جست‌وجوی استاد و پژوهشگر

Alasdair B R Stewartمشاهده پروفایل

مدرس

• Social Policy
• Welfare Conditionality
• Mental Health Policy
• +۵ مورد دیگر

Dr Alasdair B R Stewart is a Lecturer in Social and Public Policy at the University of Glasgow's School of Social and Political Sciences. He holds dual roles as a Research Fellow and Data Lead at the GCRF Centre for Sustainable, Healthy and Learning Cities and Neighbourhoods (SHLC), and Co-Investigator for a Health Foundation-funded project examining welfare conditionality's impact on mental health. His research focuses on how large-scale social processes shape inequality, with particular attention to homelessness, welfare systems, and open-source research tools like PythiaQDA. Affiliations: GCRF SHLC, University of Glasgow's School of Social and Political Sciences Education: Not explicitly stated in provided text Stewart’s work bridges post-philosophical sociology with empirical research, critiquing proprietary qualitative analysis software and advocating for open science. His projects frequently address the intersection of welfare policies, mental health, and social security. He co-developed PythiaQDA, an open-source QDA tool designed to democratize qualitative research. His recent articles analyze Universal Credit's impact on mental health claimants, punitive welfare sanctions, and EU migrant welfare rights. Key findings emphasize systemic invalidation of mental health struggles within welfare systems and the need for policy reforms. Grants & Funding: Health Foundation, GCRF, Joseph Rowntree Foundation Supervision: Advises student Faith Ougham Stewart is actively involved in the Theory Reading Group at the University of Glasgow, exploring themes like 'The Body and Emotions' through transdisciplinary lenses. He also maintains blogs ( Constellations ) for open academic discourse.

Guanhong Taoمشاهده پروفایل

استادیار

• AI Security
• Machine Learning Security
• Adversarial Generative AI
• +۳ مورد دیگر

Guanhong Tao is an Assistant Professor at the Kahlert School of Computing, University of Utah. His research focuses on the security and safety of AI-enabled systems, particularly addressing adversarial attacks on machine learning models and large language models (LLMs). He has received notable awards, including the NVIDIA Academic Grant Award (2025) and the Maurice H. Halstead Memorial Award (2023). Educational Background: He earned his Ph.D. in Computer Science from Purdue University under Dr. Xiangyu Zhang’s supervision. His work spans adversarial generative AI, LLM agent security, and machine learning for security applications. Research Interests: Tao’s research emphasizes securing AI systems against adversarial threats, including backdoor attacks, alignment loss in LLMs, and privacy-preserving techniques. His projects have been published in top venues like IEEE S&P, USENIX Security, and NeurIPS. Recent Contributions: Key publications include 'Alleviating the Fear of Losing Alignment in LLM Fine-tuning' (S&P 2025) and 'BAIT: Large Language Model Backdoor Scanning' (S&P 2025). His work often bridges cybersecurity and machine learning, addressing real-world vulnerabilities in AI systems. Grants & Awards: In addition to his NVIDIA grant, Tao has received the ACM SIGPLAN Distinguished Paper Award (2019) and multiple best-paper recognitions. His research is funded by leading industry and academic partnerships. Advising & Teaching: He advises students like Shih-Chieh Dai and co-advises Kang Yang (with Dr. Jun Xu). He teaches courses such as 'Machine Learning Security' at the University of Utah and has guest-lectured at institutions like Purdue and Rutgers. Professional Service: Tao serves on program committees for top conferences, including IEEE S&P, ACM CCS, NeurIPS, and CVPR. He chairs workshops like BANDS (ICLR) and AISCC (NDSS), fostering collaborative research in AI security.

