جست‌وجوی استاد و پژوهشگر

Riccardo Lazzerettiمشاهده پروفایل

دانشیار

• Privacy-Preserving Technologies
• Secure Multi-Party Computation
• Biometric Security
• +۵ مورد دیگر

Riccardo Lazzeretti serves as Associate Professor at Sapienza University of Rome since September 2022, following progression from Assistant Professor roles (RTD-A/B) at the same institution from 2017-2022. His academic trajectory includes post-doctoral research at the University of Siena's VIPP group, a research grant at the University of Padua, and industry experience at Italian startup Cynny s.p.a. His educational foundation comprises: MSc in Computer Science Engineering, University of Siena (2007) PhD in Information Engineering, University of Siena (2012) Lazzeretti's research centers on privacy-preserving technologies with emphasis on Secure Multi-Party Computation for encrypted signal processing. His work spans biometric security (including multi-biometric authentication), IoT security protocols, blockchain applications in healthcare, and social network misinformation detection. Recent publications demonstrate deep integration of cryptographic techniques with machine learning for resource-constrained devices and critical infrastructure protection. Analysis of his 15 most recent publications reveals dominant trends in IoT/drone security (32% of works), browser/API vulnerabilities (13%), and privacy-preserving architectures (27%). His research consistently bridges theoretical cryptography with practical system implementations, particularly for emerging technologies like NDN and programmable data planes. His scholarly recognition includes: SIGMM Test of Time Paper Honourable Mention (2021) for Multimedia Security contributions IET Biometrics Premium Best Paper Award (2021) Lazzeretti has supervised graduate students at the University of Siena and secured research funding through collaborations with NATO's CMRE, Digital Catapult (UK), and IMT Lucca. Current projects include privacy-preserving consensus algorithms for IoT and blockchain-based health applications. He maintains active partnerships with European research entities including Centre for Maritime Research and Experimentation and Digital Catapult. His laboratory affiliations encompass the VIPP research group at University of Siena and ongoing collaborations with Sapienza's cybersecurity initiatives, focusing on cross-disciplinary teams integrating signal processing, cryptography, and machine learning expertise.

Leonardo Querzoniمشاهده پروفایل

استاد

• Cybersecurity
• Stream Processing
• Dependable Distributed Systems
• +۶ مورد دیگر

Leonardo Querzoni is a Professor at the Department of Computer, Automatic and Management Engineering Antonio Ruberti within Sapienza University of Rome . He currently serves as Deputy Rector for Digital Technologies and Cybersecurity (2024-2026) and President of the CYBER 4.0 Competence Center since 2022. His academic career spans over two decades with 120+ publications. PhD in Computer Engineering (2007) with thesis "Techniques for Efficient Event Routing" Coordinates Italy's first joint PhD program in Cybersecurity (Sapienza-Luiss) Co-author of Italy's National Cybersecurity Framework Research spans Cybersecurity , Stream Processing , Dependable Distributed Systems , and Big Data Scalability . Particular focus areas include: Malware analysis and incident forensics Secure distributed systems Binary code analysis using neural networks Security for cyber-physical systems IoT attack triage Stream processing optimization Key awards: 2023 DEBS 10 Years Time Award 2021 ASPLOS Distinguished Paper 2019 DIMVA Best Paper Runner-Up 2017 DEBS 10 Years Time Award Active in European projects EU-GUARDIAN, ATENA, and national initiatives like PRIN TENACE. Industry collaborations include: Presidenza del Consiglio dei Ministri Leonardo-Finmeccanica CISCO Research Banca MPS

• Artificial Intelligence in Construction
• Building Information Modeling
• Graph Neural Networks
• +۳ مورد دیگر

