جست‌وجوی استاد و پژوهشگر

Mohd. Tasleem Khanمشاهده پروفایل

استادیار

• Machine Learning/Artificial Intelligence
• Signal Processing
• Communication Systems
• +۴ مورد دیگر

Dr. Mohd. Tasleem Khan is an Assistant Professor at the Institute of Sensors, Signals, and Systems (ISSS), School of Engineering and Physical Sciences (EPS), Heriot-Watt University. Previously, he held roles as Principal Engineer at TSMC (2019), Assistant Professor at IIT Dhanbad (2020–2021), Research Consultant at KAUST (2020–2021), and Postdoctoral Researcher at Linköping University (2021–2024). He earned his Ph.D. in VLSI for signal processing and communication systems from IIT Guwahati (2019). His research focuses on Machine Learning/AI, Signal Processing, and Communication Systems, with expertise in VLSI architectures. Key contributions include energy-efficient designs for neural networks, adaptive filtering algorithms, and 6G systems. His work bridges theoretical algorithms with hardware implementation, emphasizing low-power and high-throughput solutions. Publications span circuits, systems, and interdisciplinary areas like biochemistry, showcasing his interdisciplinary approach. He has contributed to advancements in distributed arithmetic-based architectures, LMS filters, and FPGA implementations. Current affiliations include the Microwaves and Antenna Engineering Group at Heriot-Watt University, a global leader in wireless systems research.

• Artificial Intelligence
• Machine Learning
• Social Network Analysis
• +۴ مورد دیگر

Andreas Kaltenbrunner is a Part-Time Lecturer at the Universitat Pompeu Fabra (UPF) in Barcelona, specializing in Data Driven Social Analytics and Information Retrieval. He serves as Director of Research on AI and Data Science at IN3 - UOC R&I and is an Affiliate Researcher at ISI Turin, Italy. His research focuses on computational social science, user behavior analysis, and applications of AI/ML in social media and network dynamics. Key interests include large language models (LLMs), personality assessment simulations, and digital epidemiology. His work bridges theoretical frameworks with practical applications, such as predicting urban mobility patterns and evaluating AI systems’ performance in political contexts. He collaborates with institutions like UNICEF and the ISI Foundation, contributing to projects on data-driven decision-making and social impact. His interdisciplinary approach integrates network science, computational methods, and socio-cultural analysis. Recent publications highlight innovations in LLM validation, cross-lingual Wikipedia reliability modeling, and climate-related forecasting. While no explicit awards are listed, his prolific output reflects sustained contributions to computational social science and AI ethics.

• Static Analysis
• Logic Programming
• Program Verification
• +۴ مورد دیگر

Manuel V. Hermenegildo is a Professor at the Universidad Politécnica de Madrid, Spain. He is a prominent researcher in the field of programming languages and static analysis, with significant contributions to logic programming, program verification, and formal methods. His work focuses on advancing static analysis techniques, compiler optimization, and energy-efficient computing. He has co-authored numerous papers and organized international conferences such as LOPSTR and SAS, demonstrating his leadership in academic and research communities. His research explores topics including abstract interpretation, runtime checking, and parallel logic programming systems. He is a key contributor to the Ciao Prolog system, emphasizing comprehensive tool integration and formal methods. His research interests span static analysis frameworks, program verification, resource usage analysis, and energy efficiency in computing. He has developed methodologies for optimizing program performance while ensuring correctness, with applications in both theoretical and applied domains. His work often bridges the gap between high-level program analysis and low-level hardware constraints, particularly in embedded systems. Recent trends in his publications include advancements in static cost analysis, dynamic inference of invariants, and tools for incremental assertion checking. His collaborations with institutions like the University of Copenhagen and the University of Kent reflect a global network in advancing computational logic and software engineering. He has been actively involved in academic service, including editorial roles for conference proceedings and journals. His contributions highlight a commitment to both foundational research and practical tools for the programming language community.