Vahid Yazdanpanahمشاهده پروفایل

استادیار

• Multiagent Systems
• Artificial Intelligence
• Responsibility of AI Systems
• +۳ مورد دیگر

Vahid Yazdanpanah is an Assistant Professor (Lecturer) of Computer Science at the University of Southampton and a Visiting Lecturer at the University of Twente. He holds a PhD from the University of Twente (2019), an MSc in Artificial Intelligence from Utrecht University (2015), and an MBA from the University of Greenwich (2012). His research focuses on multiagent systems, AI responsibility, and circular economy applications. He leads the Agents, Interaction and Complexity (AIC) research group and is an RRI Champion for the UKRI CDT in AI for Sustainability (SustAI). Research interests include agent-based computing, formal logics for multiagent decision-making, and socio-technical systems. Notable awards include the Best Paper Award at PRIMA 2016 and recognition at AAMAS 2021. He teaches courses such as COMP2211 (Software Engineering) and supervises PhD students in AI and sustainability. Active projects include the ARGOS (AI Resilience Governance) and AutoTrust (Internet of Vehicles) initiatives. He has served on program committees for AAAI, IJCAI, and AAMAS, and reviews for journals like AI & Society and Annals of Operations Research. His work bridges technical AI advancements with ethical, legal, and societal challenges in responsible AI deployment.

Baishakhi Rayمشاهده پروفایل

دانشیار

• Software Engineering
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Baishakhi Ray is an Associate Professor at Columbia University, specializing in improving software reliability and developers' productivity for both traditional and AI-driven systems. She leads the ARiSE Lab, focusing on interdisciplinary research at the intersection of software engineering and artificial intelligence. Her research interests include software testing for AI systems, adversarial robustness, automated testing of autonomous systems, and leveraging AI techniques such as neural networks for dynamic analysis and fuzzing. Notable projects include DeepTest for autonomous car testing and NEUZZ for efficient fuzzing. Awards: VMware Early Career Faculty Award (2020), IBM Faculty Award (2019), NSF CAREER Award (2019), and multiple best paper awards including EAPLS FASE (2020) and ACM Distinguished Papers (FSE 2017, MSR 2017). Grants: NSF CAREER grant (2019-2024) for deep learning testing, NSF grants for workshops and security bug detection, and collaborative grants on persistent memory and SSL/TLS implementations. Her recent work emphasizes advancing code generation with large language models (LLMs), evaluating model robustness under data contamination, and developing tools like CodeSense and CrashFixer for code semantics and kernel debugging. The ARiSE Lab also explores causal performance debugging and transfer learning for configurable systems.

• Software Engineering
• Industrial Automation
• Cloud Computing
• +۷ مورد دیگر

David Hästbacka is an Associate Professor (tenure track) at the Department of Computing Sciences, Faculty of Information Technology and Communication Sciences at Tampere University. His research focuses on software engineering, industrial automation, and energy systems, emphasizing system architecture, interoperability frameworks, and dependable IoT solutions. He leads a research group exploring edge and cloud computing, semantic integration, and smart energy systems. Education & Professional Background : While specific educational details are not provided, his academic career includes roles such as Postdoctoral Researcher in the SEMIS project (2017-2020) and extensive involvement in EU-funded initiatives like COCOP (EU H2020) and Horizon Europe projects. Research Projects : Active in high-impact projects like Hedge-IoT (Horizon Europe, 2024-2027), TwinfFlow (Business Finland), and TRINEFLEX (Horizon Europe), with a focus on industrial automation, distributed systems, and energy grids. Past projects include FEMMa (Business Finland), DisMa (Academy of Finland), and Arrowhead (ECSEL). Teaching & Supervision : Specializes in Web/Cloud architectures, IoT systems, and dependable automation technologies. Supervises students in topics like edge computing frameworks and MLOps pipelines. Technical Contributions : Develops frameworks for industrial interoperability (e.g., OPC UA PubSub integration), edge-cloud toolchains, and MLOps methodologies. His work addresses challenges in microservices, Kubernetes distributions, and semantic data integration. Labs & Teams : Leads a research group advancing automation technologies through interdisciplinary collaboration, with partnerships in industry and academia to bridge theory and practice in smart systems.

