جستجوی استاد راهنمای دانشگاهی

• Environmental Informatics
• Remote Sensing
• Artificial Intelligence
• +۲ مورد دیگر

Thomas Nauss has served as President of Marburg University since February 2022, with a six-year term ending in February 2028. Concurrently, he holds a professorship in Environmental Informatics at Philipps-Universität Marburg since 2011, and previously held administrative roles including Vice President for Information Management (2019-2022) and Dean of the Department of Geography (2015-2017). His academic journey began with studies in Geography, Remote Sensing and Bioclimatology at the University of Munich (1996-2001), culminating in a doctorate in Geography in 2005 from Philipps-Universität Marburg focusing on satellite-based rainfall retrievals. Nauss's primary research involves spatial sensing of environmental systems through networked sensors, remote sensing, and artificial intelligence. His work pioneers intelligent monitoring systems for biodiversity and ecosystem processes, with significant fieldwork in African montane regions. Key projects include Nature 4.0 for integrated environmental monitoring and contributions to hessian.AI as a founding member. Analysis of his recent publications reveals a consistent focus on applying remote sensing and AI to ecological challenges. His work spans sensor network deployment, biodiversity assessment in tropical mountains like Mount Kilimanjaro and the Bale Mountains, and development of open-source tools for environmental data analysis, with strong emphasis on climate change impacts and sustainable land management. Nauss leads the Nature 4.0 initiative for intelligent ecosystem monitoring and co-founded hessian.AI. He also serves on the research advisory board of the Kellerwald-Edersee National Park, contributing expertise in environmental informatics to conservation efforts.

• Health Psychology
• Nutritional Psychology
• Risk Perception and Communication
• +۵ مورد دیگر

Prof. Dr. Britta Renner heads the Psychological Assessment and Health Psychology research group at the University of Konstanz since 2007 as a W3 Professor in the Department of Psychology within the Faculty of Science. She serves in multiple high-level advisory roles including as Vice President of the German Nutrition Society (DGE), Deputy Chair of the Scientific Advisory Board for Agricultural Policy at the Federal Ministry of Food and Agriculture, and spokesperson for the Cluster of Excellence EXC 2117 'Collective Behavior' since December 2023. Her educational background includes a Diploma in Psychology from Free University Berlin (1993), Doctorate from Free University Berlin (2000), and Habilitation in Psychology from University of Greifswald (2004). Prior to her current position, she served as Professor of Psychology at Jacobs University Bremen (2004-2007), Postdoctoral Researcher at University of Greifswald (2000-2004), and Research Assistant at Free University Berlin (1993-1999). Renner's research focuses on psychological determinants of health behavior with emphasis on dietary behavior, development of mobile interventions for behavior change, subjective risk assessment, and sustainability. She leads the 'Collective Appetite' project within the EXC 2117 'Collective Behavior' cluster and the 'Why we move how we move' sustainability project at BWIM. Her recent publications reveal a strong trend toward interdisciplinary research bridging psychology, nutrition science, sustainability studies, and digital health interventions, with particular emphasis on the intersection of health and sustainability perceptions. Transferpreis für die Transferaktivität 'Forschung, Lehre und Politikberatung für mehr Nachhaltigkeit in der Ernährung' (2024) LUKS-Preis für exzellente Lehre (2021) Fellow of European Health Psychology Society (2015) Wissenschaftspreis Kulinaristik (2015) Fellow of Association of Psychological Science (2010) Marie-Schlei-Dissertationspreis (2001) Renner has secured substantial third-party funding including leadership roles in multiple BMBF and EU-funded projects such as DEDIPAC, SMARTACT, and EATMOTIVE. She has been instrumental in developing mobile health interventions for dietary behavior change and has contributed significantly to national and international policy discussions on nutrition, sustainability, and health. Her laboratory focuses on understanding the psychological mechanisms behind eating behavior within collective contexts and developing evidence-based interventions to promote healthier and more sustainable food choices.