Antonio García Cabotمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Educational Technology
• Natural Language Processing
• +۵ مورد دیگر

Antonio García Cabot is an Associate Professor in the Department of Computer Science at the University of Alcalá. His research focuses on artificial intelligence, educational technology, natural language processing, and mobile computing. He leads the INTELIA research group (Interaction Technologies and Artificial Intelligence Lab) and previously contributed to the PMI group (Intelligent Mobile Platforms). He earned his Doctorate in Computer Science from the University of Alcalá in 2013 with a thesis titled *Propuesta de un sistema multi-agente para la adaptación de contenidos docentes a las competencias, contexto y dispositivo del usuario*. His work emphasizes accessibility in digital education, gamification in MOOCs, and software engineering innovations like automated code repair using LLMs. Research trends in his 2024-2025 publications include: Advancing AI applications in educational assessment (e.g., automated question generation, distractor design) Improving mobile app usability through gesture-based interfaces and sensor integration Developing large language model-based tools for vulnerability repair and teacher simulation analysis Systematic reviews on digital competence ecosystems and multilingual AI systems His contributions to open educational resources (OER) and accessible virtual campuses have been widely adopted in Latin America. Current research extends into embedded systems education and olfactory stimuli impacts on mobile app performance.

Olaf Landsiedelمشاهده پروفایل

استاد

• Distributed Systems
• Wireless Sensor Networks
• Peer-to-Peer Systems
• +۴ مورد دیگر

Olaf Landsiedel is a Full Professor and head of the Distributed Systems Group at Kiel University, where he leads research in distributed computing, wireless sensor networks, and peer-to-peer systems. He has been a key contributor to the field since joining COMSYS in 2006 and earning his PhD in 2010. His research interests center on enabling accurate, scalable, and energy-efficient network simulations and protocols. He focuses on bridging the gap between simulation and real-world deployment, improving timing accuracy, modeling power consumption, and designing robust communication for unstable wireless environments. His work emphasizes modularity, flexibility, and reliability in distributed systems. The 15 most recent publications reflect a strong trend toward enhancing simulation fidelity, addressing bursty wireless links, enabling dynamic software updates in sensor networks, and developing tools for realistic experimentation. His work spans both theoretical models and practical implementations, often validated through simulation frameworks and testbeds. Olaf Landsiedel has advised numerous students on topics ranging from routing protocols to modular communication frameworks and ontology design, primarily during his time at RWTH Aachen University. While no specific grants are mentioned, his sustained publication record suggests consistent research funding and collaborative projects. He leads the Distributed Systems Group, which conducts cutting-edge research in network simulation, protocol development, and sensor network reliability. The group's work includes tools like KleeNet for bug detection and Horizon for parallel simulation, indicating a strong focus on practical system building and validation.

• Cybersecurity
• Information Security
• Internet of Things
• +۱۲ مورد دیگر

Niels Alexander Nijdam is a Senior Lecturer and researcher at the University of Geneva, affiliated with the Centre Universitaire d'Informatique (CUI) and the Geneva School of Economics and Management (GSEM). He leads the Information Security group (I-Sec lab) under the Research Institute for Statistics and Information Science (RISIS), focusing on cutting-edge research in cybersecurity, privacy, and distributed systems. PhD in Computer Science, University of Geneva His research interests span cybersecurity, Internet of Things (IoT), autonomous vehicles, smart cities, medical imaging, and virtual reality. He has pioneered work in secure frameworks for connected vehicles, trusted computing in embedded systems, GDPR compliance in mobility, and human-centric security visualization. His recent publications reflect a strong focus on automotive cybersecurity, blockchain for IoT, and risk assessment methodologies. The trend in his recent work (2019–2023) shows a consistent emphasis on cybersecurity in emerging technologies, particularly in transportation and IoT domains, integrating technical security mechanisms with regulatory and human factors. His publications frequently involve collaboration with researchers like M. Benyahya, A. Collen, and T. Lenard. Dr. Nijdam has not been explicitly mentioned with any scientific awards or fellowships in the provided text. As a research leader and senior lecturer, he supervises and mentors students and researchers within the I-Sec lab, though specific advisees are not listed. He has led multiple research projects related to IoT security, autonomous shuttles, and blockchain applications. No specific grants are mentioned, but his extensive publication record suggests active research funding. He directs the Information Security group (I-Sec lab), a research team focused on cybersecurity challenges in distributed and embedded systems, particularly in smart cities and autonomous mobility. The lab engages in both theoretical and applied research, often in collaboration with industry and academic partners.

