جست‌وجوی استاد و پژوهشگر

Daniel J. Jacobمشاهده پروفایل

استاد

• Atmospheric Chemistry
• Environmental Engineering
• Climate Modeling
• +۵ مورد دیگر

Roles & Affiliations: Daniel J. Jacob is the Vasco McCoy Family Professor of Atmospheric Chemistry and Environmental Engineering at Harvard University. He leads the Atmospheric Chemistry Modeling Group at the Harvard John A. Paulson School of Engineering and Applied Sciences, part of the Department of Earth and Planetary Sciences. He has held academic ranks including Gordon McKay Professor (1994-2004) and Associate/Assistant Professor (1991-1994), and was a postdoc at Harvard (1985-1987). Education: Ph.D. in Environmental Engineering Science from Caltech (1985), Ingenieur Chimiste from École Supérieure de Physique et Chimie Industrielles (1981), and earlier studies at Lycee du Parc (Lyon). Research Interests: Jacob's work focuses on atmospheric chemistry, climate modeling, and air quality. Key areas include methane emissions, tropospheric ozone, satellite remote sensing, and global biogeochemical cycles. His research integrates field campaigns (e.g., SEAC4RS, ARCTAS) and chemical transport models (GEOS-Chem) to address environmental challenges like pollution and climate change. Publications & Awards: Jacob has authored over 550 peer-reviewed publications, with an H-index of 145 (ISI) and 184 (Google Scholar). Notable awards include the Haagen-Smit Prize (2010), Macelwane Medal (1994), and recognition for teaching and climate science leadership. His work on methane emissions and air quality has been featured in Nature , Science , and AGU journals. Grants & Advising: Jacob advises numerous PhD students and postdocs, many of whom hold academic or research roles globally. He leads international initiatives like the Carbon Mapper project and chairs committees for NASA and the National Academies. His grants support studies on methane detection, aerosol chemistry, and climate policy. Labs & Collaborations: The Atmospheric Chemistry Modeling Group collaborates with NASA, NOAA, and institutions worldwide. Key projects include the GEOS-Chem model, TROPOMI satellite inversion analyses, and the Integrated Methane Inversion (IMI) tool for emissions monitoring.

Hamidreza Karamiمشاهده پروفایل

دانشیار

• Production Engineering
• Multiphase Flow
• Artificial Lift
• +۳ مورد دیگر

Hamidreza Karami is an Associate Professor in the School of Petroleum and Geological Engineering at the University of Oklahoma. His research focuses on multiphase flow, production engineering, artificial lift, and flow assurance, with applications in unconventional wells, geothermal systems, and hydrogen transportation. BSc, Petroleum Engineering, Sharif University of Technology (2009) MSc, Petroleum Engineering, The University of Tulsa (2011) PhD, Petroleum Engineering, The University of Tulsa (2015) Karami's work combines experimental and computational fluid dynamics (CFD) with machine learning to address challenges in gas lift, downhole separators, well cleanout, and leak detection. Recent publications emphasize data-driven modeling of multiphase flow systems and optimization of artificial lift methods. His lab at the University of Oklahoma investigates advanced technologies for flow assurance, including paraffin and asphaltene deposition, foam lifting, and surfactant applications. Collaborative projects involve Tulsa University Fluid Flow Projects (TUFFP) and industry stakeholders.