Joseph Alejandro Gallego Mejiaمشاهده پروفایل

عضو هیئت علمی

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۱۲ مورد دیگر

Joseph Alejandro Gallego Mejia is an Assistant Teaching Professor in the Department of Computer Science at Drexel University's College of Computing and Informatics. He holds a PhD with meritorious distinction in Systems and Computing Engineering from the National University of Colombia, along with a Master’s and dual Bachelor’s degrees in Systems and Computing Engineering and Industrial Engineering. PhD in Systems and Computing Engineering, National University of Colombia (Meritorious Distinction) Master of Systems and Computing Engineering, National University of Colombia Bachelor of Engineering in Systems and Computing Engineering, National University of Colombia Bachelor of Engineering in Industrial Engineering, National University of Colombia His research focuses on artificial intelligence, machine learning, computer vision, quantum machine learning, natural language processing, and cybersecurity. He explores robustness estimation, anomaly detection, incremental learning, and scalable software architectures for AI systems. His work bridges theoretical foundations and practical applications in health, remote sensing, and edge computing. The recent publications reflect a strong trend in interdisciplinary AI research, combining machine learning with quantum computing, cybersecurity, and natural language understanding. His work spans domains such as satellite imagery analysis, medical diagnostics, IoT security, and conversational AI, demonstrating a commitment to scalable and robust intelligent systems. Keywords across publications include Computer Science, Machine Learning, Quantum Computing, and Cybersecurity, with subfields ranging from adversarial robustness to hybrid quantum-classical models. Scientific distinctions include: PhD with meritorious distinction, National University of Colombia Postdoctoral fellow, Frontier Development Lab (Trillium), supported by NASA and ESA He has served as a reviewer for top-tier journals and conferences including Neurocomputing, IEEE Access, Radioscience, NeurIPS, and NLDL. Though no formal grants are listed, his postdoc was funded by NASA and ESA, indicating significant external support. He teaches courses in programming, data science, machine learning, deep learning, NLP, and software engineering. He founded the tech company Sammu and mentors students through instruction and research supervision. He is actively involved in research and teaching, contributing to innovative programs in AI and computing education. His lab and team affiliations are not explicitly stated, but his work suggests collaboration with AI, quantum computing, and cybersecurity research groups.

Jedidiah Crandallمشاهده پروفایل

دانشیار

• Internet Security
• Censorship Resistance
• Network Security
• +۳ مورد دیگر

Jedidiah Crandall is an Associate Professor at Arizona State University's School of Computing and Augmented Intelligence, with an affiliation to the Biodesign Center for Biocomputing, Security and Society. His research focuses on Internet censorship, network security, and privacy-preserving technologies. Crandall collaborates with journalists and activists to expose surveillance mechanisms, particularly in politically sensitive regions like Russia and China. His work includes analyzing VPN vulnerabilities , decentralized censorship systems , and cross-border data flows . He teaches advanced courses in computer network security and advises graduate students on thesis/dissertation research. Research trends in his publications emphasize measuring state-level information control , attack vectors in modern networks , and secure communication technologies . Notable work includes TSPU: Russia's censorship infrastructure and Hidden Links: Analyzing Secret Families of VPN Apps . Crandall's teaching spans courses like Advanced Computer Network Security and Applied Cryptography , reflecting his commitment to preparing the next generation of security professionals. His Censored Planet project tracks global Internet censorship patterns through large-scale measurements.