• Target Tracking
• Navigation
• SLAM
• +۴ مورد دیگر

Edmund Førland Brekke is a Professor at the Department of Technical Cybernetics, Norwegian University of Science and Technology (NTNU). He leads the Autosit and Autosight projects, and serves as a work package leader in the SFI Autoship center. His research focuses on target tracking, navigation, and SLAM, with applications in collision avoidance for unmanned vessels. He co-founded the company Zeabuz for marine surface autonomy solutions. PhD in Technical Cybernetics (NTNU, 2010) MSc in Industrial Mathematics (NTNU, 2005) Research Interests: Edmund specializes in theoretical foundations of multitarget tracking, integrating target tracking with navigation/SLAM, and applying these to autonomous maritime collision avoidance. His work addresses challenges in heavy-tailed clutter, sensor fusion, and situational awareness for autonomous ferries and river barges. Publications Trends: His recent work (2018–2022) emphasizes collision avoidance algorithms, sensor fusion, and SLAM for autonomous vessels. Key areas include maritime radar tracking, trajectory prediction using AIS data, and integration of visual/Lidar sensors for navigation. Guidance: He has supervised numerous PhD candidates on topics like digital twins, multi-sensor tracking, and risk assessment for autonomous ships, including graduates from 2014–2024. Projects: Active in Autoferry (autonomous ferries), Autobarge (river barges), and the ORCAS initiative. Collaborates with the SFI Autoship center.

• Smart Wireless Systems
• Internet of Things (IoT)
• Information Security
• +۸ مورد دیگر

Mohammad Derawi is a Professor in the Department of Electronic Systems at the Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU), Gjøvik campus. He leads the Smart Wireless Systems (SWS) research group and serves as the scientific leader of the IoT Lab at NTNU Gjøvik. Educational Background: PhD in Information Security from NISLab (Norway) and CASED (Germany) BSc and MSc in Informatics from DTU (Denmark) His research interests span smart wireless systems, Internet of Things (IoT), information security with a focus on biometric authentication, digital electronics, applied machine learning for activity recognition, and e-learning technologies. His work integrates cybersecurity, embedded systems, and data science to develop secure and intelligent IoT solutions for real-world applications. The recent publications highlight a strong trend in mmWave-based sensing for unmanned aerial systems, RF fingerprinting for secure identification, IoT security frameworks, and machine learning applications in education and human resource analytics. His research bridges theoretical innovation with practical implementation, particularly in smart cities, healthcare, and transportation. Scientific Awards and Recognition: Invitation to the Crown Prince and Princess's 50th birthday celebration, 2023 Study Quality Award, NTNU, 2017 Norway’s Youngest Professor Award, 2016 Denmark’s youngest M.Sc. engineering award, 2009 IEEE Commendation for Young Professionals Volunteer, 2011 Multiple best paper awards from IEEE, ACM, and Springer Mohammad Derawi has been involved in several funded research and development projects, including IoT Safetraffic (RFF Inland), Ambulance Drone (NTNU Vice-Rector), Wireless ECG (Innovation Norway), biometric handgun security (RFF Innlandet), and the EU Framework 7 TURBINE project. He mentors students and collaborates with international researchers, contributing significantly to both academic and applied domains. His leadership in the SWS group and IoT Lab fosters innovation in wireless and secure embedded systems. He is actively engaged in laboratory and team-based research, particularly through the Smart Wireless Systems group and the IoT Lab, focusing on developing secure, intelligent, and scalable solutions for next-generation wireless applications.

• Concurrency and Parallelism
• Real-time Systems
• Distributed Systems
• +۶ مورد دیگر

Lukasz (Luke) Ziarek serves as Associate Dean for Academic Affairs and Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo's School of Engineering and Applied Sciences. His work bridges theoretical computer science with practical systems engineering, focusing on real-time capabilities in distributed environments and safety-critical applications. His educational foundation includes a PhD in Computer Science from Purdue University (2011) and a BS in Computer Science from the University of Chicago (2003). Ziarek's research centers on formal verification of distributed protocols , real-time systems engineering , and mobile/embedded computing . He pioneers session type theory for IoT security, develops real-time variants of Android (RTDroid) and Standard ML (RTML), and investigates UAV software reliability. His work consistently addresses the tension between theoretical guarantees and practical system constraints in concurrency, timing, and security. Recent publications (2022-2025) reveal three dominant trajectories: formal methods for rate-based session types in IoT protocols, performance analysis of visual SLAM systems for robotics, and security vulnerabilities in embedded platforms like ARM TrustZone. These threads converge on ensuring correctness and timeliness in resource-constrained distributed systems. His scientific accolades include the IEEE Region One Technological Innovation Award (2023) and NSF CAREER Award (2018), reflecting dual excellence in research and education. IEEE Region One Technological Innovation (Academic) Award, 2023 President Emeritus and Mrs. Meyerson Award for Distinguished Undergraduate Teaching and Mentoring, 2022 NSF CAREER Award, 2018 SEAS Early Career Teacher of the Year, 2016 Halstead Award for Outstanding Research in Software Engineering, 2009 Intel Fellowship, 2008 GAANN Fellowship, 2004 Ziarek directs significant research initiatives including a $900K NSF UAV infrastructure project (as PI) and a $1.7M MRI grant for connected vehicle testing. His funding portfolio spans real-time systems, compiler design, and pocket-scale data management, emphasizing collaborative, interdisciplinary approaches to software reliability. CRI:CI-New UAV Infrastructure ($900K, PI 31%) NSF CAREER: Real-time Object-Oriented Systems ($500K, PI 100%) MRI: iCAVE2 Vehicle Testing ($1.7M, co-PI 14%) III: Just-in-Time Data Structures ($499K, co-PI 50%) II-EN: MLton Compiler Research ($606K, PI 63%) He leads an open-source ecosystem including RTDroid (real-time Android), Multi-MLton (parallel SML compiler), and BlueSeal (Android security analyzer), fostering community-driven advances in systems software.

