جستجوی استاد راهنمای دانشگاهی

Andrea Dunbarمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۵ مورد دیگر

Andrea Dunbar serves as the Focus Activity Manager of Data & AI at CSEM and holds the position of Professor of Practice at École Polytechnique Fédérale de Lausanne (EPFL). With a PhD in Physics from Trinity College, Dublin and an Executive MBA from EPFL, she combines deep technical expertise with business acumen in her work at the intersection of AI and industry applications. Her research focuses on developing sustainable AI solutions for resource-constrained environments, with particular expertise in machine learning applications, intelligent vision systems, and multispectral technologies. Dunbar's work emphasizes ultra-low power systems design, including low power imagers, hierarchical computing architectures, and resource-aware machine learning training specifically tailored for IoT applications. Her research bridges the gap between theoretical AI advancements and practical implementations that address real-world sustainability challenges. As an active board member and startup coach, Dunbar applies her knowledge of innovation management and digital transformation to help businesses generate value through strategic AI and data implementation. Her expertise spans the entire spectrum from foundational research to commercial application, with a strong emphasis on creating sustainable technological solutions that can operate effectively in resource-limited environments. Professor Dunbar has participated in specialized workshops such as the tinyML session at the AI for Good Summit 2024, where she contributed to discussions about pioneering sustainable solutions in resource-constrained settings. Her work demonstrates a commitment to advancing AI technologies while maintaining environmental consciousness and practical applicability in real-world scenarios.

• Smart Grids
• Distributed Systems
• Energy Management
• +۴ مورد دیگر

Dr. Daniel Brettschneider is a researcher at the Osnabrück University of Applied Sciences , affiliated with the School of Engineering and Computer Science and the Laboratory for High Frequency Technology and Mobile Communications . His work focuses on distributed systems for smart grids and energy management. Research Interests: Smart Grids and Distributed Energy Management Privacy Preservation in Energy Systems Context-sensitive Services and Mobile Applications Communication Requirements for Distributed Algorithms Cluster-based Energy Optimization Integration of Power, Heat, and Communication Networks Article Trends: His publications (2011-2016) emphasize smart grid algorithms, privacy-preserving protocols, context-aware mobile systems, and simulator development for multi-domain energy networks. Keywords include distributed computing, homomorphic encryption, and cooperative energy systems.

• Wireless Communication
• 5G/6G Networks
• Internet of Things (IoT)
• +۳ مورد دیگر

Abhishek Roy is a researcher at Samsung Electronics, Suwon, South Korea , with a PhD in Software Department, Sungkyunkwan University (2010) . His work focuses on 5G/6G wireless networks , Internet of Things (IoT) , and machine learning-based network optimization . His research interests span beamforming , discontinuous reception (DRX) , device-to-device (D2D) communication , and network slicing , often integrating AI/ML for predictive analytics. Key contributions include optimizing NR-Unlicensed spectrum , enhancing V2X communication efficiency, and developing O-RAN frameworks for future networks. Recent publications analyze cross-frequency beam prediction (2024), GPS-based beam selection (2023), and predictive service automation in O-RAN (2022). His work intersects network resource management with smart grid integration and disaster connectivity .

• Machine Learning
• Computational Modeling
• Biomedical Engineering
• +۳ مورد دیگر

Stephen Baek is a faculty member at the University of Iowa, Department of Industrial and System Engineering, with a PhD from Seoul National University's School of Mechanical and Aerospace Engineering. His research spans interdisciplinary applications of machine learning in computational modeling, biomedical engineering, and geometric data processing. Current Affiliation: University of Iowa, Department of Industrial and System Engineering PhD Institution: Seoul National University Stephen's work focuses on physics-informed machine learning , multiscale modeling , and geometric deep learning . He develops algorithms that integrate physical principles with neural networks for applications in energetic materials , human pose estimation , and medical imaging . His research also includes federated learning and interpretable AI for constraint-based synthesis and text classification. Recent publications highlight a physics-aware deep learning framework (PARCv2) for spatiotemporal dynamics, graph convolutional networks for airway mesh smoothing, and prototype trajectory methods for explainable AI. This work bridges computer science with applied physics and healthcare domains. Stephen actively collaborates across disciplines, evidenced by co-authors from institutions like Iowa, Seoul National University, and Samsung Electronics, with publications in venues such as CoRR , J. Mach. Learn. Res. , and NeurIPS . His methodological innovations address challenges in model heterogeneity , 3D surface processing , and constraint satisfaction .

