جست‌وجوی استاد و پژوهشگر

Sarah Alice Gagglمشاهده پروفایل

پژوهشگر

• Abstract Argumentation
• Answer Set Programming (ASP)
• Knowledge Representation
• +۵ مورد دیگر

Dr. Sarah Alice Gaggl is a Researcher at the International Center for Computational Logic (ICCL) within the Technische Universität Dresden , where she has served as Group Leader for Logical Programming and Argumentation since October 2020. She also leads the BMBF-funded project NAVAS - Navigation in the Solution Space of Answer Sets and was a Principal Investigator in the Collaborative Research Center 248 (CPEC) from 2019 to 2022. Her research centers on Abstract Argumentation , Answer Set Programming (ASP) , and Knowledge Representation . Doctorate in Computer Science, Vienna University of Technology, March 2013 Her work bridges Answer Set Programming with practical applications in Knowledge Representation and Nonmonotonic Reasoning , focusing on navigation in plan spaces, efficient algorithms for ASP, and multi-criteria answer set selection. She has supervised numerous theses on topics like Multi-Shot ASP , Abstract Argumentation Frameworks , and Reinforcement Learning in game environments. Recent publications highlight trends in Answer Set Navigation (e.g., PlanPilot , IASCAR ), Algorithm Refinement (e.g., Winning Snake ), and Rule-Based Argumentation (e.g., Grounding Rule-Based Argumentation ). Her contributions span Computational Logic , Automated Reasoning , and Software Systems . She has held editorial and organizational roles for journals and conferences, including the Argument & Computation journal, KR , IJCAI , and ICLP . Dr. Gaggl leads the Logical Programming and Argumentation group and has been affiliated with the Computational Logic Group at TU Dresden since 2013. Her teaching includes courses like Theoretical Computer Science & Logic and Advanced Problem Solving .

• Head and Neck Surgery
• Optical Diagnostic Imaging
• Sinonasal Pathologies
• +۳ مورد دیگر

Christian Betz is a full Professor and Director of the Department of Otorhinolaryngology at the University Medical Center Hamburg-Eppendorf (UKE), Faculty of Medicine, University of Hamburg. As Deputy Director of the Head and Neurocenter, he specializes in head and neck surgery, optical diagnostic imaging, and HPV-related cancers. Medical Specialist in Otorhinolaryngology Vice-Deanery for Research representative Active in the European Platform for Photodynamic Medicine International collaborations in LASER SURG MED and radiobiology His research focuses on: Optical metabolic imaging for tumor differentiation AI-driven computer-aided diagnosis of sinus anomalies DNA repair mechanisms in HNSCC Photodynamic therapy applications Post-COVID olfactory dysfunction Key scientific contributions include: Over 30 publications in LASER SURG MED and HEAD NECK-J SCI SPEC 2025 international multicenter studies on surgical outcomes 2024 leadership in AI integration for maxillary sinus classification Awards: Video Award for 5-ALA fluorescence endoscopy Best Oral Communication Prize for OCT applications

Cornelius Königمشاهده پروفایل

استاد

• Work and Organizational Psychology
• Occupational Health Psychology
• Personnel Selection
• +۱۲ مورد دیگر

Prof. Dr. Cornelius König is a full Professor and leads the Chair of Work and Organizational Psychology at Saarland University, Faculty of Social Sciences and Humanities, Department of Psychology. He is an active researcher, educator, and supervisor, contributing significantly to organizational psychology, occupational health, and ethical workplace practices. His research interests include workplace surveillance, algorithmic fairness in HR, diversity and inclusion, labor migration, justice sensitivity, and employee well-being . He has led innovative teaching initiatives, including a seminar on generative AI in science, aimed at equipping students with future-ready competencies. The recent publications highlight a strong trend toward ethical and social justice issues in the modern workplace, spanning AI-based personnel selection, racial allyship in harassment cases, electronic monitoring, and stress underreporting. His work often involves cross-cultural collaborations, particularly with researchers in Uganda, Pakistan, and France. Scientific Awards and Recognition: Co-author on a study awarded the IAPP SOUPS Privacy Award (2023) for research on cyber threats in Pakistan. Prof. König actively supervises students and junior researchers, including Denise Vesper and Markus Langer (now Professor at Freiburg). He has secured international research collaborations and industry engagement through excursions to companies like Ursapharm, Fissler, and Saarstahl AG. His work bridges academic research with real-world organizational challenges.