Fabio Hellmannمشاهده پروفایل

پژوهشگر

• Biomedical Computer Vision
• Deep Learning
• Human-Computer Interaction
• +۳ مورد دیگر

Fabio Hellmann is a Ph.D. candidate and Researcher at the Chair for Human-Centered Artificial Intelligence under Prof. Dr. Elisabeth André at the University of Augsburg . Holding an M.Sc., he focuses on biomedical image/signal processing, deep learning, and explainable AI, with affiliations to the Faculty of Applied Computer Science and Institute of Computer Science . Research Interests : Biomedical Computer Vision Deep Learning Applications Human-Computer Interaction Explainable AI Medical Image Analysis Facial Phenotyping for Genetic Disorders Publications highlight trends in AI-driven medical imaging (e.g., GANonymization , GestaltGAN ), food viscosity analysis via sound, and rare disease diagnostics. He reviews for journals like IEEE Transactions on Dependable and Secure Computing and contributes to projects such as FORSocialRobots and Dynalearn .

Stina Kleinمشاهده پروفایل

پژوهشگر

• Human-Computer Interaction
• Human-Robot Interaction
• Cobot Error Management in Industry
• +۳ مورد دیگر

Stina Klein is a Scientific Associate at the Chair of Human-Centered Artificial Intelligence within the Institute of Computer Science at the University of Augsburg 's Faculty of Applied Computer Science . Her research focuses center on Human-Computer Interaction , Human-Robot Interaction , and Cobot Error Management in Industry , with applications in social robotics, affective computing, and multimodal systems. Research Interests Human-Computer Interaction Human-Robot Interaction Cobot Error Management in Industry Affective Computing Sign Language Recognition Media Memorability Teaching Lecture: Human-Computer Interaction (Summer 2025) Lecture + Exercise: Human-Robot Interaction (Summer 2025) Research Projects Open Topics for Theses & Projects FORSocialRobots KodiLL

• Search Based Software Engineering
• Software Testing
• Evolutionary Computation
• +۷ مورد دیگر

Giovani Guizzo is a Software Engineer at Kii working as a Blockchain Engineer and Front-end developer with React, while maintaining an active research profile in Search-Based Software Engineering. He earned his PhD in Computer Science from the Department of Informatics at Federal University of Paraná (UFPR) in Brazil under Professor Silvia Regina Vergilio in 2018. His academic collaborations include significant affiliations with University College London where he has published as a researcher. His research program centers on applying evolutionary computation and search-based techniques to software engineering challenges, particularly in software testing and optimization. Guizzo's work bridges theoretical advances in multi-objective optimization with practical software engineering applications, resulting in innovative solutions for test model inference, mutant reduction strategies, and automated program repair. His approach often combines natural language processing with finite state machine generation to transform bug reports into actionable test models. Guizzo's publication record reveals a consistent trajectory of increasing impact in top-tier software engineering venues. His recent work demonstrates sophisticated integration of multi-objective evolutionary algorithms with practical software testing challenges, particularly in the areas of model inference from natural language bug reports and optimization of mutation testing processes. The evolution of his research shows progression from foundational work on design patterns in evolutionary algorithms toward more complex applications in automated software testing and repair. His achievements include: SSBSE 2021 Challenge Winner for innovative work on fitness functions in automated program repair Distinguished Artifact Award at ICSE 2021 recognizing reproducibility in genetic improvement research Microsoft Azure Research Award in 2017 supporting his work in cloud-based software engineering research Guizzo maintains active engagement with the research community through editorial roles for IET Software and Science of Computer Programming, membership on the SSBSE Steering Committee, and service on program committees for major conferences including ESEC/FSE, ASE, GECCO, and ICSE. His academic visits to University College London (3 months in 2017) and Queen Mary University (1 month in 2017) established lasting research collaborations with Dr. Jens Krinke, Dr. Federica Sarro, and Dr. John Drake that continue to produce high-impact publications. Through his interdisciplinary approach combining software engineering, evolutionary computation, and natural language processing, Guizzo has established himself as a significant contributor to the search-based software engineering community, with research that consistently addresses practical challenges while advancing theoretical foundations.