• Database Systems
• Data Management
• Recommender Systems
• +۴ مورد دیگر

Sihem Amer-Yahia is a distinguished Research Professor at the University of Grenoble Alpes (affiliated with Grenoble Informatics Laboratory ), with significant contributions to database systems , data exploration , and fairness in AI . Her work bridges human-computer interaction and machine learning to create systems that enhance data-driven decision-making. Research Pillars : Algorithmic fairness, interactive data mining, recommender systems, and human-AI collaboration Recent Advances : 2023-2025 publications focus on statistically sound hypothesis testing , multi-objective recommendation , and conversational analytics Leadership : Co-organized major conferences (DASFAA 2024) and led DEI initiatives in database communities Her 15 most recent articles (2020-2025) span topics like producer fairness in recommendation , statistical hypothesis frameworks , and AI-powered education systems , with keywords covering database optimization , reinforcement learning , and ethical data mining . She actively contributes to ACM/IEEE journals and VLDB/SIGMOD conferences.

• Network-on-Chip (NoC)
• Embedded Systems
• Fault Tolerant Design
• +۴ مورد دیگر

Martin Radetzki is a full Professor at the Institute for Computer Architecture and Parallel Systems (University of Stuttgart) , specializing in Embedded Systems . His work focuses on network-on-chip (NoC) design, fault tolerance, memory optimization, and simulation frameworks. Key research areas: NoC synthesis, deadlock-free routing, performability analysis, and power-efficient memory subsystems Recent publications emphasize integer linear programming frameworks for co-designing floorplanning and routing, chiplet-based systems , and machine learning-enabled performance evaluation His methodologies address cross-layer challenges in NoC design, combining formal optimization with practical implementation for heterogeneous processing elements. Collaborative projects include fault resilience analysis, parallel simulation techniques, and memory allocation strategies for SoCs. Dr. Radetzki supervises research with students like Shuang Liu and Manuel Strobel , contributing to IEEE Transactions on Computers , ACM TECS , and conferences such as DATE and MCSoC . Current work explores optimal routing topologies for emerging chip architectures.

• Battery Energy Storage Systems
• Power Control Optimization
• Battery Degradation Analysis
• +۲ مورد دیگر

Vivek Tanjavooru is a Research Fellow at the Institute of Energy and Drive Technology within the Allgäu Research Center at Kempten University of Applied Sciences. He specializes in energy systems, battery optimization, and thermal modeling, with a focus on industrial applications and grid technologies. His research spans battery energy storage systems, including power split control algorithms, degradation-aware dispatch optimization, and state-of-charge balancing with spatial thermal analysis. Recent work emphasizes real-time simulation feedback and heterogeneous battery systems, particularly for second-life applications. Key trends in his publications highlight integration of thermal-electric grid dynamics, additive manufacturing for automotive components, and predictive maintenance strategies. He collaborates on projects involving energy efficiency, sustainable systems, and industrial innovation.

Simon Steuerمشاهده پروفایل

پژوهشگر

• Hybrid Location Models
• Internet of Things
• Data Quality of Environmental Sensors
• +۳ مورد دیگر