Andrew Kwongمشاهده پروفایل

استادیار

• Computer Security
• Applied Cryptography
• Side-Channel Attacks
• +۴ مورد دیگر

Andrew Kwong is an Assistant Professor at the University of North Carolina at Chapel Hill in the Department of Computer Science. His research focuses on computer security and applied cryptography, particularly side-channel attacks and defenses, including Rowhammer, Spectre, and cache timing vulnerabilities. He teaches courses such as Hardware Security and Side-Channels and Research Topics in Computer Security , covering topics like transient execution attacks, speculative probing, and cryptographic implementation flaws. Department of Computer Science, UNC Chapel Hill Assistant Professor Teaching COMP 790-184 (Hardware Security) and COMP 790-185 (Computer Security Research) His research involves cutting-edge work on hardware vulnerabilities, including Rowhammer-based key recovery in post-quantum cryptography, cache eviction side-channels, and speculative execution attacks. His publications appear at top venues like IEEE S&P, CCS, and USENIX Security. He received a Best Paper Award Honorable Mention at CCS 2022 for his work on FrodoKEM exploitation. Key trends in his publications include leveraging hardware flaws for data leakage, cryptographic protocol breakdowns, and combining transient execution with memory corruption attacks. His work has implications for hardware design security and cryptographic implementation practices. Best Paper Award Honorable Mention, CCS 2022 Contact: andrew@cs.unc.edu

• Wireless Communications
• Machine Learning
• Digital Twins
• +۵ مورد دیگر

Pierluigi Salvo Rossi is a Professor at the Department of Electronic Systems , Norwegian University of Science and Technology ( NTNU ), with additional roles as Deputy Head of Department (since 2021) and Deputy Manager at the Center for Green Shift in the Built Environment (since 2022). He also serves as a part-time Research Scientist at SINTEF Energy's Gas Technology department. Education: Ph.D. in Computer Engineering, University of Naples “Federico II”, Italy (2005) Dr.Eng. (cum laude) in Telecommunications Engineering, University of Naples “Federico II”, Italy (2002) Research Interests span Wireless Communications , Digital Twins , Machine Learning , and Statistical Signal Processing , focusing on applications like Industrial IoT , Fault Detection , and Energy Systems . His recent Publications highlight trends in Federated Learning , Graph Signal Processing , and Multi-Sensor Anomaly Detection across domains from Natural Gas Pipelines to Subsea Leakages . Scientific Awards include: Exemplary Senior Editor, IEEE Communications Letters (2018) Department Ambassador, NTNU (2016) IEEE Senior Member (since 2011) Professional Roles encompass editorial leadership (e.g., IEEE Sensors Journal) and conference organization (e.g., General Chair for IEEE Sensor Array and Multichannel Signal Processing Workshop, 2022). He leads major funded research projects like PREFERENCE (RCN, 2023-2027) and AUTOSHIP (RCN, 2020-2028).

• Control Theory
• Partial Differential Equations
• Drilling Engineering
• +۶ مورد دیگر

Ole Morten Aamo is a Professor at the Department of Engineering Cybernetics within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU) in Trondheim, Norway. His office is located at Elektro D/B2, D344, Gløshaugen, O. S. Bragstads plass 2, and he can be reached at aamo@ntnu.no or by phone at 73594386. Professor Aamo's research focuses on control theory with particular emphasis on partial differential equations (PDEs) and their applications in drilling engineering and the petroleum industry. His work spans multiple areas including boundary control of hyperbolic systems, adaptive control methodologies, vibration control in drilling operations, and leak detection systems for pipe networks. His research combines theoretical control developments with practical applications in the oil and gas sector, particularly addressing challenges related to stick-slip phenomena, torsional vibrations, and pressure oscillations in drilling operations. His publication record reveals a consistent trajectory of high-impact research in control systems, with a notable shift toward integrating machine learning approaches with traditional control theory in recent years. The majority of his work centers around hyperbolic PDE systems, with applications primarily in drilling engineering and fluid dynamics. His research demonstrates a strong connection between theoretical control developments and practical implementations in the petroleum industry. Professor Aamo has actively supervised multiple graduate students, as evidenced by the master's theses listed in his publication record. His work often appears in top-tier control journals including IEEE Transactions on Automatic Control, Automatica, and IEEE Control Systems Letters, as well as petroleum engineering venues like SPE Journal and ASME publications.