Gustavo A. Olivaمشاهده پروفایل

استاد مدعو

• Programmable Blockchains
• Software Ecosystems
• Code Analytics
• +۶ مورد دیگر

Gustavo A. Oliva is an Adjunct Professor at Queen's University in Canada, where he leads the blockchain research team at the Software Analysis and Intelligence Lab (SAIL). His research focuses on enabling cost-effective decentralized applications on programmable blockchain platforms like Ethereum, alongside empirical studies in software ecosystems, code analytics, and explainable AI. Dr. Oliva earned his PhD from the University of São Paulo (USP) in Brazil under Professor Dr. Marco Gerosa. Prior to his current role, he was a Post-Doctoral Fellow at Queen's University supervised by Professor Dr. Ahmed Hassan. His primary research spans programmable blockchains, software ecosystems (particularly npm), code analytics, and explainable AI. He employs static analysis, historical repository mining, and machine learning to investigate software evolution, dependency management, and smart contract development. Current projects address gas efficiency challenges in Ethereum, upgradeability patterns in smart contracts, and the impact of foundation models on software engineering practices. Recent publications reveal a dominant focus on blockchain systems (70% of recent work), with growing emphasis on foundation model challenges (FMware). His Ethereum research explores transaction processing, gas optimization, and technical debt, while newer work catalogs software engineering challenges in trustworthy AI-powered systems. Scientific recognition includes: Microsoft Azure for Research sponsorship Capes/CNPq scholarship for Visiting Research at Queen's University (2014) HPE scholarships for Smart Cities and Cloud Service Choreography projects European Commission FP7 funding for CHOReOS project Dr. Oliva actively mentors 8+ students across academic levels. His PhD advisees include Muhammad Ahasanuzzaman (ongoing), Amir Mohammad Ebrahimi, and Filipe Cogo (now at Huawei). Master's students Michael Pacheco and Ahmad Abdullah Zarir now work at Huawei and Amazon respectively. He also supervises visitor and undergraduate researchers in blockchain projects. His service includes program committees for ICSE, SANER, and MSR conferences, plus tutorial leadership at ASE, KDD, and FSE. As director of SAIL's blockchain research team, he manages projects on Ethereum smart contract analysis, npm dependency ecosystems, and AI-driven software engineering. Current initiatives include SPICE (automated issue labeling) and foundational work on trustworthy FMware development, with industry collaborations at Huawei and Amazon.

Morakot Choetkiertikulمشاهده پروفایل

مدرس

• AI-Driven Software Engineering
• Defect Prediction
• Machine Learning for Software Engineering
• +۲ مورد دیگر

Morakot Choetkiertikul is a Lecturer at the Faculty of ICT, Mahidol University, Thailand, where he co-founded the SERU research group. He earned his Ph.D. in computer science from the School of Computing and Information Technology, Faculty of Engineering and Information Sciences (EIS) at the University of Wollongong (UOW), Australia, where he worked in the Decision Support Lab (DSL). His research focuses on AI-Driven Software Engineering , particularly in defect prediction, code quality assessment, and security vulnerability analysis. His work bridges artificial intelligence with practical software development challenges, creating tools that address real-world problems in software engineering processes. The SERU research group he co-founded demonstrates a strong commitment to developing practical solutions for the software industry. Morakot's publication record from 2020-2025 shows a clear evolution from foundational defect prediction research to comprehensive tool development across multiple aspects of the software lifecycle. His work spans code proficiency analysis (PyGress, jscefr), vulnerability detection (V-Achilles, DEV-EYE), and AI applications in development processes (Autorepairability studies), with increasing emphasis on empirical validation in real-world settings. Examiners' Commendation for Outstanding Thesis Best thesis award from University of Wollongong Dr. Choetkiertikul actively contributes to the software engineering community through program committee roles at major conferences including ASE, APSEC, ICSE, and ICSME. His leadership roles have expanded from committee member to track chair and early research achievements co-chair, reflecting his growing recognition in the field. His research on autorepairability, bus factor monitoring, and code proficiency assessment demonstrates a commitment to improving both software quality and developer productivity through data-driven approaches.