Dr. Zijian Wang is an independent postdoctoral researcher at the TUM Georg Nemetschek Institute (TUM GNI), Technical University of Munich, advancing construction digitalization through AI and graph-based approaches to Building Information Modeling (BIM). His educational background includes a PhD from Technion – Israel Institute of Technology (Marie Curie Early-Stage Researcher in EU Horizon 2020 Cloud BIM project), a master's in Computer and Machine Vision from Cranfield University, a master's in Civil Engineering from Central South University, and a bachelor's in Civil Engineering from Chongqing Jiaotong University. He has also conducted research at the University of Cambridge and industry work at Trimble Finland. Dr. Wang's research centers on Building Information Graphs (BIGs), transforming design data into graph structures to enable machine learning applications. His work addresses critical gaps in BIM interoperability through semantic enrichment using graph neural networks, with applications in construction safety monitoring, multidisciplinary change propagation, and automated consistency maintenance. Specific projects include PPE detection via deep learning, tunnel temperature data mining, and graph-based object classification. His publication trajectory (2021-2025) demonstrates increasing sophistication in graph-based BIM solutions, evolving from foundational room classification to complex cross-domain interoperability frameworks and generative AI applications for construction planning constraints. He has received significant recognition: Thorpe Medal, European Council on Computing in Construction (EC3) (2023) Eastman Best Ph.D. Paper, Int Joint Conference CIB W78 - LDAC (2021) Dr. Wang supervises theses in TUM's Software Lab and contributes to EU-funded research initiatives. His current BIGs research aims to establish graph-based foundations for generative design tools, fostering more collaborative and intelligent construction workflows through explicit relationship modeling and multi-modal data embedding.

Shweta Shindeمشاهده پروفایل

استادیار

• Trusted Computing
• System Security
• Program Analysis
• +۵ مورد دیگر

Shweta Shinde is an Assistant Professor at the Department of Computer Science, ETH Zurich, leading the Secure & Trustworthy Systems (SECTRS) group. She is affiliated with the Institute of Information Security and the ZISC Center . Research Focus : Trusted computing, system security, and program analysis, with emphasis on foundational and practical security for devices ranging from phones to accelerators. Key Awards : Best Paper Award at SysTEX 2025, Distinguished Paper Award at USENIX Security 2024, Best Applied Research Paper Award at DeFi’25. Advising : Mentors PhD students including Mark Kuhne, Supraja Sridhara, and Benedict Schlüter. Service : Active in PC/steering committees for Oakland, NDSS, CCS, and others.

• Cryptography
• Internet of Things (IoT)
• Wireless Communications
• +۳ مورد دیگر

Arslan Shafique is a Research Fellow at the University of Glasgow affiliated with the Autonomous Systems & Connectivity research group. His work focuses on developing secure communication frameworks for emerging technologies in healthcare, automotive, and industrial systems. His core research areas include: Cryptography Internet of Things (IoT) Wireless Communications Medical Imaging Security Machine Learning for Security Radar Signal Processing Analysis of his 2024-2025 publications reveals a strong emphasis on quantum-inspired and chaotic encryption techniques applied to medical telemedicine and automotive safety. His work consistently integrates machine learning to optimize security for resource-constrained IoT devices within 5G/6G networks, demonstrating practical solutions for real-world deployment challenges. No scientific awards were documented in the source material. Details regarding student supervision or research grants were not provided in the available information. He actively contributes to the Autonomous Systems & Connectivity team at the University of Glasgow, which specializes in advanced security solutions for next-generation autonomous communication systems.

• Electrical Engineering
• Diagnostics of Electrical Machines
• Induction Motor Diagnostics
• +۴ مورد دیگر

Jarosław Tulicki serves as a Lecturer at the Department of Electrical Engineering within the Faculty of Electrical and Computer Engineering at Cracow University of Technology. Having recently completed his doctorate in 2024, he specializes in electrical machine diagnostics with emphasis on induction motor fault detection through non-invasive techniques. His research focuses on rotor cage damage diagnostics using stator current spectrum analysis and axial flux signal processing under steady-state conditions. Key contributions include methodologies for detecting rotor asymmetries in double-cage induction motors and developing diagnostic systems for industrial applications like tramway drive systems. His work bridges theoretical electromagnetic modeling with practical condition monitoring solutions. Tulicki's publication record demonstrates consistent research progression from fundamental electromagnetic analysis (2015-2018) toward applied diagnostic systems (2019-2024). The most recent works emphasize double-cage motor diagnostics and real-time implementation, showing strong technical depth in signal processing and system integration. His research consistently targets industrial applicability while maintaining rigorous theoretical foundations. With 27 publications yielding an h-index of 4 in both Scopus and Web of Science, his scholarly impact is reflected in a total ministerial score of 497 within the Polish academic evaluation system. His ORCID profile (0000-0003-1720-3448) documents this active research trajectory.