• Machine Learning
• Deep Learning
• Anomaly Detection
• +۵ مورد دیگر

Peter Karsmakers serves as Associate Professor at KU Leuven's Department of Computer Science within the Faculty of Engineering Technology, based at the Geel Campus. He coordinates the Declarative Languages and Artificial Intelligence (DTAI) research group and holds leadership roles including coordinator of Research and Education for Computer Science across Geel and Diepenbeek Campuses. Karsmakers earned his PhD in Engineering Science in May 2010, focusing on kernel-based learning algorithms for sparse modeling and efficient predictions from large datasets. His doctoral work established foundations for his current research trajectory in resource-constrained machine learning systems. His research integrates machine learning with signal processing for real-time sensor data interpretation, specializing in anomaly detection from acoustic, radar, and accelerometer signals on embedded devices. Current projects address industrial condition monitoring, elderly care systems, and livestock facility monitoring through three main tracks: acoustic monitoring (e.g., SINS, WATCHDOG), radar-based systems (e.g., FARADAY, NextPerception), and smart electronics for power converters. Recent publications demonstrate strong trends in constraint-guided deep learning architectures for industrial applications, cross-environment robustness in sensor systems, and domain-knowledge integration to reduce data requirements. His work consistently bridges theoretical machine learning with practical implementations in resource-constrained environments. No scientific awards or fellowships were mentioned in the provided materials. Karsmakers supervises over 10 master's theses annually and coordinates a research team of 10 PhD students and a post-doc within DTAI-ADVISE. He has secured approximately 2.3 million euros in funding through VLAIO, EU-ECSEL, and bilateral industry contracts, including 10 active projects such as AutoEdgeML (2024-2028) and Fault Tolerant Neural Networks for Space Applications (2024-2027). He leads the DTAI-ADVISE research group focused on developing software that attaches semantics to sensor data on resource-constrained devices. The team operates across multiple campuses with specialized labs for acoustic monitoring (Geel), radar-based systems (in collaboration with ESAT-TELEMIC), and smart electronics (with Electrical Engineering department), maintaining strong industry partnerships with companies in healthcare, manufacturing, and agriculture sectors.

Seongkyoon Jeongمشاهده پروفایل

استادیار

• Digital Supply Chain
• Cybersecurity
• Sustainable Operations
• +۳ مورد دیگر

Seongkyoon Jeong is an Assistant Professor of Supply Chain Management at the Haslam College of Business , University of Tennessee, Knoxville. His research addresses contemporary challenges in digital supply chains, cybersecurity risks, and sustainable operations. PhD (2022) - Supply Chain Management, Arizona State University MSc (2016) - Management, Georgia Institute of Technology MSc (2009) - Technology Management, Economics and Policy, Seoul National University BSc (2007) - Naval Architecture and Ocean Engineering, Seoul National University Jeong's work bridges supply chain security and sustainability , with recent publications examining cyberattack dynamics , epidemic-driven demand , and technology convergence . His 2018-2025 publications reveal a trajectory from R&D collaboration to digital transformation in supply chains. Scientific Awards Jack Meredith Best Paper Honorable Mention (JOM 2023) Arizona State University Outstanding Research Award (2022) Korea Management Association Consulting Excellence Award (2018) KIPO Director's Research Award (2016) Korea Institute for Industrial Economics and Trade Best Project (2013) Korea Inno-Skill Grand Prize (2010) Previously at Korea Institute of Machinery and Materials, Jeong contributed to interorganizational R&D before focusing on supply chain dynamics. His media contributions to Supply Chain Management Review and Supply Chain Dive highlight global cybersecurity risks and semiconductor production challenges .

• Cybersecurity
• Cyber-Physical Systems
• Industrial Control Systems
• +۴ مورد دیگر

Andreas Ekelhart is a Researcher at TU Wien's Department of Information and Software Engineering. His work focuses on cybersecurity, cyber-physical systems, and industrial control systems. He specializes in developing frameworks like SLOGERT for automated log analysis and Kyrstal for attack discovery using knowledge graphs. His research also explores digital twin technology for threat detection and semantic web applications in machine learning systems. Key contributions include the VloGraph framework for distributed security log analysis and the QualSec approach for automated security risk identification in production systems. He collaborates on standards like AutomationML and emphasizes privacy-preserving data analysis through semantic architectures.