Simon Steuer, M.Sc., is a Research and Teaching Assistant (Wissenschaftlicher Mitarbeiter) at the Chair of Mobile Systems within the Faculty of Information Systems and Applied Computer Sciences at the University of Bamberg, Germany. Since 2016, he has been actively contributing to research and teaching in the areas of hybrid location models, Internet of Things (IoT), and data quality of environmental sensors. Education 2014–2016: Master of Science in Applied Computer Science, University of Bamberg 2010–2014: Bachelor of Science in Media Informatics, Hochschule Hof 2004–2007: Vocational Training as IT Systems Electronics Technician, Deutsche Telekom AG Research Interests Simon Steuer's research is centered around the development of hybrid location models that integrate symbolic and geometric location information. He is particularly focused on applications in smart agriculture, such as the WeideInsight project, where he works on energy-efficient localization systems for cattle using Bluetooth Low Energy (BLE) and Mioty (LPWAN) technologies. His work also encompasses the improvement of data quality from environmental sensors, especially in citizen science contexts, and the design of privacy-preserving architectures for smart city labs. Research Projects & Theses Supervision Steuer actively supervises student theses and projects, including: Development of semantic models for hybrid cow location techniques Data generators for smart spaces and agriculture simulations Filtering and evaluation of beacon-based indoor positioning data Literature surveys on map matching and information visualization in smart agriculture Code refactoring for LPWAN-based environmental sensors Design of location data players and visualization tools Labs and Teams He is a member of the Chair of Mobile Systems research group led by Prof. Dr. Daniela Nicklas. The group collaborates on projects such as Explanym , Crowdanym , FutureIOT , Living Lab Bamberg , SIMUTOOL , and WeideInsight , fostering interdisciplinary research in mobile systems, IoT, and smart environments.

Reiner Creutzburgمشاهده پروفایل

استاد

• Applied Computer Science
• Algorithms
• Data Structures
• +۷ مورد دیگر

Prof. Dr. rer. nat. Reiner Creutzburg is a professor at the Brandenburg University of Technology Cottbus-Senftenberg in the Department of Computer Science and Media , specializing in Applied Computer Science with a focus on Algorithms and Data Structures . Research Focus: Cybersecurity, Machine Learning, Computer Vision, IoT Security, Open Source Intelligence (OSINT), and Critical Infrastructure Protection Recent Trends: Over 15 recent publications explore AI-driven cybersecurity solutions, image/video processing for event management, and secure voting systems using blockchain.

Olga Levinaمشاهده پروفایل

استاد

• Ethical Issues of Digitalization
• Business Process Management
• Low-Code Development
• +۲ مورد دیگر

Prof. Dr. Olga Levina serves as Professor of Business Informatics at Brandenburg University of Technology (BTU), Department of Economics, where she bridges technical systems design with ethical governance in digital transformation. Her institutional leadership includes contributions to DIN working groups on Responsible AI and UNESCO's "Artificial Intelligence for more gender equality and against discrimination" guideline. Her educational background includes: Industrial Engineering with technical specialization in Information and Communication Systems (Technical University of Berlin and LUISS Rome) Doctorate in Network Analysis (TU Berlin) Levina's research critically examines ethical digitalization , business process management , and low-code development through participatory frameworks. She investigates how socially-aware information systems can mitigate digital inequality while advancing sustainability. Current projects analyze dark patterns in consent interfaces and AI's impact on journalistic values, emphasizing transparency and stakeholder inclusion as foundational principles. Her 15 most recent publications (2021-2025) reveal three dominant trajectories: (1) operationalizing ethics in software design through assessment tools and pipelines, (2) analyzing low-code platforms' organizational impact, and (3) exposing biases in algorithmic systems via empirical studies of dark patterns and recommender systems. This work consistently connects technical implementation with societal consequences. Levina actively supervises Master's theses through structured processes requiring English proficiency and research proposals. Her Ethical and Legal Aspects of Digitalization course generates publishable student research on topics like cookie consent dark patterns and AI sentiment analysis. She leads the InnoWest project on sustainable IT development while maintaining roles as journal/conference reviewer and DIN working group contributor. Her research group produces empirical studies through student projects examining digital ethics in real-world contexts, including cross-national analyses of cookie banners and values in messenger apps. Current work explores "naming as framing" in sustainability discourse and machine learning system auditing.

