جست‌وجوی استاد و پژوهشگر

Timothy Tzen Vun Yapمشاهده پروفایل

استادیار

• System Identification
• Blockchain Technology
• Data Engineering
• +۳ مورد دیگر

Dr. Timothy Tzen Vun Yap is an Assistant Professor at the School of Mathematical & Computer Sciences, Heriot-Watt University Malaysia. Previously, he served as Senior Lecturer and Chair of the Center for Big Data and Blockchain Technologies at Multimedia University. He holds a PhD in Engineering from Multimedia University's System Identification and Control Group. His research focuses on blockchain technology, machine learning, data engineering, and system identification, with emphasis on consensus mechanisms, Sybil resistance in blockchain networks, and sentiment/aspect modeling. His research interests span technical domains including spyware detection, network security, educational data mining, and cryptocurrency efficiency. Notable contributions include advancements in Bitcoin block propagation, dataset curation for malware classification, and machine learning applications in intrusion detection systems. He has also explored the intersection of machine learning and healthcare, such as predictive modeling for breast cancer risk factors. His publications reflect a trend toward interdisciplinary solutions, blending cybersecurity with machine learning and applying data science to societal challenges like tourism and education. Collaborations often target practical implementations of theoretical models, such as optimizing blockchain protocols or improving real-time network traffic analysis. Though no formal awards are listed, his prolific output (59+ research outputs) and diverse collaborations underscore his active role in academic and applied research. His work contributes to UN Sustainable Development Goals through technological solutions addressing education equity, healthcare accessibility, and secure digital infrastructure.

David Wehlauمشاهده پروفایل

استاد

• Algebraic groups
• Invariant theory
• Commutative algebra
• +۴ مورد دیگر

David Wehlau is a Professor of Mathematics at the Royal Military College of Canada (RMC), with a joint affiliation at Queen's University. He holds a Ph.D. (Brandeis, 1989) and Master’s (Brandeis, 1984) in Mathematics, and an Honors BSc in Mathematics and Computer Science from Western University. His research focuses on algebraic groups, invariant theory, commutative algebra, and discrete mathematics, with notable contributions to modular invariant theory and cryptographic applications. He has advised numerous graduate students, including Asia Matthews (PhD 2015), Yinglin Wu (PhD 2009), and Emilie Dufresne (PhD 2008). His awards include the Cowan Prize (2012) for research and the RMC Teaching Excellence Award (2002). He has organized major conferences like the 2016 Algebraic Combinatorics and Group Actions conference and co-authored influential books such as Modular Invariant Theory . Wehlau collaborates extensively with researchers at Queen's University, including Eddy Campbell and Ivan Dimitrov, on algebraic geometry and representation theory. His work also bridges cryptography and finite geometry, with applications in error-correcting codes and secure communication systems.

• Image Processing
• Facial Expression Recognition
• Pattern Recognition
• +۳ مورد دیگر

Prof. Dr. Hasan Demirel is a faculty member in the Department of Electrical and Electronic Engineering at Eastern Mediterranean University (EMU). He holds a PhD in Electrical and Electronic Engineering from Imperial College London (2003), an MS in Computer Science from EMU (1993), and a BS in Electrical and Electronic Engineering from EMU (1992). His research focuses on image and video processing, facial expression recognition, pattern recognition, and biomedical applications. He has authored/co-authored over 100 peer-reviewed publications and supervised numerous PhD and MS students in areas such as Alzheimer's disease detection using MRI, SAR target recognition, and deep learning for emotion synthesis. Prof. Demirel's awards include multiple EMU Publication Citation Awards (2017–2021). He has led projects on multimodal emotion recognition and developed systems for real-time face recognition using robotics platforms like NAO humanoid robots. His work integrates machine learning techniques with medical imaging, remote sensing, and computer vision. He currently serves as a faculty member at EMU, contributing to academic programs and advising students in electrical engineering and biomedical engineering. His research labs focus on advancing AI-driven solutions for healthcare diagnostics and visual surveillance systems.

Christophe Hauserمشاهده پروفایل

استادیار

• Software Security
• Binary Program Analysis
• Reverse Engineering
• +۶ مورد دیگر

Christophe Hauser is an Assistant Professor at Dartmouth College and a member of the Institute for Security, Technology and Society (ISTS). His research focuses on software security, binary program analysis, reverse engineering, and vulnerability discovery across software and hardware systems. He integrates formal methods, machine learning, and program analysis to enhance cybersecurity defenses. Education: Joint PhD from CentraleSupélec (France) and Queensland University of Technology (Australia). Prior roles include Research Lead at USC Information Sciences Institute (USC-ISI) where he founded the Binary Analysis and Systems Security (BASS) group, and postdoctoral researcher at UC Santa Barbara’s Seclab. Research Interests: Binary code and firmware analysis, intrusion detection, usable security, privacy-preserving systems. Notable projects include BinPool (vulnerability dataset), BinHunter (vulnerability localization), and Harm-DoS (DoS mitigation). His work emphasizes practical applications such as automated fuzzing, decompilation analysis, and neuro-symbolic code search systems. He has contributed to open-source tools like angr and developed frameworks for firmware integrity validation (BootKeeper).