Vahid Alizadehمشاهده پروفایل

استادیار

• Empirical Software Engineering
• Software Quality
• Software Refactoring & Maintenance
• +۷ مورد دیگر

Vahid Alizadeh is an Assistant Professor in the College of Computing and Digital Media (CDM) at DePaul University in Chicago, USA, where he has been serving since 2020. His academic career focuses on bridging the gap between software quality research and industrial practice through empirical studies and intelligent tool development. Education: Ph.D. in Computer Science, University of Michigan (2015-2020) M.Sc. in Electrical Engineering, University of Tehran (2011-2013) B.Sc. in Electrical Engineering, Iran University of Science and Technology (2006-2011) Research Interests: Dr. Alizadeh's research spans empirical software engineering, software quality, refactoring & maintenance, intelligent software engineering, and AI-enabled systems. His work combines rigorous empirical methods with practical tool development to address real-world software engineering challenges. He has particular expertise in developing intelligent refactoring technologies that are currently deployed by organizations impacting thousands of programmers worldwide. Research Trends: His publication record shows a consistent focus on applying AI and machine learning techniques to software engineering problems, particularly in the areas of refactoring and quality assurance. Recent work demonstrates increasing integration of AI/ML approaches with traditional software engineering practices, reflecting the broader trend toward AI4SE (AI for Software Engineering). Awards & Recognition: Excellence in Teaching Award from DePaul University (2025) $67,000 DePaul-RFUMS Grant for AI-Powered Community Pharmacy Research (2024) ACM SIGSOFT Distinguished Paper Award at MODELS Conference (2020) Distinguished University of Michigan-Dearborn Honors Scholar (2020) Outstanding Graduate Research Assistant Award (2018/2019) Professional Activities: Dr. Alizadeh has served in various capacities at major software engineering conferences including ASE 2022 as Session Chair and Virtualization Co-Chair, and MODELS 2025 as Web Co-Chair. His work has resulted in one patent and multiple invention licenses through the University of Michigan Tech Transfer Office. He actively mentors graduate students interested in empirical software engineering, software quality, and intelligent refactoring technologies.

Earl T. Barrمشاهده پروفایل

استاد

• Software Engineering
• Program Analysis
• Automated Program Repair
• +۵ مورد دیگر

Earl T. Barr is a Professor of Software Engineering at University College London (UCL), where he heads the System Software Engineering Group and is a member of the Centre for Research on Evolution, Search and Testing (CREST). He received his Ph.D. in Computer Science from the University of California, Davis in 2009. His educational background includes: Ph.D. in Computer Science, 2009, University of California, Davis Barr's research focuses on software engineering, particularly program analysis, automated program repair, and the application of machine learning to code (AI4Code). He is renowned for his work on dual channel analysis, which examines how code combines natural language elements (in identifiers, comments, and stylistic choices) with formal programming language. His research also explores game theory applications to software development processes and how dual channel constraints can improve type inference and code understanding. His recent publications demonstrate a strong trend toward leveraging large language models for code understanding and modification, with particular emphasis on dual channel constraints and natural type inference. His work bridges traditional software engineering techniques with modern AI approaches, showing how machine learning can enhance program analysis and repair while maintaining rigorous theoretical foundations. Notable awards include: ACM SIGSOFT Distinguished Paper Award for Automated Software Transplantation (2015) ACM SIGSOFT Distinguished Paper Award for Learning Natural Coding Conventions (2014) ACM SIGSOFT Distinguished Paper Award for Collecting a Heap of Shapes (2013) Best Paper Award for TrustDavis: A Non-Exploitable Online Reputation System (2005) Barr actively supervises numerous PhD students and postdocs, with current research focusing on AI for code, software security, and program analysis. He collaborates extensively with Santanu Dash of Royal Holloway on dual channel program analysis, and they jointly supervise PhD students through the EPSRC Centre for Doctoral Training in Cyber Security for the Everyday. His work often combines theoretical rigor with practical tool development, resulting in several publicly available research tools that influence both academic research and industry practice. He leads the System Software Engineering Group at UCL, which focuses on developing novel approaches to software engineering challenges at the intersection of human and machine aspects of programming. Current research directions include dual channel analysis for vulnerability detection, game-theoretic approaches to development processes, and AI-assisted software development.