Xiaolin Xuمشاهده پروفایل

دانشیار

• Security
• Machine Learning
• AI Security/Privacy
• +۵ مورد دیگر

Xiaolin Xu is an Associate Professor in the Department of Electrical and Computer Engineering at Northeastern University. His research focuses on hardware and AI security, machine learning privacy, and energy-efficient deep learning. He earned a PhD from the University of Massachusetts Amherst and completed postdoctoral work at the Florida Institute for Cybersecurity Research. Education PhD, Electrical and Computer Engineering, University of Massachusetts Amherst, 2016 M.S., B.E., University of Electronic Science and Technology of China Research Interests : His work spans secure hardware design, AI model protection, and embedded systems security. Notable projects include securing FPGA-based ML accelerators and developing defenses against adversarial attacks. Recent Article Trends : Recent publications emphasize robustness in neural architectures, secure multi-party computation, and lightweight graph-based models for edge devices. Grants & Awards 2025 DAC Under-40 Innovators Award NSF CAREER Award (2023) Multiple NSF grants for hardware security research Advising : Supervises PhD students including Shijin Duan and Jiaxing, focusing on ML security and hardware-software co-design.

• Image Processing
• Signal Processing
• Data Compression
• +۴ مورد دیگر

Dr. Guang Deng serves as an Adjunct Associate Professor in the College of Engineering at La Trobe University, where he has maintained academic appointments since 1994. His technical expertise bridges communications engineering, signal processing, and advanced image analysis with practical applications in medical devices and computer vision systems. Academic Background: BSc from Sun Yat-Sen University MEng from Chinese Academy of Sciences PhD from La Trobe University Dr. Deng's research program centers on generalized linear image processing and statistical signal processing , with significant contributions to lossless image compression algorithms and noise reduction techniques specifically engineered for cochlear implant devices. His methodology combines theoretical mathematical frameworks with practical hardware implementation constraints, particularly evident in his recent work on fixed-point acceleration methods for resource-limited systems. His publication trajectory reveals consistent innovation in image filtering techniques, evolving from foundational work on discrete Laplacian operators to contemporary deep learning applications in marine imaging. Key thematic developments include the progression from traditional signal processing to hybrid approaches incorporating machine learning, with growing emphasis on real-world constraints like embedded system limitations and illumination variability in agricultural imaging. Funded Research Initiatives: Virtual Speech Pathologist (National ICT Australia, 2013-2016) ARC Centre of Excellence in Electromaterial Sciences (Australian Research Council, 2009-2013) Dr. Deng maintains active research collaborations across engineering and life sciences domains, particularly evident in his cross-disciplinary work on plant phenotyping systems and medical device signal processing. His current research demonstrates increasing focus on edge computing applications and biometric security systems alongside his longstanding image processing expertise.

Lingxiao Jiangمشاهده پروفایل

دانشیار

• Software Engineering
• Program Analysis
• Software Testing & Debugging
• +۵ مورد دیگر

Lingxiao Jiang is an Associate Professor at the School of Computing and Information Systems (SCIS) at Singapore Management University (SMU) in Singapore. His research and teaching interests focus on software engineering, program analysis, testing & debugging, code search & reuse, and deep learning & analysis of code. He is actively involved in multiple research tracks across major software engineering conferences including ASE, ICSE, ESEC/FSE, and MSR. His research interests encompass practical techniques and tools that enhance software quality, increase development productivity, reduce maintenance cost, and improve user experience. He also explores programming languages, systems, security & privacy, data mining, and machine learning to solve software engineering and security problems. His work focuses on context-aware software mining, analysis, and deep learning, with applications in code clone detection, code query processing, bug detection, search for bug fixes, refactoring, and testing & debugging techniques. Professor Jiang's research involves large-scale, diverse, contextual data sources beyond program code, including code change histories, bug databases, test suites, developer activities, user feedbacks, and socio-technical information. His methodology leverages static & dynamic program analysis, code representations, software engineering methodologies, natural language processing, information retrieval, data mining, deep learning, and distributed computing techniques. His research has resulted in numerous publications with significant impact, including the DECKARD tool which received the ACM SIGSOFT Impact Paper Award in 2018. His work spans various areas including scalable code clone detection, deep learning of code, and analysis of software repositories. Scientific Awards: ACM SIGSOFT Impact Paper Award 2018 for DECKARD paper ICSE '18 Distinguished Paper Award for Hierarchical learning of cross-language mappings Professor Jiang actively advises graduate students and has mentored numerous PhD and Master's students to completion. He also leads the Centre for Research on Intelligent Software Engineering (RISE) at SMU, which focuses on high-quality and impactful research in intelligent software engineering. His research has practical applications in various domains including Android security, smart contracts, drone security, and compiler testing.