Anwar Hasanمشاهده پروفایل

استاد

• Cryptography
• Post-Quantum Cryptography
• Secure Multiparty Computation
• +۵ مورد دیگر

Anwar Hasan is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. He specializes in cryptography, post-quantum cryptography, and secure computation, with a focus on algorithm optimization, cryptographic hardware implementation, and energy efficiency. His work spans theoretical foundations and applied systems, including blockchain technology, fault-tolerant cryptosystems, and secure multiparty computation. His research interests emphasize developing quantum-resistant cryptographic protocols, improving efficiency in cryptographic algorithms (e.g., EdDSA signature verification, CSIDH optimization), and designing secure systems against adversarial attacks (e.g., poisoning in federated learning, covert adversary models). He also explores energy consumption analysis of cryptographic algorithms, particularly in the context of NIST PQC standards and elliptic curve-based systems. Recent work includes contributions to threshold cryptography (isogeny-based schemes), decentralized oracle networks (CountChain), and privacy-preserving blockchain applications (AdChain). His publications frequently address hardware-software co-design for cryptographic primitives, emphasizing both theoretical advancements and practical implementation challenges. Dr. Hasan’s research also extends to applied areas such as fraud detection systems, digital rights management using blockchain, and energy efficiency in embedded cryptographic systems. He collaborates on projects involving secure communication in cloud computing and resilient key management for mobile applications.

Ladan Tahvildariمشاهده پروفایل

استاد

• Software Engineering
• Cloud Computing
• Self-Adaptive Systems
• +۵ مورد دیگر

Ladan Tahvildari is a Full-time Professor in the David R. Cheriton School of Computer Science at the University of Waterloo. Her research focuses on software engineering, self-adaptive systems, cloud computing, and test case prioritization. She leads the Software Technologies Applied Research Laboratory (STAR Lab), emphasizing hands-on industry collaboration and practical software solutions. Her work spans over two decades, with notable contributions to adaptive software systems, runtime adaptation frameworks (GRAF), and cloud modeling (StratusML/Adoop). She has pioneered techniques for flaky test detection (FlaKat), spatiotemporal auto-scaling (STaleX), and POMDP-based uncertainty management for security systems. Key research areas include: Self-protecting software systems Component-based software evolution Defect detection and prioritization Autonomic computing decision models Cloud infrastructure optimization Her recent work bridges academia and industry through hands-on learning approaches and frameworks like Semeru Cloud Compiler for performance enhancement. She has served as workshop chair for ACSOS 2023 and contributed to IBM tool integration in educational curricula. Her lab focuses on transforming theoretical concepts into practical tools like StarMX for self-managing systems and ReLACK for VoIP steganography. Current efforts emphasize adaptive machine learning frameworks and scalable microservice architectures.

• Compiler Testing
• Program Analysis
• Static Binary Taint Analysis
• +۵ مورد دیگر

Chen Sun is an Adjunct Assistant Professor at the Department of Data and Systems Engineering, The University of Hong Kong. His research focuses on compiler testing, program analysis, static binary taint analysis, and software engineering methodologies. Notable areas include leveraging large language models (LLMs) for compiler testing baselines, probabilistic delta debugging, and enhancing program reduction techniques across multiple languages. Recent work addresses ransomware defense mechanisms, fuzzing countermeasures, and database management system (DBMS) bug discovery through configuration transformations. Research interests span compiler optimization, fault localization, cybersecurity, and algorithmic efficiency. His publications from 2023-2025 highlight trends in combining AI with traditional software engineering challenges, such as improving type inference for Java code and developing syntax-guided program reduction frameworks. Articles frequently address practical security concerns like protecting embedded devices from protocol fuzzing and mitigating memory leaks through sanitizer-based localization. No scientific awards are explicitly mentioned. Advising and grants sections remain underdeveloped in available data. Current affiliations emphasize academic-industrial collaboration through adjunct roles focused on cutting-edge software reliability and security research.