Andrea De Luciaمشاهده پروفایل

استاد

• Software Engineering
• Program Comprehension
• Software Security
• +۳ مورد دیگر

Andrea De Lucia serves as Full Professor in the Department of Computer Science at the University of Salerno, Italy, maintaining an active research profile with office hours at Fisciano Campus (Building F2, Room 089) and correspondence via adelucia@unisa.it. His scholarly contributions span software engineering with particular emphasis on security, mobile systems, and emerging quantum applications. His research portfolio demonstrates evolving focus through distinct phases: 2018-2020 : Code smell analysis and mobile energy efficiency (e.g., Android energy consumption studies) 2021-2022 : Security vulnerability lifecycle and quantum software engineering foundations 2023-2025 : Ethical AI integration (fairness in ML engineering) and advanced exploit prediction Recent publications reveal strategic expansion into quantum-computing applications and AI ethics, maintaining core software engineering principles while addressing contemporary challenges in secure, reliable systems development. His work consistently bridges theoretical frameworks with empirical validation through large-scale studies. De Lucia actively contributes to the software engineering community as program committee member for premier conferences including ICSE, ASE, and ICSME across multiple years (2018-2026), demonstrating sustained leadership in the field.

• Software Engineering
• Binary Analysis
• Reverse Engineering
• +۲ مورد دیگر

Han Gao is a researcher at the University of Science and Technology of China specializing in binary code analysis and reverse engineering, leveraging machine learning techniques to address challenges in stripped executable understanding. His research interests include: Software Engineering Binary Analysis Reverse Engineering Machine Learning for Software Engineering Program Analysis His publication trend demonstrates a focused application of large-scale pre-training models to infer missing information in stripped binaries, significantly advancing software security and maintenance capabilities for real-world executable analysis. No scientific awards were mentioned in available sources. No information is available regarding student advising, research grants, or laboratory team affiliations.

• Software Engineering
• Software Security
• Machine Learning for Code
• +۲ مورد دیگر

Qing Liao is a Researcher at Harbin Institute of Technology, specializing in software engineering with a focus on security, machine learning applications for code, and automation. His work bridges theoretical and practical challenges in modern software systems. Research Interests: Qing's research spans several interconnected areas: Software Security : Vulnerability detection, patch analysis, and configuration security. Machine Learning for Code : Application of ML models (e.g., transformers, graph networks) to code understanding, generation, and API recommendation. Program Analysis : Techniques for static analysis, browser fuzzing, and performance tuning. Automation : Tools for IaC generation, UI-to-code transformation, and configuration optimization. Publication Trends (2022–2026): His recent publications emphasize security (7/11 papers), particularly vulnerability detection using graph learning and static analysis. A secondary focus is ML-driven code automation (4/11 papers), including knowledge distillation, API generation, and UI-to-code systems. Work consistently targets real-world applicability, evidenced by industry-track publications at ASE/ICSE.

Luisa Verdolivaمشاهده پروفایل

دانشیار

• Image and Video Forgery Detection
• Deepfake Video Detection
• GAN Fingerprints Attribution
• +۵ مورد دیگر

Luisa Verdoliva is an Associate Professor at the Department of Industrial Engineering, University Federico II of Naples, Italy. She holds a Hans Fischer Senior Fellowship at the Technical University of Munich (TUM) Institute for Advanced Study (2020–present), hosted by Prof. Matthias Nießner. Her research focuses on multimedia forensics, deepfake detection, and generative AI analysis. She has been a visiting professor at Friedrich-Alexander-University (FAU) and a visiting scientist at Google AI's Perception team. Her research interests include image/video forgery detection, GAN fingerprints, biometrics liveness detection, and remote sensing applications. Verdoliva’s work has been funded by DARPA, Google, and the Italian Ministry of Research. She serves as Chair of the IEEE Signal Processing Society’s Information Forensics and Security Technical Committee and is an IEEE Fellow (2021). Key achievements include pioneering FaceForensics++ (a benchmark dataset for manipulated facial images), winning the IEEE Signal Processing Cup (2018), and receiving the Google Faculty Research Award (2018). Her awards span best paper recognitions at CVPR, ICIP, and ICIAP conferences. As part of TUM’s Visual Computing Focus Group, her fellowship research advances digital twin technology for built environments and AI-driven media forensics. Collaborations span academia and industry, with impactful contributions to combating synthetic media misuse and improving multimedia trustworthiness.