Berk Sunarمشاهده پروفایل

استاد

• Applied Cryptography
• Cybersecurity
• Microarchitectural Security
• +۵ مورد دیگر

Berk Sunar is a Professor of Electrical & Computer Engineering and the founder of the Vernam Applied Cryptography and Cybersecurity Laboratory at Worcester Polytechnic Institute (WPI). He joined WPI in 2000 after holding postdoctoral and research roles at Oregon State University (OSU) and Trust Inc. His work focuses on applied cryptography, microarchitectural security, AI security, post-quantum cryptography, and homomorphic encryption. Sunar received his BSc from Middle East Technical University (1995) and PhD from Oregon State University (1998). Research interests include vulnerabilities in hardware (e.g., Rowhammer, TPM-FAIL), side-channel attacks, and cryptographic implementations. Notable contributions include discovering flaws in Intel CPUs and TPM chips affecting billions of devices, as well as developing defenses like cuHE (GPU-accelerated homomorphic encryption). Publications highlight breakthroughs in transient execution attacks (e.g., LVI, RIDL), post-quantum signature schemes (Dilithium), and cloud security (Firecracker VMM vulnerabilities). Awards include NSF CAREER (2002) and IBM Pat Goldberg Best Paper (2007). Advised over 30 graduate students, many of whom hold senior roles in academia and industry. Current research addresses AI security, quantum-resistant algorithms, and automated attack detection via machine learning. The Vernam Lab remains a hub for cybersecurity innovation.

• Cybersecurity
• Computer Security
• Hardware Security
• +۶ مورد دیگر

Herbert Bos is a Full Professor at Vrije Universiteit Amsterdam, holding positions in the Faculty of Science (Computer Systems department), the Network Institute, and the Systems and Network Security group. His research focuses on hardware and software security, including transient execution attacks, memory exploitation, and vulnerability detection. He has authored over 229 research outputs, including influential papers on Spectre mitigation, Rowhammer attacks, and fuzzing techniques. Notable contributions include frameworks like PANDAcap and BinRec. Bos teaches courses such as Binary and Malware Analysis and Operating Systems. His work aligns with UN Sustainable Development Goals related to innovation and infrastructure security. Education details are not explicitly provided, but his academic titles (prof. dr. ir.) suggest advanced degrees in computer science and engineering. Ancillary activities include roles as an author for Pearson textbooks and a member of the Kiesraad in The Hague. Research interests emphasize cutting-edge hardware vulnerabilities (e.g., Spectre, Rowhammer), memory safety, and automated testing (fuzzing). Recent work highlights practical defenses against transient data leaks (Phantom Trails) and data-only attacks. Collaborations span international institutions, reflecting his global influence in cybersecurity. Publications since 2016 showcase advancements in CPU architecture security, kernel exploitation, and embedded device defenses. His datasets (e.g., PANDAcap SSH Honeypot) provide foundational resources for the security community. Grants and lab affiliations are inferred through his research outputs and teaching roles.

Richard Collinsمشاهده پروفایل

مدرس ارشد

• Water Distribution Systems
• Hydraulic Transients
• Pipe Fatigue Analysis
• +۵ مورد دیگر

Dr Richard Collins is a Senior Lecturer in Water Engineering at the University of Sheffield , affiliated with the School of Mechanical, Aerospace and Civil Engineering. His research focuses on hydraulic transients , pipeline integrity , and smart water infrastructure . Graduated with an Aerospace Engineering degree (2005) and PhD in Materials and Mechanical Engineering (2009) Current research explores pressure transients , leak detection , and autonomous robotic systems for pipeline inspection Projects include fatigue analysis , biofilm mobilisation , and ultrasound-based pipe assessment His publications emphasize cast iron pipe fatigue , acoustic leak detection , and transient-induced contamination . Funded by RCUK and Datatecnics , his work bridges mechanical engineering and civil infrastructure challenges.

