جست‌وجوی استاد و پژوهشگر

OLINDA NELLY CONDORI FERNANDEZمشاهده پروفایل

استادیار

• Software Engineering
• Sustainability Assessment
• Requirements Engineering
• +۴ مورد دیگر

Olinda Nelly Condori Fernández is an Assistant Professor at the Department of Electronics and Computing within the Higher Technical School of Engineering at the University of Seville. She holds a PhD in Computer Science from the Universitat Politècnica de València (2007), supervised by Dr. Oscar Pastor López and Dr. Silvia Mara Abrahao Gonzalez. Her research focuses on software sustainability , requirements engineering , and persuasive technology , with a particular emphasis on integrating sustainability into software design and developing emotion-aware systems for healthcare and workplace environments. Her work spans interdisciplinary collaborations, including the design of the Emobook app for dementia care and the HAPPYNESS framework for enhancing user experience through emotion-aware systems. She leads the Intelligent Systems Group (GSI) and contributes to the Center for Research in Intelligent Technologies (CITIUS) . Key research areas include sustainability assessment frameworks (SAF), requirements prioritization in software product lines, and applying machine learning to classify non-functional requirements in Spanish datasets. Condori Fernández has developed tools like SimRE for requirements similarity analysis and CoSTest for model-level validation. Her contributions address challenges in green software strategies, user-centric security perceptions, and stress detection via physiological data. She actively publishes in top venues like REFSQ and co-organizes workshops on sustainability and cyber-physical systems.

DAVID ENRIQUE LOSADA CARRILمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۴ مورد دیگر

David Enrique Losada Carril is a Professor at the Department of Electronics and Computing, within the Higher Technical School of Engineering at the Universidade de Santiago de Compostela. His research focuses on AI-driven solutions for mental health monitoring, misinformation detection, and healthcare informatics. He leads the Intelligent Systems Group (GSI) and collaborates with the Center for Research in Intelligent Technologies (CITIUS). His work integrates natural language processing, machine learning, and social media analysis to address challenges in early risk prediction, such as depression, eating disorders, and pathological gambling detection. He holds a PhD from the University of A Coruña (2001) with a thesis on logical models for information retrieval. His contributions span experimental IR methodologies, computational mental state assessment, and real-time social media monitoring tools like Social Minder and LudoTrack. He actively participates in CLEF eRisk campaigns, advancing early risk prediction systems through collaborative research. Key research themes include: (1) Developing AI models for mental health symptom analysis using social media data, (2) Evaluating large language models’ roles in health question answering and assessment, (3) Combating health misinformation via search engines and conversational AI. His work emphasizes ethical AI applications in healthcare and public health communication.

Michele Melchioriمشاهده پروفایل

دانشیار

• Information Systems
• Semantic Web Technologies
• Blockchain Integration
• +۷ مورد دیگر

Michele Melchiori is an associate professor at the Università degli Studi di Brescia (Italy) since 1998, specializing in systems for information processing. He holds a PhD in Information Engineering from the University of Brescia and a Master's in Computer Science from the University of Milan. His research focuses on information systems design, semantic-based services, blockchain integration, and smart city technologies. Notable contributions include frameworks for smart contract design, blockchain applications in agri-food supply chains, and IoT-driven solutions for construction quality assurance. His work bridges theoretical advancements with practical implementations, spanning projects funded by collaborative initiatives. Key areas include personalized data exploration using semantic web technologies, trust management in decentralized systems, and healthcare applications like food recommendation systems. He has authored over 80 publications, emphasizing interdisciplinary approaches to data management challenges. Melchiori frequently contributes to academic events such as the Italian Symposium on Advanced Database Systems. His research bridges technical innovations (e.g., blockchain) with societal needs (e.g., smart city infrastructure and post-pandemic healthcare models).