• Seismology
• Marine geophysics
• Lithosphere-asthenosphere boundary
• +۴ مورد دیگر

Dr. Catherine Rychert is an Associate Professor in the Department of Geology and Geophysics at the University of Southampton, where she conducts cutting-edge research in seismology and marine geophysics. She is a member of both the Geology and Geophysics research group and the Southampton Marine and Maritime Institute, contributing significantly to our understanding of Earth's interior structure and dynamics through advanced seismic imaging techniques. Her research focuses on several key areas: Seismic imaging of lithosphere-asthenosphere boundary Subduction zone dynamics and slab structure Continental rifting processes Seafloor spreading mechanisms Mantle flow patterns and upwellings Development of novel seismic sensing technologies Dr. Rychert's recent publications (2023-2025) demonstrate a strong focus on applying advanced seismic techniques across diverse tectonic settings including subduction zones (Lesser Antilles, Cascadia, Hikurangi), mid-ocean ridges (Mid-Atlantic Ridge), and continental rift systems (East African Rift). A notable trend is her increasing use of distributed acoustic sensing technology for both terrestrial and planetary applications, showing interdisciplinary reach beyond traditional Earth science. Dr. Rychert actively supervises PhD students, including William Arnold Buffett working on the INSPIRE project. She has secured significant research funding from diverse sources including the European Union (EURO-LAB project), National Geographic Society, and Natural Environment Research Council (NERC). Her collaborative network includes Dr. Nicholas Harmon and Professor Derek Keir, with whom she frequently publishes. Her research team conducts fieldwork and data analysis focused on understanding fundamental Earth structure and processes through innovative seismic methodologies, contributing to both theoretical understanding and practical applications in hazard assessment and resource exploration.

• Computer Security
• Cryptography
• Distributed Systems
• +۳ مورد دیگر

Nickolai Zeldovich is the Joan and Irwin M. Jacobs Professor of Electrical Engineering and Computer Science at MIT, and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL). He received his PhD from Stanford University in 2008 and focuses on building practical secure systems, including encrypted databases, undefined behavior detection tools, formally verified file systems, and cryptocurrency protocols. His work spans both theoretical and applied aspects of computer security and distributed systems. Research interests include: Secure system design Distributed consensus mechanisms Formal verification of software/hardware Cryptographic protocols Privacy-preserving web technologies Publications & Verification Tools Recent work focuses on modular verification of complex systems, including: Shipwright (2025): Byzantine-fault-tolerant distributed system verification PoWER (2025): Crash consistency verification framework K2 Architecture (2023): Trustworthy hardware security modules Grove (2023): Separation-logic-based verification library Tiptoe (2023): Private web search protocols Major Awards Best paper award, ACM SOSP (2011, 2015, 2017) Sloan Research Fellowship (2010) NSF CAREER award (2011) MIT Jamieson Award for Teaching (2024) Active in multiple startup ventures including Algorand (cryptocurrency), MokaFive (virtualization), and PreVeil (end-to-end encryption).

Yongshan Dingمشاهده پروفایل

استادیار

• Quantum Computing
• Computer Architecture
• Quantum Algorithms
• +۴ مورد دیگر

Yongshan Ding is an Assistant Professor of Computer Science and Applied Physics at Yale University. He leads the Quantum Systems Lab (QSL) and directs Yale's Quantum Science and Engineering Certificate program. Affiliated with the Yale Quantum Institute (YQI) and Computer Systems Lab (CSL), his research focuses on quantum computing systems spanning algorithms, architecture, and hardware/software co-design. Dr. Ding earned his Ph.D. from the University of Chicago and a B.Sc. from Carnegie Mellon University. He has received prestigious awards including the Siebel Scholarship (2020) and William Rainey Harper Dissertation Fellowship (2020). Research Interests: Quantum computing architectures, noise-resilient quantum algorithms, error correction methods, quantum compilation, hardware-software co-design, and NISQ system optimization. Editorial Roles: Editor at Quantum journal and Associate Editor at ACM Transactions on Quantum Computing . Labs: Founder of Yale's Quantum Systems Lab (QSL) and contributor to the Computer Systems Lab (CSL). Awards: Siebel Scholarship (2020) William Rainey Harper Dissertation Fellowship (2020) QCE Best Paper Award (2024) IEEE Micro Top Picks Honorable Mention (2023, 2020) IBM Q Best Paper Award, First Prize (2020) Mathematics Competition Runner Up (2016)