• Artificial Intelligence
• Machine Learning
• Automotive Production
• +۸ مورد دیگر

Prof. Dr. Alexander Schiendorfer is a faculty member at Technische Hochschule Ingolstadt within the Faculty of Industrial Engineering , focusing on AI-based Optimization in Automotive Production . His research bridges Artificial Intelligence with manufacturing and industrial engineering , particularly in constraint programming, self-organizing systems, and machine learning applications for composite materials. His work spans pedagogical innovation in machine learning education, real-time manufacturing analytics , and AI for energy systems . Recent publications highlight applications in gas grid management, synthetic data frameworks, and defect analysis in autonomous driving sensors. He leads teams at AImotion Bavaria , collaborating on projects like SmartManPy for synthetic manufacturing data and MORL agents for multi-objective energy optimization. His methodological contributions include certainty groups for neural network confidence estimation and hierarchical resource allocation algorithms.

Michael Mumaمشاهده پروفایل

استاد

• Robust Data Science
• Signal Processing
• Machine Learning
• +۵ مورد دیگر

Michael Muma is a Professor in the Department of Electrical Engineering and Information Technology at Technische Universität Darmstadt. His research focuses on robust data science theory and methods applied to signal processing and machine learning in biomedicine and engineering. He leads the ERC Starting Grant ScReeningData project, developing methods for reproducible information discovery in biomedical databases, and is a Principal Investigator in the LOEWE center emergenCITY and BMBF cluster curATime. Prior roles include Independent Junior Research Group Leader (Athene Young Investigator) and Lecturer at TU Darmstadt from 2017 to 2022, and Research Associate (Post-Doc since 2014) from 2009 to 2017. His research interests span robust statistical methods, high-dimensional data analysis, emergency response systems, and biomedical signal processing. Notable projects include FDR-controlled portfolio optimization, ECG delineation algorithms, and radar-based vital sign estimation. Muma has contributed to distributed sensor networks, robust clustering, and sparse regression techniques. His work addresses challenges in multi-source detection, financial data analysis, and genomics through interdisciplinary approaches combining signal processing, machine learning, and robust statistics. Recent publications emphasize scalable solutions for high-dimensional problems, including applications in robotics, cardiology, and financial index tracking.

Jonas Hurmمشاهده پروفایل

پژوهشگر

• Housing Finance
• Credit Risk Modeling
• Financial Engineering
• +۶ مورد دیگر

Jonas Hurm is a Researcher at the Department of Banking and Financial Services, University of Stuttgart. He is affiliated with the Chair of Business Administration: Banking and Financial Services (510F). His research focuses on Housing Finance, Credit Risk Modeling, and Financial Engineering with a specialization in structured financial products and portfolio strategies. He actively contributes to academic publications in journals such as Zeitschrift für das gesamte Kreditwesen and Corporate Finance . Teaching responsibilities include master's courses on Portfolio Management and Derivatives, as well as doctoral-level seminars in Finance and Contract Theory. His work often bridges theoretical finance with practical applications, such as analyzing yield curve modeling using German and UK government bonds, evaluating hedging strategies via cash-secured put options, and exploring the role of catastrophe bonds in asset allocation. He has published a monograph on volatility-based hedge fund strategies (Springer Nature, 2024) and collaborates on case studies in financial engineering, including reverse convertible bonds. His research also investigates EU crowdfunding markets and their regional dynamics. Contact him via his university office in Room 4.36/120 (+49 711 459-23283).