Moez Louatiمشاهده پروفایل

دانشیار مدعو

• Fluid Mechanics of Waves
• Pipeline Hydraulics
• Water Loss Management
• +۵ مورد دیگر

Moez Louati is an Adjunct Associate Professor in the Department of Civil and Environmental Engineering at The Hong Kong University of Science and Technology (HKUST). His expertise spans fluid mechanics of waves, pipeline hydraulics, and smart water infrastructure. He holds a PhD from HKUST, supported by scholarships and the SENG PhD Fellowship Award. His research focuses on pipeline defect detection, hydraulic transients, and smart urban water systems, with notable contributions including the discovery of Bragg resonance connections in pressurized pipes. He has led projects funded by RGC, ITF, and international collaborations, and co-founded Hyele Limited, a startup developing pipeline condition assessment technologies. Education: B.Eng. (Electro-Mechanical Engineering) and MPhil (Renewable Energy) from Tunisia’s National School of Engineering of Sfax (ENIS). Professional credentials include HKIE chartered engineer status and roles as Chair of IAHR’s Africa Division and Assistant Editor of the Journal of Hydraulic Research. Research Interests: Fluid mechanics of waves, computational fluid dynamics (CFD), machine learning for infrastructure optimization, and sustainable water management. Key projects include Smart Urban Water Supply Systems and high-frequency wave-based defect detection methods. Awards: Geneva Innovations Expo 2023/24 awards, Straub Award nomination, and HKUST’s Tech-Ship startup funding. Active in international organizations and advisory roles for Hong Kong’s WSD and DSD. Labs & Facilities: Designed three water lab facilities at HKUST and collaborated globally on projects like the FREJLEV Facility’s air-water stratified flow studies. Holds five patents in pipeline diagnostics and HPC applications.

• Statistical Machine Learning
• Signal Processing
• Data Fusion
• +۱۷ مورد دیگر

Salvo Rossi is a Full Professor of Statistical Machine Learning for Signal Processing at the Department of Electronic Systems, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU). He holds leadership roles as Deputy Director for Research and Deputy Manager of the Centre for Green Shift in the Built Environment. Additionally, he serves as a part-time Senior Research Scientist at SINTEF Energy Research. His work bridges academia and industry, with significant contributions to signal processing, machine learning, and IoT systems. Research Interests: Statistical Machine Learning Data Fusion in Wireless Sensor Networks Digital Twins and Industrial IoT Anomaly Detection and Fault Diagnosis Federated and Distributed Learning Graph Signal Processing His recent publications reflect a strong trend toward intelligent, distributed systems for industrial monitoring, particularly in energy and safety-critical environments. The integration of machine learning with signal processing for decision fusion in sensor networks is a central theme. Scientific Awards and Recognition: Exemplary Senior Editor, IEEE Communications Letters (2018) Department Ambassador, NTNU (2016) IEEE Senior Member (since 2011) Editorial and Professional Service: Senior Area Editor, IEEE Transactions on Signal and Information Processing over Networks (since 2025) Topical Editor, IEEE Sensors Journal (since 2022) Area Editor, IEEE Open Journal of the Communications Society (2019–2023) Executive Editor, IEEE Communications Letters (2019–2021) General Chair, IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Trondheim, 2022 He has advised numerous PhD and master’s students (not explicitly listed), led major research projects in IoT and green energy, and contributed to national and international research initiatives. His lab, SPIN (Signal Processing Group), focuses on intelligent signal processing for real-world applications in smart environments and Industry 4.0.

Stephen Beckمشاهده پروفایل

استاد

• Fluid Mechanics
• Flow Measurement
• Pipeline Leak Detection
• +۵ مورد دیگر

Professor Stephen Beck is a faculty member at the University of Sheffield, affiliated with the School of Mechanical, Aerospace and Civil Engineering. He holds a PhD in Mechanical Engineering from the University of Sheffield (1992) and has been a key figure in advancing engineering education and fluid mechanics research. Director of the Centre for Engineering Education (CEE) Instrumental in designing the Diamond building First Faculty Director of Learning and Teaching (2008-2014) His research spans experimental fluid mechanics, leak detection in pipelines, energy systems in buildings, and educational pedagogy. Recent work focuses on optimizing laboratory teaching methods and remote practicals during pandemics. Professor Beck’s publications analyze leak detection systems (e.g., cepstrum analysis, vibro-acoustic measurements) and energy efficiency strategies (e.g., heat pump modeling, building energy use). His 15 most recent articles reflect a blend of fluid dynamics, sustainability, and pedagogical innovation. CATE award for collaboration (2021) Published extensively on pressure wave analysis and educational frameworks He has supervised 28 PhD and MPhil students, including Butterfield (leak signal analysis), AlHarbi (pipeline leak detection), and Castleton (building energy systems). As Faculty Director of Learning and Teaching, he oversaw curriculum reforms like activity weeks and reduced winter exams. The Diamond building, under his leadership, centralizes multidisciplinary laboratory teaching with 50 staff, redefining practical engineering education. His work combines experimental, CFD, and analytical techniques to improve teaching scalability and energy efficiency.