Prahlad Murthyمشاهده پروفایل

استاد

• Environmental Engineering
• Air Quality
• Water and Wastewater Treatment
• +۳ مورد دیگر

Prahlad Murthy serves as Professor of Environmental Engineering and Associate Dean for the College of Science & Engineering at Wilkes University, where he has held academic positions since 1993. He also directs Global Engagement initiatives and advises the university's Air & Waste Management Association student chapter. His educational credentials include: Ph.D. in Civil & Environmental Engineering from Texas A&M University M.S. in Environmental Engineering from Anna University, Chennai, India B.S. in Civil Engineering from Bangalore University, Bangalore, India Dr. Murthy's research integrates environmental engineering with practical applications, focusing on air quality management, sustainable water treatment systems, and geospatial technologies for environmental monitoring. His work bridges classroom instruction with real-world challenges like Marcellus Shale development and homeland security applications, while emphasizing ethical professional practices in engineering education. His publications demonstrate consistent focus on embedding regional environmental issues into undergraduate curricula, advancing sustainability frameworks in engineering education, and applying geospatial tools to complex challenges like energy extraction and security monitoring. Notable recognitions include: Wilkes University Outstanding Advisor Award (2015) Wilkes University Alumni Mentorship Award (2013, 2005) Air & Waste Management Association Education Award (1999) Outstanding Teaching Award (1997) Dr. Murthy has mentored numerous senior capstone design teams and independent research projects while serving as ABET program evaluator for over a decade. His administrative leadership includes department chairmanship and current associate deanship, driving curriculum development and accreditation compliance. He co-founded and advises Wilkes' A&WMA student chapter, and served as Chair (2013) and Vice-Chair (2012) of the Mid-Atlantic States Section, fostering industry-academia partnerships through regional conferences and professional development initiatives.

Hamed Haddadiمشاهده پروفایل

استاد

• User-Centered Systems
• IoT
• Applied Machine Learning
• +۴ مورد دیگر

Professor Hamed Haddadi holds the position of Professor of Human-Centred Systems at the Department of Computing, Faculty of Engineering, Imperial College London. He is also an Imperial College Research Fellow and serves as Security Science Fellow at the Institute for Security Science and Technology. In industry, he acts as Chief Scientist at Brave. His research focuses on User-Centred Systems, IoT, Applied Machine Learning, Privacy, and Human-Data Interaction. He leads the Imperial-X initiative and holds an EPSRC Open Plus Fellowship (2022-2027). His work bridges academia and industry, addressing challenges in privacy-preserving technologies, edge computing, and secure AI systems. Affiliations include the Artificial Intelligence Network, Centre for Cryptocurrency Research and Engineering, Data Science Institute, Energy Futures Lab, and Institute for Security Science and Technology. He actively supervises PhD students through programs like the President’s PhD Scholarships and Islamic Development Bank scholarships. Recent research trends emphasize privacy-preserving AI, secure edge computing, federated learning, and IoT security. His publications span topics like differential privacy, adversarial ML defense, and energy-efficient neural networks. Notable awards include the EPSRC fellowship supporting his work on Human-Centred Systems. Grants include Imperial College Research Fellowships and collaborations with industry partners. He directs the NetSys group and contributes to interdisciplinary initiatives like the Energy Futures Lab. His work often involves collaborative projects with industrial partners such as Brave Software to advance real-world applications of secure technologies.

• Wireless Security
• Cyber-Physical Systems Security
• Location Privacy
• +۵ مورد دیگر

Bruce DeBruhl is an Associate Professor in the Computer Science and Software Engineering Department at California Polytechnic State University (Cal Poly San Luis Obispo). He is affiliated with the Computer Engineering Program and focuses on research areas including wireless security, cyber-physical systems, automotive security, and privacy engineering. His teaching portfolio includes courses such as Intro to Computer Security, Privacy Engineering, Network Security, and Hardware Security. Dr. DeBruhl holds a PhD and MS in Electrical and Computer Engineering from Carnegie Mellon University Silicon Valley (under Patrick Tague) and a BS in Electrical Engineering from Kettering University. His research explores cutting-edge topics like jamming defense algorithms for OFDM systems, security in autonomous vehicle platoons, and privacy-preserving vehicular communication protocols. Recent work includes developing interleaving algorithms to resist jamming attacks, analyzing adversarial strategies in vehicular networks, and creating educational frameworks to introduce privacy concepts to computing students. His publications span prestigious venues like IEEE WiSec, ACM SIGCSE, and Digital Humanities conferences. Though no scientific awards are explicitly listed, his prolific publication record (over 20 papers since 2010) and active involvement in cybersecurity education indicate significant contributions to the field. Current projects include vehicular radio tracking, collaborative autonomous vehicle security testing, and pedagogical innovation in CS education.