• Agent Technology
• Artificial Intelligence
• Autonomous Driving
• +۹ مورد دیگر

Prof. Dr.-Ing. habil. Dr. hc Sahin Albayrak is a distinguished academic and entrepreneur at the Technical University of Berlin , where he founded and directs the Distributed Artificial Intelligence Laboratory (DAI Laboratory) . He leads the Agent Technologies in Business Applications and Telecommunications research group and serves as founding member of Deutsche Telekom Laboratories (2004) and European Center for ICT (EICT) (2005). As initiator of Connected Living e.V. (2009) and managing director of German-Turkish Advanced Research Center for ICT (2012), he bridges international collaborations. He also founded IOLITE GmbH (2014) and other startups. Research Focus: Agent technology, autonomous driving, smart cities, cyber security, machine learning, and AI applications in energy systems Awards: Federal Cross of Merit (2014), multiple Best Paper Awards Leadership: Director of DAI Laboratory, head of research group at TU Berlin His 20+ recent publications (2022-2025) demonstrate expertise in agent-based architectures , smart mobility solutions , context-aware computing , and AI-driven security systems . Notable trends include integrating large language models into database interfaces, optimizing multi-agent coordination for logistics, and advancing explainable AI through feature attribution frameworks. Scientific Contributions: Recipient of Germany's Bundesverdienstkreuz for German-Turkish cooperation Best Paper Award at Smart Grid Architectures conference

• High Performance Computing
• Multi- and Manycore Computing
• Power Aware Computing
• +۱ مورد دیگر

Dr. Alfredo Remon is a Researcher at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, Germany, since 2013. Previously, he served as an Assistant Researcher at the University Jaume I in Castellón, Spain, from 2005 to 2013. Research Focus: High Performance Computing, Multi- and Manycore Computing, Power Aware Computing, Solution of large-scale matrix equations

Masud Rahmanمشاهده پروفایل

دانشیار

• Software Engineering
• Artificial Intelligence for Software Engineering (AI4SE)
• Software Maintenance and Evolution
• +۱۱ مورد دیگر

Masud Rahman is an Associate Professor in the Faculty of Computer Science at Dalhousie University, Canada, where he leads the RAISE Lab. Previously a tenure-track Assistant Professor, he completed his Ph.D. in Computer Science/Software Engineering from the University of Saskatchewan and a postdoctoral fellowship at Polytechnique Montreal. His academic career demonstrates strong progression with significant research impact in software engineering. Faculty of Computer Science, Dalhousie University (Current) University of Saskatchewan (Ph.D. studies) Polytechnique Montreal (Postdoctoral research) Dr. Rahman's research focuses on the intelligent automation of software maintenance and evolution, particularly targeting software debugging, code search, and code reviews. His work strategically combines Software Engineering with Artificial Intelligence techniques including Machine/Deep Learning, Information Retrieval, Mining Software Repositories, and Natural Language Processing. His industry experience as a professional developer for three years significantly shaped his research direction toward solving practical software maintenance challenges that cost the global economy billions annually. His research program addresses critical problems in software bug detection, diagnosis, explanation, and reproduction, with increasing focus on AI-powered and simulation modeling software. His publications demonstrate consistent output in top-tier venues including 7 papers at ICSE (A*), 3 at FSE (A*), 3 at ASE (A*), 8 at EMSE (A), 6 at ICSME (A), and 9 at MSR (A). The research trends show increasing focus on deep learning applications for software engineering problems, with particular attention to code search, bug localization, and debugging automation. His work has evolved from traditional information retrieval approaches to incorporate advanced neural network techniques and generative AI. Governor General's Gold Medal 2019 U of S Doctoral Thesis Award 2019 CS Best PhD Thesis Award 2019 TCSE Distinguished Paper Award Most Influential Paper Award Dr Keith Geddes Award Dalhousie Belong Research Fellowship President's Gold Medal (Bangladesh) Dr. Rahman has secured $500K+ in competitive research funding as Principal Investigator, including an NSERC Discovery Grant, Mitacs Accelerate International, and Climate Action and Awareness Fund. He actively collaborates with industry partners including Metabob Inc., Mozilla Firefox, and Vendasta Technologies. His service to the community includes extensive program committee work for major conferences and journal reviewing. He leads the RAISE Lab, which focuses on developing AI-powered solutions for software maintenance challenges, with current projects emphasizing sustainable software innovation and sustainable AI as part of Dalhousie's strategic goals.