• Water Distribution Systems
• Cybersecurity in Infrastructure
• Resilience Engineering
• +۷ مورد دیگر

Dr. David Ayala Cabrera is an Ad Astra Fellow and Lecturer/Assistant Professor in the School of Civil Engineering at University College Dublin. He holds a PhD in Water and Environmental Engineering from the Universitat Politècnica de València (UPV, Spain), awarded Cum Laude with the Extraordinary Thesis Award 2017. His research focuses on cybersecurity, resilience engineering, and non-destructive testing (e.g., GPR) for critical infrastructure, particularly water distribution systems. He has contributed to projects like STOP-IT (H2020) and ResiWater, addressing cyber-physical threats and network vulnerability. His teaching includes modules like Civil Engineering Systems and Computer Applications in Civil Engineering. Education: B.Eng. (Sanitary Engineering, Universidad del Valle, Colombia), MSc (Hydraulic & Environmental Engineering, UPV), PhD (Water & Environmental Engineering, UPV). He also holds postgraduate certifications in university teaching and leadership. Research interests include smart city technologies, machine learning applications, and infrastructure resilience. His work spans over 49 publications, with recent focus on GPR-based leak detection, cybersecurity, and data-driven state estimation in water networks. Grants: Led projects like the EU-funded WatQual (2018–2019) and contributed to innovative tools for cyber-physical security. Awards: PhD Cum Laude, International Doctor honor, and multiple research fellowships (e.g., KIOS Research Center, Cyprus). Advising: Co-supervised PhD and Master’s theses at UPV on GPR applications and WDS analysis. His lab collaborations include ICCS (Greece), Irstea (France), and the University of Cyprus’s KIOS Center, advancing tools for infrastructure resilience and smart water management.

• Hydraulics
• Hydroacoustics
• Hydroinformatics
• +۶ مورد دیگر

Dr. Wei Zeng is an ARC DECRA Fellow at the School of Architecture and Civil Engineering (University of Adelaide), specializing in hydraulics, hydroacoustics, and smart infrastructure systems. His research focuses on integrating machine learning, IoT, and physics-based modeling for water network monitoring, hydraulic transient analysis, and pipeline condition assessment. He leads the development of anomaly detection systems commercialized via the startup Adelitics Pty Ltd, deployed in five water utilities globally. His work spans smart water networks, sustainable asset maintenance, and pumped hydro energy storage, with contributions to CFD, control systems, and sensor fusion technologies. He supervises PhD students in related fields and teaches engineering courses on structural dynamics and fluid mechanics. Research Interests: Smart IoT-enabled water infrastructure systems Hydraulic transient modeling for aging energy systems Physics-informed machine learning for civil systems Hydroacoustic-based pipeline condition assessment Pumped hydro energy storage integration with renewables Key Contributions: Commercialized IoT leak detection systems through Adelitics Pty Ltd Pioneered paired-impulse response function (IRF) methods for pipeline diagnostics Developed transient prediction frameworks using physics-informed neural networks Advanced sensor placement optimization strategies for sewer systems Teaching & Supervision: Eligible to supervise PhD/Masters students in hydraulics, hydroinformatics, AI, and CFD. Active in courses covering structural analysis, fluid dynamics, and engineering statics.

