petawatt laser systems, attosecond-scale electron bunches, and feasibility studies for laboratory astrophysical processes (e.g., neutron capture sequences). Collaborations include CEA, LULI, and Chalmers University. Awards & Recognition: His papers have been featured in Physics World and Physics . He has been invited to speak at international conferences such as EPS Plasma Physics and SPIE. Grants & Advising: Supervised 3 students and co-led projects like the Apollon facility commissioning. Active in EU-funded initiatives and international workshops. Labs & Facilities: Principal user of ELI-NP's 10 PW laser, Apollon facility, and other high-power laser systems (e.g., PALS in Prague).

• Cyber Security
• Big Data Analytics
• Software Engineering
• +۲ مورد دیگر

Dr. Faheem Ullah is an Assistant Professor in the School of Computer and Mathematical Sciences at the University of Adelaide. He holds a dual role as Lecturer/Assistant Professor and is part of the Centre for Research on Engineering Software Technologies (CREST), where he leads R&D in big data analytics and cloud computing. His research focuses on cybersecurity, big data analytics, software engineering, cloud computing, and machine learning. He has applied these skills in healthcare, oil & gas, defense, and green computing domains. Dr. Ullah is eligible to supervise Masters and PhD students as a co-supervisor, emphasizing collaborative research endeavors. He actively contributes to the design and evaluation of cybersecurity systems, including frameworks for microservices, distributed data processing, and adaptive security analytics. His work bridges theoretical advancements with industry applications, addressing challenges such as vulnerability analysis in microservices, AI-driven threat detection, and optimizing cloud infrastructure. He is a sought-after expert in cybersecurity and cloud-native technologies, with a strong publication record in top-tier venues.

Are Strandlieمشاهده پروفایل

استاد

• High Energy Physics (HEP)
• Particle Physics
• Data Analysis
• +۳ مورد دیگر

Are Strandlie is a Professor at the Physics Institute of the University of Oslo . His research focuses on high energy physics data analysis, particle tracking algorithms, and material science applications in additive manufacturing. Previously, he held roles at CERN and Gjøvik University College. Education: cand. scient., Theoretical Physics, University of Oslo (1995) dr. scient., Experimental Particle Physics, University of Oslo (2000) Research Interests: His work spans advanced track reconstruction methods, particle mass determination, and computational material science. Recent projects include durability analysis of composite materials and optical properties in 3D printing. His research is published in journals like Journal of High Energy Physics and Materials & Design . Grants & Labs: Collaborates with teams like the ATLAS experiment at CERN. Active in material jetting and intermetallic compound studies. No specific grants mentioned in the text.