Karthik Dantuمشاهده پروفایل

دانشیار

• Mobile Sensor Networks
• Robot Networks
• Networked Embedded Systems
• +۸ مورد دیگر

Karthik Dantu is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, State University of New York, within the School of Engineering and Applied Sciences. His research focuses on mobile sensor networks, robot networks, networked embedded systems, mobile computing, wireless networks, and embedded operating systems. He leads the Distributed Robotics and Networked Embedded Sensing (DRONES) Lab and has received significant funding including an NSF CAREER Award. Dr. Dantu's educational background includes: PhD in Computer Science from University of Southern California (2009) BE in Computer Science from Sri Jayachamarajendra College of Engineering (1999) His research interests center on algorithmic and systems challenges in Edge Computing Systems, with particular focus on enabling seamless vision sensing in cloud-edge environments. Dantu's work bridges mobile systems and robotics, developing novel approaches for UAV software, visual SLAM, and distributed sensing. His research addresses critical challenges in resource-constrained environments, security, and real-time performance for mobile and robotic systems, with emphasis on practical implementations that solve real-world problems in autonomous systems. Dr. Dantu's publication record shows a strong trajectory in mobile systems and robotics research, with increasing focus on edge computing applications for visual sensing. His recent work demonstrates expertise in adapting visual SLAM to edge environments, securing mobile systems through technologies like Rushmore, and developing novel approaches for UAV software reliability and depth sensing. The research spans theoretical algorithms and practical system implementations, with particular strength in bringing academic research to practical applications in robotics and mobile computing. Dr. Dantu has received several scientific honors: NSF CAREER Award on Enabling Seamless Vision Sensing in Cloud-Edge Systems Outstanding service award from the Office of International Services NSF Travel Grant for SenSys 2005 Conference Travel Grant for SIGCOMM 2002 As an advisor, Dr. Dantu has mentored numerous PhD students to completion, with graduates now working at companies like Samsung Research and Zoox Inc., or continuing academic careers as Assistant Professors. His research is supported by substantial grants including a DARPA OFFSET Sprint 4 award ($470k), an NSF CAREER award ($550k), and multiple NSF collaborative grants totaling over $1.5 million. He serves on numerous conference committees including Mobicom, MobiSys, and ICRA, demonstrating leadership in the mobile systems and robotics research communities. Dr. Dantu leads the Distributed Robotics and Networked Embedded Sensing (DRONES) Lab at UB, which focuses on developing algorithms and systems for mobile sensor networks, robot networks, and embedded sensing applications. The lab's work spans theoretical foundations to practical implementations, with particular expertise in UAV systems, visual SLAM, and edge computing for robotics, maintaining strong collaborations with industry partners and other academic institutions to advance the state of the art in mobile and robotic systems.

Xueqiang (Brandon) Wangمشاهده پروفایل

استادیار

• Software Supply Chain Security
• Mobile and IoT Systems Security
• Cybercrime Analysis
• +۳ مورد دیگر

Xueqiang (Brandon) Wang is an Assistant Professor of Computer Science at the University of Central Florida (UCF), where he is affiliated with the Cyber Security and Privacy Cluster. He leads the Security and PRIvacy for smarT systems (SPIRIT) lab, focusing on technical solutions for security and privacy threats in real-world systems. Education Ph.D. in Computer Science, Indiana University Bloomington (2021) Master’s in Computer Science, IIE CAS (2015) Bachelor’s in Computer Science, USTC (2012) Research Interests Security and privacy compliance for software supply chains Mobile and IoT systems security Cybercrime analysis Vulnerability discovery and exploitation Automated security analysis and data-driven mitigation strategies Labs & Teams Lead the SPIRIT Lab at UCF, specializing in security and privacy for smart systems.