Rami Younisمشاهده پروفایل

دانشیار

• Petroleum Engineering
• Computational Methods
• High Performance Computing
• +۷ مورد دیگر

Rami Younis is an Associate Professor in the Harold Vance Department of Petroleum Engineering at Texas A&M University, and holds the Marilyn and W.F. Albers '47 Faculty Fellowship. He specializes in computational methods for subsurface engineering, with a focus on coupled thermo-hydro-chemo-mechanical (THCM) dynamics, fracture mechanics, and geomechanical modeling. His work addresses challenges in oil/gas recovery, geothermal energy, and CO2 storage. Education: PhD and M.S. in Petroleum Engineering and Scientific Computing from Stanford University; B.Eng. in Mechanical Engineering from McGill University. Research emphasizes high-performance computing for reservoir simulation, fracture propagation modeling, and subsurface storage security. Recent work includes studies on in-situ geobarriers for carbon sequestration, adaptive time-stepping for seismic event simulation, and multiscale matrix-fracture transfer functions. Publications span computational methods, geomechanics, and unconventional reservoir engineering. He develops advanced numerical models for multiphase flow, geomechanics, and coupled processes. His methods include embedded discrete fracture models (EDFM), XFEM hybrid approaches, and machine learning-augmented simulation frameworks. Current projects involve seismic-assisted fracturing, induced seismicity modeling, and CO2 storage integrity. His lab focuses on integrating physics-based models with data-driven techniques for reservoir performance optimization.

• Measurement and Instrumentation
• Fibre Optic Sensors
• Optical Sensing
• +۷ مورد دیگر

Professor Kenneth Grattan OBE FREng is a leading academic at City St George's, University of London , where he holds the position of Professor of Measurement and Instrumentation and the Royal Academy of Engineering Research Chair in Scientific Instrumentation. He has served in major leadership roles including Head of the Department of Electrical, Electronic and Information Engineering, Dean of the School of Engineering & Mathematical Sciences, and inaugural Dean of the City Graduate School. He is currently the George Daniels Professor of Scientific Instrumentation. Education: BSc in Physics (First Class Honours), Queen's University Belfast (1974) PhD in Laser Physics, Queen's University Belfast (1979) Doctor of Science (DSc), City, University of London (1992) Honorary Doctorate (DUniv), University of Oradea (2014) His research interests focus on the development and application of fibre optic and optical sensing systems for measuring physical and chemical parameters in industrial, environmental, and structural contexts. His work spans structural health monitoring , high-temperature sensing , chemical detection , and industrial process monitoring , often involving custom instrumentation and patented technologies. Supported by EPSRC, EU, and industry partners, his research has led to over 700 publications and strong international collaborations. The recent publications highlight a trend toward advanced optical fibre sensors integrated with nanomaterials (e.g., graphene oxide), molecular imprinting, and machine learning for enhanced sensitivity and specificity. Applications include infrastructure monitoring (pipelines, bridges), environmental sensing (greenhouse gases, humidity), and security (explosives, drugs), demonstrating his focus on real-world industrial and societal challenges. Scientific Awards and Honors: Callendar Medal, Institute of Measurement and Control (1992) Honeywell Prize (twice) Sir Harold Hartley Medal (2012) Applied Optics Divisional Prize (2010) OBE for services to science and engineering Fellow of the Royal Academy of Engineering (FREng) President of IMEKO (2015–2018) Professor Grattan has supervised over 60 PhD and MPhil students and continues to advise research students in optical sensing. He has led numerous grants from EPSRC, EU, and industry, and serves on the editorial boards of key journals such as Measurement Science and Technology and Measurement . He is actively involved in professional societies including the IET, IOP, and IMEKO, and holds visiting professorships in China. He chairs university committees on sustainability and business continuity, reflecting his broader institutional leadership. Labs and Research Teams: He leads a prominent research group in optical fibre sensors at City St George's, collaborating with institutions in the UK, Europe, and China. The team focuses on developing next-generation sensors for industrial and environmental applications, often integrating photonics with material science and data analytics.