Laurent Pautetمشاهده پروفایل

استاد

• Real-Time Systems
• Critical Systems Design
• Embedded Systems
• +۷ مورد دیگر

Laurent Pautet is a Professor at Télécom Paris since 2005 and Head of the Autonomous Critical Embedded Systems (ACES) research team at the Information Processing and Communication Laboratory (LTCI). He holds a PhD in Computer Science from Télécom Paris (1993) and an HDR (2001) from Université Pierre et Marie Curie (UPMC). His research focuses on real-time systems, critical systems design, security, and model-based engineering. He leads the ACES team, which addresses challenges in concurrent systems, scheduling algorithms, and safety-critical applications. His academic background includes a PhD supervised by Dassault Electronics and an HDR emphasizing formal methods and distributed systems. His work spans real-time scheduling (e.g., mixed-criticality systems), embedded software reliability, and intrusion detection systems. He has contributed to tools like the Ocarina AADL tool suite and frameworks such as Flex-eWare for embedded distributed systems. Research interests also include cybersecurity threats to intrusion detection systems (IDS), motion control for autonomous vehicles, and application of mixed-criticality scheduling in AI-driven systems like Monte Carlo Tree Search. He actively supervises internships and theses on topics like renewable energy-aware real-time scheduling and 5G NR in SCADA systems. Pautet’s publications span journals like Journal of Systems Architecture and conferences such as RTSS and IEEE CSR. His work bridges theoretical foundations (e.g., linear programming for scheduling) with practical implementations in domains like aerospace and automotive systems.

Shengchao Qinمشاهده پروفایل

استاد

• Formal Methods
• Programming Languages
• Software Engineering
• +۳ مورد دیگر

Dr. Shengchao Qin is a Professor of Computer Science at Teesside University's School of Computing & Digital Technologies, specializing in formal methods and software verification. He holds a BSc and PhD from Peking University, with postdoctoral experience at the Singapore-MIT Alliance. As Associate Dean for Research & Innovation (2016-2019), he led strategic research initiatives. His research focuses on automated verification of software safety/security, program analysis, and cyber-physical systems. Major funded projects include EPSRC grants for resource analysis of embedded software (£403k) and inference mechanisms for separation logic domains (£213k). He actively contributes to academic service as Program Committee Chair for ICFEM/TASE conferences, steering committee member for formal methods symposiums, and editorial roles for IEEE Access and Science of Computer Programming. Collaborations span top institutions including National University of Singapore and Peking University. Research Supervision: Current PhD advisees: Chris Curry, Yang Liu, Colin Joy, Ndidi Ogbo Former supervisees: Zhang Zhang (PhD '20), Florin Craciun (Postdoc), Ryuta Arisaka (PhD '13)

Sadegh Soudjaniمشاهده پروفایل

پژوهشگر

• Cyber-Physical Systems
• Formal Verification
• Stochastic Hybrid Systems
• +۵ مورد دیگر

Sadegh Soudjani is currently a Senior Research Group Leader at the Max Planck Institute for Software Systems (MPI-SWS) since December 2023. Prior to this, he served as the director of the AMBER group and a Reader (full professor) in Cyber-Physical Systems at Newcastle University, United Kingdom. His research focuses on developing integrated environments for programming, verifying, and designing high-performance, scalable cyber-physical systems in uncertain physical environments. Education: BSc in Pure Mathematics BSc in Electrical Engineering MSc in Control Engineering PhD in Systems & Control Research Interests: Formal synthesis, abstraction, and verification of complex dynamical systems under probabilistic temporal specifications. Applications include energy networks, autonomous systems, smart grids, transportation systems, and systems biology. Projects: SymAware (€4 million EIC-funded), CodeCPS (EPSRC-funded), MoVeS, Safe-CPS, AMBI. His work bridges control theory and formal methods, with a focus on stochastic hybrid systems. Scientific Awards: EPSRC New Investigator Award (2021, £484k) DISC Best PhD Thesis Award (2015) QEST Best Paper Award (2018) Newcastle Teaching Award (2020) Best Repeatability Prize at IFAC ADHS'21 Advising & Grants: Supervised 4 PhD students jointly with Max Planck Institute and Ludwig Maximillian University. Secured €4 million for SymAware and €728k for 7 PhD studentships. Led collaborative projects with institutions like KTH, Uppsala, TU Eindhoven, Siemens, and Netherlands Aerospace Centre. Labs & Teams: Currently leads the AMBER group at MPI-SWS, previously directed AMBER group at Newcastle University. Organized international workshops including V2CPS, SNR, VARS, and ARCH (stochastic category).