• Computer Security
• Mobile Security
• Network Security
• +۶ مورد دیگر

Georg Merzdovnik is a Lecturer at Vienna University of Technology (TU Wien) with a focus on computer security and privacy . His work spans binary rewriting, web privacy, IoT security, and Android application analysis, reflected in publications in top venues like ACM Computing Surveys and IEEE Euro S&P. He actively supervises student research projects in security-related domains. Primary Affiliation: Vienna University of Technology (TU Wien) Research Interests include: Binary rewriting and obfuscation techniques Web privacy mechanisms post-GDPR IoT device security in IPv6 networks Mobile application threat analysis Malware detection in Windows shellcodes Evaluation of tracker-blocking tools Thesis Supervisions (2012–2024) cover topics like IoT testbeds, Android intent firewalls, and secure messaging services.

• Computer Security
• Machine Learning
• Binary Analysis
• +۳ مورد دیگر

Michael Pucher is an External Lecturer in the Department of Logic and Computation at Technische Universität Wien. His research focuses on applying machine learning techniques to identify obfuscated function clones in binary code, with notable work published in 2021. He teaches courses such as 'Attacks and Defenses in Computer Security' (Course ID: 192.111). Education details are not explicitly provided, but his diploma thesis indicates academic engagement in computer security. No scientific awards or grants are mentioned in the text. He is affiliated with the university's informatics department and maintains a TISS profile (ID: 281901).

Davide Balzarottiمشاهده پروفایل

استاد

• Reverse Engineering
• Forensic Memory Analysis
• Advanced Malware Analysis
• +۳ مورد دیگر

Davide Balzarotti is a Professor and Head of the Digital Security Department at EURECOM. His expertise spans reverse engineering, forensic memory analysis, advanced malware analysis, and web security. He holds a PhD in Computer Engineering from the Polytechnic Institute of Milan (2006), followed by a postdoctoral fellowship at the University of California, Santa Barbara (2006–2008), and an HDR (Habilitation à Diriger des Recherches) from EURECOM in 2015. His research focuses on understanding malware behavior, improving forensic techniques, and enhancing web security through machine learning and static analysis. Notable contributions include frameworks like ModSec-Learn for boosting intrusion detection and PhishEye for monitoring phishing kits. He has received multiple awards, including the Best Paper Award at SAC 2017 and the ACM Europe Student Best Paper Award at CCS 2016. His work bridges academic research and practical cybersecurity challenges, addressing topics such as adversarial attacks, embedded system security, and evasion techniques in malware. His projects include evaluations of voting machine security (Project Everest) and collaborations to improve vulnerability detection in software. Education: PhD in Computer Engineering, Polytechnic Institute of Milan (2006) Postdoctoral Research at UCSB (2006–2008) HDR, EURECOM (2015) Awards: Best Paper Award (2017) ACM Europe Student Best Paper Award (2016) Best Student Paper Award (2013) Distinguished Paper Award (2011) Key Research Themes: Memory forensics Malware analysis Fuzzing and vulnerability discovery Web application security

Falk Herwigمشاهده پروفایل

استاد

• Stellar Hydrodynamics
• Nuclear Astrophysics
• Stellar Evolution
• +۳ مورد دیگر

Falk Herwig is a Professor and Director of the Astrophysical Research Center (ARC) at the University of Victoria's Department of Physics and Astronomy. His research focuses on stellar hydrodynamics, nucleosynthesis, and the origin of elements. He leads the Computational Stellar Astrophysics (CSA) group, which conducts large-scale 3D hydrodynamics simulations of stellar convection and nucleosynthesis processes. The CSA group collaborates with the NSF Physics Frontier Center Joint Institute for Nuclear Astrophysics (JINA-CEE) and the NuGrid collaboration, leveraging high-performance computing resources like the Niagara supercomputer. Herwig's work includes studying convection-nuclear burning interactions in massive and binary stars, nucleosynthesis in diverse astrophysical environments, and the chemical evolution of galaxies. He has pioneered methods to model stellar yields and integrate computational models with observational data. His research spans topics from core convection in massive stars to the physics of merging white dwarfs and nova explosions. Herwig has contributed significantly to advancing computational infrastructure for astrophysics, including the development of tools like SYGMA for galactic chemical evolution modeling. His projects are supported by Compute Canada and involve collaborations with international institutions. Recent research highlights include investigating the role of neutron capture processes in element formation and refining models of white dwarf cooling and stellar evolution.