Kanad Basuمشاهده پروفایل

استادیار

• Hardware Security
• AI Hardware
• Quantum Computing
• +۶ مورد دیگر

Kanad Basu is an Assistant Professor in the Department of Electrical & Computer Engineering at the University of Texas at Dallas (UTD), affiliated with the Erik Jonsson School of Engineering and Computer Science. He holds the title of Fellow, Eugene McDermott Distinguished Professor. Previously, he worked at IBM and Synopsys, and was an Assistant Research Professor at New York University. His research focuses on hardware security, AI hardware, quantum computing, and VLSI testing. Basu has authored over 130 peer-reviewed publications, 2 patents, and received the Best Paper Award at the 2011 International Conference on VLSI Design. Education: PhD and MS in Computer Engineering from the University of Florida (2012), BE in Electronics and Telecommunication Engineering from Jadavpur University, India (2007). Research Interests: His work spans hardware security (e.g., side-channel attacks, hardware Trojans), functional safety in automotive systems, quantum computing EDA tools, and AI-driven verification techniques. Recent projects include secure assertion generation using LLMs, radiation hardening for edge AI, and quantum circuit equivalence checking. Recent Achievements: Won NSF CAREER Award (2025), served on TPC for IEEE DATE 2026 and IEEE Quantum Week 2026, and led the TIES lab to win NSF CAREER funding. His lab has produced over 15 PhD graduates, many now in industry roles at Intel, NXP, and Oak Ridge National Lab. Awards: Includes NSF CAREER (2025), IEEE Top Picks (2024/2023), and Blavatnik nomination (2019). Academic service roles include associate editorships for IEEE Design & Test and IET Computers. Lab & Collaborations: The Trustworthy & Intelligent Embedded Systems (TIES) lab collaborates with NSF CHEST and TxACE. Ongoing projects involve quantum simulation frameworks (QuaSi), secure DNN acceleration (MENDNet), and radiation-aware functional safety.

• Software Engineering
• Cybersecurity
• Internet of Things (IoT)
• +۴ مورد دیگر

Jacques Pasquier is a Professor in the Department of Informatics at the University of Fribourg, Switzerland, and Head of the Software Engineering Group. His academic affiliation falls under the Interfaculty Informatics unit, emphasizing interdisciplinary research and education in computer science. His research and teaching focus on software engineering, cybersecurity, IoT systems, and agile methodologies. Research interests include IoT security, blockchain applications in decentralized networks, and privacy-preserving technologies. He has contributed to frameworks for secure IoT middleware, lightweight communication protocols, and trusted execution environments. His work bridges theoretical advancements with practical implementations, such as the ImputeGAP library for time series imputation and the Universal Explorer for Web of Things interoperability. Publications span topics like secure IoT infrastructure, blockchain-enabled LPWAN systems, and agile development metrics. His articles often address challenges in privacy, scalability, and resilience within distributed systems. While no specific awards are mentioned, his prolific publication record highlights sustained contributions to computer science and engineering. Led the Software Engineering Group, focusing on advancing methodologies for modern software systems. Collaborates on projects involving industry and academic partners to address real-world challenges in IoT and cybersecurity.

• Cybersecurity
• Cryptography
• IT Security
• +۷ مورد دیگر

Assoc. Prof. Peter Schartner is an Associate Professor at the Department of Artificial Intelligence and Cybersecurity, Alpen-Adria-Universität Klagenfurt. He also serves as the Data Protection Officer, overseeing institutional compliance with data privacy regulations. His research focuses on cybersecurity, cryptography, and secure communication systems, with particular emphasis on automotive cybersecurity, quantum-resistant protocols, and secure exam environments. His work spans hardware security for embedded systems, privacy-preserving healthcare technologies, and IoT community-based security models. Notable contributions include developing the Secure Exam Environment (SEE) for online testing, cryptographic authentication methods, and quantum nonce mechanisms. He actively collaborates with the Trust Center to advance interdisciplinary security solutions. Research interests include: Cryptology, Digital Signatures, Information Security, Secure E-Business, and Cybersecurity in distributed systems. His projects often address practical challenges like functional safety in automotive control units and privacy in smart city technologies.