• Computer Vision
• Machine Learning
• 3D Reconstruction
• +۵ مورد دیگر

Andreas Geiger is Professor and Head of the Department of Computer Science at the University of Tübingen, Germany, where he leads the Autonomous Vision Group (AVG) within CyberValley. He serves as core faculty at the Tübingen AI Center, Principal Investigator in the Excellence Cluster ML in Science and CRC Robust Vision, and ELLIS fellow coordinating the ELLIS PhD program. Prof. Geiger's research centers on machine learning for computer vision, natural language processing, and robotics, with emphasis on 2D/3D scene representations, geometry reconstruction, and robust model development. His group pioneers neural rendering techniques like Gaussian splatting while addressing real-world challenges in autonomous driving, VR/AR, and scientific document analysis through discriminative and generative approaches. Recent publications (2025) demonstrate strong focus on 3D scene understanding using Gaussian splatting, autonomous driving simulation with world models like ReSim and Vista, and generative methods for controllable 3D scenes. The group maintains Scholar Inbox for personalized academic recommendations while advancing reinforcement learning for self-driving (CaRL) and robust perception evaluation (EMPERROR). Major recognitions include: Best Paper Awards at CVPR 2024/2021, 3DV 2017/2015, GCPR 2015 Sage 10-Year Impact Award 2024 and Longuet-Higgins Prize 2022 ERC Starting Grant 2019 and IEEE PAMI Young Researcher Award 2018 nuPlan Challenge Winner 2023 and German Pattern Recognition Prize 2017 Prof. Geiger actively supervises PhD students including Reiser (3D view synthesis), Baur (Lidar scene flow), Jaeger (reinforcement learning), and Liao (urban scene transfer). His group secures substantial funding through the ERC Starting Grant, Vector Stiftung's MINT Innovation Program, ML in Science Cluster, and CRC Robust Vision, while collaborating with industry via Waymo and nuPlan challenges. The Autonomous Vision Group operates from CyberValley's new campus building with a diverse international team (12+ nationalities). They maintain Scholar Inbox for academic discovery and organize regular technical retreats and unique team-building activities like deep cave expeditions, fostering innovation in 3D vision and autonomous systems.

• Media Aesthetics
• Media Culture
• Game Studies
• +۵ مورد دیگر

Dr. Rolf F. Nohr serves as Professor of Media Aesthetics/Media Culture at Braunschweig University of Art (HBK Braunschweig) and holds an External Affiliate position at the University of Arizona's College of Humanities. His research centers on media evidence methodologies, game studies, and instant images, with particular emphasis on simulation games as cultural techniques that shape rationality and decision-making processes. Nohr's scholarly work investigates the interplay between media theory, cultural techniques, and ludic systems. He examines how games function as evidentiary media through historical analysis of business simulations (1955-1975), military war games, and contemporary digital environments. His research reveals how strategic play constructs rational subject positions while interrogating the materiality of game interfaces and the epistemological status of media images. Recent publications demonstrate a cohesive trajectory analyzing games as media artifacts that produce knowledge through procedural logic. His work bridges historical media archaeology with contemporary game design, focusing on genre theory, player agency, and the pedagogical dimensions of serious games. Key themes include the transformation of work logic into play systems, feedback mechanisms in teaching machines, and the cultural techniques embedded in simulation interfaces. Scientific recognition includes: LehrLeo TU Braunschweig Award for Best Lecture in BA Studies (2013) German Study Prize, 3rd Place by Körber Foundation (1998) Nohr has secured major research funding from the German Research Foundation (DFG), Federal Ministry of Education and Research (BMBF), and NORD/LB Foundation for projects including 'Strategie Spielen' (2006-2011), 'Kulturtechnik Unternehmensplanspiel' (2012-2019), and 'PlanA – Planspiel Arbeitswelten' (2018). As Regional Director of the Learning Games Initiative Research Archive since 2015, he leads game preservation efforts while collaborating across engineering, humanities, and social science disciplines. He co-founded the Games Research Group within the German Society for Media Studies (GfM) and serves as editor for the 'Medien'Welten' and 'Braunschweiger Schriften zur Medienkultur' book series. His interdisciplinary collaborations span the TU Braunschweig's engineering departments, University of Arizona humanities scholars, and international game researchers through the Learning Games Initiative network.