Paarijaat Adityaمشاهده پروفایل

استاد

• Algorithms
• Theory & Logic
• Programming Languages & Verification
• +۴ مورد دیگر

Paarijaat Aditya is a faculty member at the Max Planck Institute for Software Systems (MPI-SWS) , focusing on interdisciplinary research at the intersection of theoretical computer science and applied systems. Their work spans algorithms, programming languages, security, and distributed systems , with a particular emphasis on serverless computing, federated learning, and privacy-preserving urban sensing. Research Areas : Machine Learning Security (e.g., model hijacking, federated learning) Serverless Computing (e.g., GPU sharing, high-performance frameworks) Privacy Engineering (e.g., urban sensing, image capture, mobile compliance) Distributed Systems (e.g., NFV, peer-assisted content delivery) Their publications reflect a trajectory of advancing scalable AI training, secure collaborative systems, and privacy-compliant infrastructures. Recent works address challenges in public cloud adaptability, while earlier contributions explore mobile privacy risks and secure resource management.

Hyunsook Doمشاهده پروفایل

دانشیار

• Software Engineering
• Software Quality
• Machine Learning Applications
• +۳ مورد دیگر

Hyunsook Do is an Associate Professor in Computer Science and Engineering at the University of North Texas, specializing in software quality, testing methodologies, and AI applications in software engineering. Her research develops innovative approaches for quality assurance in modern software systems. Research spans: Automated testing and debugging techniques AI/ML applications in software engineering Safety analysis for autonomous systems Quality metrics and bug detection Empirical software engineering studies Recent publications demonstrate strong focus on leveraging natural language processing, machine learning, and semantic analysis to improve software quality detection, bug triaging, and safety verification across diverse application domains including mobile apps and autonomous vehicles.

Heng Fanمشاهده پروفایل

استادیار

• Computer Vision
• Video Analysis
• Robotics
• +۲ مورد دیگر

Heng Fan is an Assistant Professor in the Department of Computer Science and Engineering at the University of North Texas, with affiliated faculty status in the Department of Data Science. He leads the LLaVi Lab and holds editorial positions at Pattern Recognition and serves as an Area Chair for major conferences including ICCV and NeurIPS. He earned his B.S. from Huazhong Agricultural University (2013) and Ph.D. from Stony Brook University (2021), advised by Professor Haibin Ling. His research focuses on: Computer vision, especially video analysis using vision-language integration Robotics with an emphasis on perception systems Medical image analysis for diagnostic applications Recent publications demonstrate strong emphasis on transformer architectures for spatio-temporal video understanding, 3D object detection in autonomous systems, and multimodal AI applications. Dominant themes include UAV tracking, video grounding, and privacy-preserving NLP, reflecting cross-disciplinary innovation. He actively recruits PhD/master's students for computer/robotic vision projects and leads the LLaVi Lab, focusing on cutting-edge perception systems.

Yan Huangمشاهده پروفایل

استاد

• Spatio-Temporal Databases
• Geo-Stream Data Processing
• Smart Transportation
• +۳ مورد دیگر