Martin Herdegenمشاهده پروفایل

استاد

• Mathematical Finance
• Probability Theory
• Stochastic Processes
• +۵ مورد دیگر

Prof. Martin Herdegen is a Professor in Financial Mathematics at the University of Stuttgart, leading the Research Group Stochastics and Applications within the Department of Stochastics and Applications. Previously, he held positions as a Reader at the University of Warwick (UK) and a postdoc at ETH Zurich under Prof. Martin Schweizer. His research focuses on mathematical finance, including equilibrium theory, utility maximization, stochastic differential utility, and financial risk measures, alongside probability theory topics like stochastic optimal control and weak convergence of measures. Education: PhD in Mathematics from ETH Zurich (2014), supervised by Prof. Martin Schweizer. His academic journey includes postdoctoral research at ETH Zurich and Warwick. Research interests span mathematical finance and probability, with emphasis on frictions in financial markets, risk modeling, and stochastic processes. Recent work explores mean-variance equilibria, market making dynamics, and ρ-arbitrage frameworks. Publications (2020–2024) highlight contributions to equilibrium asset pricing under transaction costs, optimal portfolio strategies with frictions, and algorithmic trading models using reinforcement learning. His work bridges theoretical stochastic analysis with practical financial applications. Advising: Supervised multiple PhD students including Osian Shelley (JP Morgan), Nazem Khan (Dublin City University), and Joseph Jerome (Liverpool University), with current advisees focusing on stochastic finance and machine learning integration. Research Group: Includes postdocs and PhD students working on topics like risk measures, market microstructure, and computational finance. Collaborations span institutions across Europe and North America.

Isabel Jalaßمشاهده پروفایل

پژوهشگر

• Healthcare Research
• Long-term Care
• Quantitative Research Methods
• +۷ مورد دیگر

Isabel Jalaß, M.Sc., is a researcher at Osnabrück University of Applied Sciences, affiliated with the Faculty of Economics and Social Sciences. She works in the BMBF-funded project "PoWEr" (2025-2028) and previously contributed to the G-BA Innovation Fund project "ReKo" (2019-2024), BGW's "PsyGeRaH" (2023-2024), and BAuA's "GuDiT" (2021-2022). Current affiliation: Faculty of Economics and Social Sciences Research focus: Healthcare research, quantitative methods, secondary data analysis, regional learning Her publications demonstrate expertise in case management, long-term care, and digital technologies in healthcare. She actively participates in conferences like the German Congress for Healthcare Research and AGENS Method Workshop. Since 2025, she is a member of the German Network for Healthcare Research (DNVF).

• E-Commerce Search Engines
• Recommender Systems
• Machine Learning
• +۴ مورد دیگر

Anxiang Zeng is a researcher affiliated with the University of Kansas School of Business , Department of Management and Leadership. His work focuses on machine learning applications in e-commerce , particularly in search engines, recommender systems, and preference optimization.

• Computer Science
• Distributed Systems
• Blockchain Technology
• +۳ مورد دیگر

Hans-Arno Jacobsen is a Professor at the Faculty of Computer Science (Technische Universität München, TU Munich) and affiliated with the Department of Electrical and Computer Engineering at the University of Toronto. His work spans Computer Science , Distributed Systems , and Artificial Intelligence . Research interests include Blockchain Technology , Consensus Algorithms , Graph Neural Networks , and Quantum Computing . Recent projects focus on decentralized consensus , energy-efficient databases , and federated learning in edge environments. His 15 most recent articles (2024–2025) explore topics such as dynamic resource orchestration , CRDT-based blockchains , and multimodal depression recognition . Collaborates with researchers like Ruben Mayer , Gengrui Zhang , and Shiqiang Wang on systems for federated computing , blockchain benchmarking , and distributed GNN training .