• Integrated Circuits
• RF Circuit Design
• Low-Power Electronics
• +۳ مورد دیگر

Jean-Baptiste Bégueret is a researcher with extensive contributions to integrated circuits , RF design , and low-power electronics . His work spans analog , digital , and mixed-signal systems.

• Health Informatics
• Implementation Science
• Medical Informatics
• +۳ مورد دیگر

Sarah L Cutrona is a Professor at UMass Chan Medical School, affiliated with the T.H. Chan School of Medicine and Morningside Graduate School of Biomedical Sciences. She specializes in the Department of Population and Quantitative Health Sciences and the Division of Health Informatics and Implementation Science. Education: BA in English from Yale University MPH in Clinical Effectiveness from Harvard University School of Public Health MD from Columbia University Research Interests: Cutrona focuses on health informatics, implementation science, and medical informatics. Her work examines electronic health record (EHR) transitions, digital health interventions, tobacco cessation support tools, and health services research within the Veterans Health Administration (VHA). She investigates clinician-patient communication, implementation fidelity, and health equity in technology adoption. Scientific Contributions: Her 15 most recent publications (2023-2025) cover EHR implementation challenges, digital divide risk scores, cancer survivorship programs, and tobacco cessation monitoring. Key themes include health informatics, internal medicine, and implementation science with subfields like EHR usability, clinician burnout, patient engagement, and health equity. Collaborations: Cutrona works extensively with institutions including the Veterans Health Administration, Harvard, and Columbia. Her research spans clinical trials, mixed methods studies, and qualitative analyses of healthcare technology adoption.

• Robotics
• Internet Technologies
• Software Engineering
• +۳ مورد دیگر

Prof. Dr. Martina Lehser is a faculty member at the Saarland University of Applied Sciences in the Faculty of Engineering , specifically within the Department of Computer Science, Fundamentals, and Sensor Technology . She has held leadership roles in multiple research laboratories, including the Embedded Robotics Lab and the Communication Informatics Laboratory . Spokesperson for the Center for Digital Neurotechnologies Saar (CDNS) Scientific Director of the Chinese-German Institute @ htw saar (CDI) Her research focuses on robotics , internet technologies , sensor systems , and software engineering , with applications in industrial automation, mobile robotics, and web-based tools. She has supervised numerous Bachelor's and Master's theses on topics like embedded systems, cloud computing, and distributed networks. Current and former leadership roles include: Head of the Test Field Digitalization in Production @ htw saar (until 2023) Vice Dean of the Faculty of Engineering (2009–2018) International Representative, Computer Science Department (2010–2018) She actively engages in STEM projects and Internet workshops , educating students and parents on technical and safety aspects of digital systems.