Yan Huang is a Regents Professor in the Department of Computer Science and Engineering at the University of North Texas (UNT). She holds ACM Distinguished Member and UNT Decker Scholar titles. Her roles include Associate Dean for Research and Graduate Studies (2016-2019), Interim Dean of the College of Engineering (2018), Senior Associate Dean (2019-2021), and Interim Chair of Computer Science and Engineering (2020-2021). She has served as a visiting scholar at Microsoft Research Asia and Fudan University. Education: B.S. in Computer Science from Peking University (1997) and Ph.D. in Computer Science from the University of Minnesota (2003). Research interests focus on spatio-temporal databases, geo-stream data processing, smart transportation, and location-based social networks. Her work is funded by NSF, DoD, Texas Department of Transportation, and Oak Ridge National Lab. Notable achievements include a $3.76M grant from the Army Research Lab (2023). Key awards include the Best Paper Award at IEEE IRI 2023 (student work) and recognition as a Regents Professor (2021). She advises multiple Ph.D. students and oversees a lab (DP F205).

Manuela Farinosiمشاهده پروفایل

دانشیار

• Digital Media Sociology
• Communicative Processes
• Participatory Culture
• +۲ مورد دیگر

Manuela Farinosi is Associate Professor in Sociology of Cultural and Communicative Processes at DMIF, University of Udine, and Director of NuMe Research Laboratory on New Media. Her research examines the social and cultural implications of digital media, communicative processes, and participatory practices across mediated and non-mediated contexts. Research interests focus on digital sociology, including internet studies, social media platforms, and the sociocultural dimensions of technology adoption. Recent work explores AI perceptions, influencer activism, digital inclusion, and pandemic impacts on social systems. Publications demonstrate consistent focus on technology-society interfaces, with recent articles examining generative AI in education, disability advocacy through social media, and community responses to emergencies. Research employs diverse methodologies including cluster analysis, action research, and cross-cultural studies. Current work addresses ethical AI implementation, digital activism, and participatory communication frameworks in crisis situations.

Dong Hyun Jeongمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Visual Analytics
• Information Visualization
• +۷ مورد دیگر

Dong Hyun Jeong is an Associate Professor in the Department of Computer Science at the University of the District of Columbia. His academic journey began with a Ph.D. in Computer Science from the University of North Carolina at Charlotte (2010), preceded by an M.S. and B.Eng. from Hallym University, South Korea (2001, 1999). Ph.D. in Computer Science, May 2010, University of North Carolina at Charlotte M.S. in Computer Science, August 2001, Hallym University B.Eng. in Computer Engineering, August 1999, Hallym University Jeong’s research focuses on Visual Analytics , Human-Computer Interaction (HCI) , and Big Data Analytics , with applications in cybersecurity, genomic data analysis, and climate modeling. His work integrates machine learning , cloud computing , and wavelet transforms to address challenges in network intrusion detection, rainfall prediction, and financial risk analysis. His publications highlight a trend toward interactive visual analytics tools like iPCA (Principal Component Analysis-based systems) and GVis (genomic data visualization). These projects emphasize user-driven analysis , uncertainty quantification , and cross-domain collaboration with institutions like UNC Charlotte and NIFA-funded teams. Service Excellence Award, University of the District of Columbia (2017) Teaching Excellence Award (2016) Exemplary Contribution Award (2011) Best Paper Award, Hawaii International Conference on System Sciences (2010) 2nd Best Graduate Student Poster Award, Applied Visualization Conference (2005) Jeong has secured grants from the U.S. Army Research Office , National Science Foundation (NSF) , and Korean Science and Engineering Foundation (KOSEF) , focusing on cloud-based intrusion detection , climate change computational infrastructure , and cybersecurity workforce development . He also leads the GVis and iPCA projects, which address scalable genomic visualization and PCA-based interactive analysis, respectively.