Ralph Neiningerمشاهده پروفایل

استاد

• Probability Theory
• Algorithms
• Stochastic Analysis
• +۳ مورد دیگر

Ralph Neininger is a Professor at the Department of Computer Science and Mathematics, Goethe University Frankfurt. His research focuses on Probability Theory, Algorithms, Stochastic Analysis, and Data Structures, with a particular emphasis on the analysis of randomized algorithms and combinatorial structures. Key research areas: Randomized algorithms, stochastic processes, data structures, and distributional analysis. Recent publications address complexity fluctuations in algorithms, analysis of satisfiability problems, and probabilistic models for trees and urns. His methodological work leverages advanced probabilistic techniques to derive limit theorems and convergence rates for algorithms. Though no scientific awards are explicitly mentioned, his extensive publication record underscores significant contributions to theoretical computer science and applied probability. He has not been listed with advisees or students in the provided materials.

• 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 .

• Data Deduplication
• Spatial Data Mining
• GPU Computing
• +۳ مورد دیگر

Witold Andrzejewski is an active researcher in computer science, focusing on data deduplication pipelines, co-location pattern mining, and GPU-accelerated algorithms. His work bridges academia and industry, with publications analyzing customer record deduplication in the financial sector, performance optimization of spatial data processing, and comparative studies of statistical modeling versus machine learning approaches. 2025: Co-location pattern mining with Euclidean metrics 2024: Customer data deduplication parameter tuning 2023: Text similarity measures in financial applications

• Plasmonics
• Electron Energy Loss Spectroscopy
• Ultra-fast Electron Optics
• +۴ مورد دیگر

Dr. Johannes Schultz is a PostDoc researcher at the Leibniz Institute for Solid State and Materials Research Dresden (IFW Dresden), affiliated with the Institute for Integrative Nanosciences. He leads the Advanced Methods of Electron Microscopy Group, focusing on cutting-edge electron microscopy techniques and plasmonics research. His scientific focus spans magnetic textures and dynamics at micro-to-nano scales , development of ultra-fast electron optical elements with sub-nanosecond response times, Electron Energy Loss Spectroscopy in TEM (particularly low-loss excitations), and plasmonics in nanoparticle assemblies and correlated materials. His work bridges fundamental physics with nanotechnology applications. Dr. Schultz has published 16 journal papers since 2018 in high-impact venues including Nature Communications , Physical Review Research , and Advanced Optical Materials , with significant contributions to understanding plasmon localization, electron optics, and nanomaterial characterization. His research demonstrates consistent technical innovation in electron microscopy methodologies. As an active contributor to the microscopy community, he has delivered 8 invited talks at major international conferences including the European Microscopy Society Congress and PICO 2024. His collaborations span multiple institutions including Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, and international partners in Belgium, France, and Austria. The Advanced Methods of Electron Microscopy Group develops specialized techniques for nanoscale characterization, with particular expertise in spectral field mapping, plasmon dynamics analysis, and computational modeling of electron-matter interactions. Current work emphasizes disordered plasmonic systems and ultrafast electron optical components.

Christian Klaesمشاهده پروفایل

استاد

• Neurotechnology
• Brain-Computer Interfaces
• Neuroscience
• +۷ مورد دیگر

Prof. Dr. Christian Klaes leads the KlaesLab at the Ruhr-University Bochum 's Department of Neurotechnology , focusing on advanced neuroprostheses and assistive devices for paralysis rehabilitation. His work integrates neuroscience , machine learning , and virtual reality to decode brain signals for controlling exoskeletons and BCI systems . Key research areas: Brain-Computer Interfaces , Neural Implants , VR-based Neurorehabilitation , and AI-driven Medical Diagnostics Collaborations with Caltech , German Primate Center , and University of Madeira expand his interdisciplinary impact. Recent publications highlight advancements in EEG decoding accuracy , spike sorting algorithms , and somatosensory feedback systems , demonstrating his lab's contributions to neural signal processing and embedded AI platforms for future implants. Current projects include developing smart upper-limb exoskeletons , exploring terahertz brain imaging , and pioneering phantom touch illusions for sensory augmentation in VR environments.