• Functional Safety
• Functional Testing
• Microprocessor Testing
• +۹ مورد دیگر

Riccardo Cantoro is an Associate Professor in the Department of Control and Computer Science (DAUIN) at Politecnico di Torino, where he is a member of the College of Computer, Film and Mechatronics Engineering and the College of Mechanical, Aerospace and Automotive Engineering. He is affiliated with the CAD - Electronic CAD & Reliability Group and the CARS@PoliTO Interdepartmental Center for Automotive Research and Sustainable Mobility. His work bridges academic research and industrial applications through multiple commercially funded projects. Scientific Disciplinary Sector: IINF-05/A - Information Processing Systems ERC Sectors: PE7_4, PE6_2, PE6_11, PE6_12 His research focuses on functional safety, functional testing, and microprocessor testing, with a strong emphasis on embedded systems and reliability. He applies machine learning and formal methods to enhance test efficiency and system robustness, particularly in automotive and safety-critical domains. His work integrates computer-aided design, fault modeling, and resilience assessment in both hardware and AI systems. The recent publications highlight a trend toward data-efficient and intelligent testing methodologies, combining machine learning (e.g., TabPFN, active learning) with traditional electronic design automation. Topics include microcontroller performance screening, CNN resiliency, FeFET device testing, and system-level test optimization, reflecting a cohesive research agenda in trustworthy computing and hardware reliability. Scientific Awards: No awards explicitly mentioned in the provided texts. Advising and Grants: Dr. Cantoro supervises numerous PhD students in Computer and Systems Engineering, focusing on functional safety, test methodologies, and AI for CAD. He leads multiple industry-funded research projects, including collaborations with Infineon Technologies and Dana-TM4 Italia, on topics such as ATPG tools, speed monitor modeling, and power module reliability. His role as Scientific Manager/Head underscores his leadership in applied research and technology transfer. Labs and Teams: He is a core member of the CAD - Electronic CAD & Reliability Group (DAUIN) and contributes to the CARS@PoliTO center, fostering interdisciplinary research in automotive systems and sustainable mobility.

Blake Borenمشاهده پروفایل

پژوهشگر

• Marine Renewable Energy
• Wave Energy
• Tidal Energy
• +۶ مورد دیگر

Blake Boren serves as a Researcher IV in Model Engineering at the National Renewable Energy Laboratory (NREL), working within the Center for Energy Conversion and Storage Systems and the water power program. His research focuses on converting ocean energy into electricity and desalinated water through innovative engineering solutions. Education: PhD in Robotics from Oregon State University Master's degree from Oregon State University Bachelor's degree from Oregon State University Dr. Boren specializes in Marine Renewable Energy systems, with expertise spanning wave and tidal energy conversion, distributed embedded energy technologies (DEEC-Tec), and robotics applications. His work integrates dynamics, controls, embedded systems, and machine learning to develop transducer-based energy harvesting solutions, emphasizing empirical prototyping and instrumentation. Key research fingerprints include Power Converter Engineering (100%), Embedded Energy Engineering (55%), and Wave Energy Engineering (45%). Recent publications (2023-2024) reveal a concentrated focus on hyperelastic transducers and adaptive structures for marine energy conversion, demonstrating advancements in DEEC-Tec architectures and HASEL transducer applications. These works consistently address energy density optimization, fluid-structure interactions, and scalability challenges in ocean environments. Dr. Boren has no documented scientific awards. His collaborative research shows no formal advisee relationships, though he frequently partners with colleagues like Chamot and Niffenegger on NREL projects. He operates within NREL's water power program, contributing to the Center for Energy Conversion and Storage Systems through experimental validation of novel energy conversion concepts and transducer technologies for marine renewable energy applications.

• Bio-IT convergence
• Intelligent Transportation Systems
• Sensors
• +۵ مورد دیگر

Chan-Young Park is a Professor in the School of Software at Hallym University, South Korea. He holds a Ph.D. from the Korea Advanced Institute of Science and Technology (KAIST) and brings significant industry experience from his tenure at Samsung Electronics between 1991 and 1999. His academic career is centered on interdisciplinary research at the intersection of software, sensors, and biomedical applications. His research interests include Bio-IT convergence , intelligent transportation systems , and sensors , with a strong emphasis on practical implementations in healthcare and civil infrastructure. These interests are reflected in his recent work on real-time PCR systems, biochip development, and structural monitoring of concrete bridges using deep learning. The recent publications highlight a consistent trend in developing compact, intelligent, and sensor-based systems for biomedical diagnostics and infrastructure safety. His work frequently involves machine learning integration, signal detection, and miniaturized hardware, demonstrating a multidisciplinary approach across engineering and computer science domains. While no formal scientific awards are listed in the provided text, his sustained publication record in reputable journals such as Sensors and Applied Sciences indicates active research contributions. He collaborates extensively with colleagues at Hallym University and other institutions, suggesting a strong research network. There is no explicit mention of student advising or grant funding in the text, but his professorial role and publication output imply involvement in mentoring and research leadership. No specific lab or research team is named, but his work suggests affiliation with a research group focused on embedded systems, sensor technologies, and Bio-IT applications within the School of Software.