• Constraint Logic Programming
• Answer Set Programming (ASP)
• Stream Data Analysis
• +۳ مورد دیگر

Joaquín Arias is an Associate Professor at the Universidad Rey Juan Carlos (URJC) in Madrid, Spain, since 2025. He previously served as an Assistant Professor at URJC (2020–2025) and as a Pre-Doctoral Researcher at the IMDEA Software Institute (2013–2020). He holds a Ph.D. in Computer Science (2020), a Master of Science in Computer Science (2015), a Bachelor of Science in Computer Science (2014), and a Master of Architecture (2002), all from the Universidad Politécnica de Madrid (UPM). His research focuses on constraint logic programming, answer set programming (ASP), and their applications in stream data analysis, spatial reasoning, and legal reasoning systems. His main research interests include (Constraint) Logic Programming, TCLP, s(CASP), and value-aware systems. He has developed frameworks like Modular TCLP and ATCLP for constraint integration and aggregate computation. Notable projects include applying s(CASP) to legal reasoning (s(LAW)), BIM modeling, and automated conversational agents using LLMs and ASP. His work emphasizes explainable AI and ethical alignment in automated decision-making. Key contributions include the Automated Legal Reasoning with Discretion framework (2024), a socialbot leveraging LLMs and ASP (2024), and a legal reasoning system for administrative processes (2024). He has contributed to proceedings of the ICLP workshops and edited volumes for conferences like AAAI and CAEPIA. His academic awards include the Best Paper Prize at CAEPIA 2021. Collaborations include the University of Texas at Dallas (2017), Aalto University (2019), and IMDEA Software Institute. His teaching includes promoting logic programming in computer science curricula, as highlighted in his 2023 SIIE conference paper.

Zachary Sunbergمشاهده پروفایل

استادیار

• Aerospace autonomy
• Partially observable Markov decision processes (POMDPs)
• Game theory
• +۵ مورد دیگر

Zachary Sunberg is an Assistant Professor in the Ann and H.J. Smead Aerospace Engineering Sciences Department at the University of Colorado Boulder. He is affiliated with the Research and Engineering Center for Unmanned Vehicles (RECUV) and leads the Autonomous Decision and Control Lab (ADCL). His research focuses on artificial intelligence for autonomous systems, particularly in aerospace autonomy, decision-making under uncertainty (via POMDPs), and human-AI interaction. Sunberg holds a PhD from Stanford University (2018), an MS and BS from Texas A&M University (2013, 2011). His work spans algorithm development for autonomous vehicles, including safe and efficient driving, rotorcraft control, and game-theoretic planning. Notable contributions include the POMCP and POMCPOW algorithms for continuous POMDPs, and open-source frameworks like POMDPs.jl. He has received a NSF CAREER Award (2024) and a NSF Graduate Fellowship (2012). Academic roles include mentoring the AI4ALL program, teaching courses on decision-making under uncertainty, and advising projects at the intersection of robotics and AI. His lab collaborates on applications ranging from weather observation to human-centered autonomy in unmanned systems.

• Cybersecurity
• Authentication Systems
• Blockchain Technology
• +۶ مورد دیگر

Jun-Ho Huh is a Professor at Sungkyunkwan University's College of Information and Communication Engineering, Department of Computer Science and Engineering. His extensive research portfolio demonstrates leadership in cybersecurity, authentication systems, and AI applications across multiple domains including financial technology, maritime security, and agricultural technology. Dr. Huh's research interests span cybersecurity, authentication systems, blockchain technology, artificial intelligence, edge computing, and IoT security. His work bridges theoretical computer science with practical applications in smart systems engineering. His research has significant implications for improving security in emerging technologies like DeFi, autonomous systems, and smart infrastructure. Analysis of Dr. Huh's recent publications reveals a strong focus on practical applications of AI and security technologies. His work covers diverse areas including cybersecurity for maritime autonomous systems, authentication mechanisms, financial technology applications, and agricultural technology solutions. The publications demonstrate consistent productivity and relevance in addressing contemporary challenges in computer science and engineering. Dr. Huh has made significant contributions to authentication systems research, particularly in biometric and behavioral authentication methods. His work on keystroke dynamics, voice spoofing detection, and wearable device authentication has advanced the field of usable security. His research extends to practical applications in smart factories, agricultural technology (AgTech), and financial technology. The integration of blockchain with AI for various applications represents a significant thread throughout his recent work, demonstrating interdisciplinary approaches to solving complex technological challenges.