Michal Ovádekمشاهده پروفایل

مدرس

• European Union Law
• Judicial Politics
• Quantitative Methods
• +۲ مورد دیگر

Dr. Michal Ovádek is a Lecturer in European Institutions, Politics, and Policy at University College London's Department of Political Science. Previously, he held postdoctoral roles at the University of Gothenburg and served as a political advisor in the European Parliament. His research focuses on the interplay of law and politics in the EU, judicial decision-making, and Central and Eastern European politics. He also contributes to quantitative methods, including R packages like nmfbin for binary data analysis. His work spans EU legal frameworks, judicial efficiency, and international litigation networks. Dr. Ovádek teaches European integration, quantitative methods, and judicial politics, and has organized workshops for doctoral students in law and humanities. Research interests include EU judicial politics, policy analysis, and methodological innovation. His publications explore topics like CJEU rulings, EU legislative processes, and data-driven legal research. He emphasizes interdisciplinary approaches, combining legal theory with computational tools.

Seth Gossageمشاهده پروفایل

پژوهشگر ارشد

• Stellar Evolution
• Binary Star Systems
• Stellar Rotation Modeling
• +۲ مورد دیگر

Seth Gossage is a Research Associate at the Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA) at Northwestern University, where he was promoted from CIERA postdoc in 2024 after three years (2021-2024). He collaborates extensively with Professor Vicky Kalogera on stellar evolution modeling and population synthesis. His research focuses on stellar evolution , particularly through computational modeling using MESA and development of the POSYDON population synthesis code. Key interests include: Effects of stellar rotation on observational signatures Binary star evolution pathways Convective dynamics in low-mass stars Progenitor systems for supernovae and gravitational wave sources Analysis of his 15 most recent publications (2023-2025) reveals a strong emphasis on binary interactions across metallicity ranges, with significant contributions to understanding stripped-envelope supernovae, double neutron star formation, and gamma-ray burst progenitors. His work bridges theoretical modeling with observational constraints from HST and spectroscopic surveys. Notable scientific contributions include: First-author paper on convective turnover times in low-mass stars (ApJ 2025) Key role in POSYDON v2 development for cosmological metallicity ranges Analysis of Be star-black hole binaries using LAMOST data Gossage mentors through CIERA's REU program (evidenced by student presentations at AAS meetings) and contributes to outreach initiatives. His current work involves developing grids of 1D stellar models to replicate population data while investigating rotational effects.

• Digital Communications
• Information Theory
• Signal Processing
• +۳ مورد دیگر

Prof. Amos Lapidoth is a Full Professor at ETH Zürich's Department of Information Technology and Electrical Engineering, leading the Signal and Information Processing Lab. He holds a B.A. (summa cum laude) in Mathematics and B.Sc. (summa cum laude) in Electrical Engineering from the Technion, along with an M.Sc. from Technion and Ph.D. from Stanford University. Previously, he was an Associate Professor at MIT and held the KDD Career Development Chair in Communications and Technology. His research focuses on Digital Communications and Information Theory , with contributions to coding theory, channel modeling, and signal processing. He has conducted R&D in wireless communications at the IDF Signal Corps Labs, earning two Creative Thinking Awards. His awards include the NSF CAREER Award and Rothschild Fellowship. Recent work explores state-dependent channels with helpers, feedback-assisted communication, and identification over noisy channels. His lab develops theoretical frameworks for reliable communication in complex systems, with applications in coding, modulation, and network design. Labs/Teams: Head of Signal and Information Processing Lab at ETH Zurich Key Contributions: Pioneering work on helper channels, zero-error capacity, and Rényi entropy applications

• Theoretical Astrophysics
• Gravitational Physics
• Numerical Relativity
• +۴ مورد دیگر

Nils Vu is a Sherman Fairchild Postdoctoral Scholar Research Associate in Theoretical Astrophysics at the California Institute of Technology (Caltech), working within the Division of Physics, Mathematics and Astronomy. His research focuses on theoretical astrophysics, gravitational physics, and numerical relativity, with particular expertise in black hole physics and gravitational waves. His research interests include: Theoretical modeling of black hole mergers and gravitational wave emissions Numerical relativity techniques for simulating strong-field gravity Gravitational wave memory effects and their detection Black hole spectroscopy through ringdown analysis Development of computational methods for relativistic astrophysics Applications to gravitational wave astronomy and data analysis Dr. Vu's recent work demonstrates significant contributions to numerical relativity, particularly in developing high-precision models for binary black hole systems. His research bridges theoretical physics with practical applications for gravitational wave observatories like LIGO and future missions like LISA. He has made notable contributions to the SpECTRE numerical relativity code and the SXS Collaboration's catalog of binary black hole simulations. His publications reveal a focus on horizon tracking in black hole simulations, quantum gravity signatures in gravitational wave memory, and advanced computational techniques for analyzing quasinormal modes. His work often addresses fundamental challenges in numerical relativity while maintaining relevance to observational gravitational wave astronomy. As a Sherman Fairchild Postdoctoral Scholar, Dr. Vu is part of Caltech's prestigious research program supporting exceptional early-career scientists in theoretical and experimental physics.