جست‌وجوی استاد و پژوهشگر

• Bioinformatics
• Computational Biology
• Plant Genomics
• +۳ مورد دیگر

Dirk Walther serves as a Professor and Research Group Leader for the Bioinformatics unit within the Infrastructure and Service Group at the Max Planck Institute of Molecular Plant Physiology in Potsdam, Germany. His position centers on leading computational research initiatives that bridge advanced data analysis with molecular plant science. His research expertise spans critical domains in life sciences computing: Bioinformatics and Algorithm Development Plant Genomics and Molecular Phenotyping Systems Biology Modeling High-Throughput Data Analysis Computational Plant Physiology Dr. Walther's group provides essential bioinformatics infrastructure for the institute, developing specialized tools to decode complex biological datasets and advance understanding of plant molecular mechanisms at scale.

Andreas Winterمشاهده پروفایل

استاد

• Quantum Shannon theory
• Classical Shannon theory
• Entropy and applications
• +۵ مورد دیگر

Andreas Winter is an ICREA Research Professor at Universitat Autònoma de Barcelona and holds a Hans Fischer Senior Fellowship at TUM-IAS, Technical University of Munich. He specializes in quantum and classical information theory with affiliations at the University of Cologne's Department of Quantum Information and Computation. His research examines fundamental limits in quantum communication, entropy applications, and quantum computing foundations. Education: Diploma in Mathematics, Freie Universität Berlin Ph.D. in Mathematics, Universität Bielefeld Research: His interdisciplinary work bridges quantum Shannon theory, thermodynamics, and discrete mathematics, exploring quantum channel capacities, information tradeoffs, and cryptographic protocols. Recent publications demonstrate advances in quantum coding efficiency and high-dimensional quantum systems. Awards: 2022: Hans Fischer Senior Fellowship, Alexander von Humboldt Prize, QCMC Quantum Award 2017: IEEE Information Theory Paper Award 2012: Whitehead Prize (LMS) 2007: Philipp Leverhulme Prize Leadership: Leads the Quantum Information Theory Focus Group at TUM-IAS, collaborating with Prof. Holger Boche on quantum communication frameworks.

Aysim Tokerمشاهده پروفایل

پژوهشگر

• Computer Vision
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Aysim Toker is a Ph.D. candidate at the Chair for Computer Vision and Artificial Intelligence , affiliated with the Technical University of Munich . She works under the supervision of Prof. Dr. Laura Leal-Taixe and Prof. Dr. Xiaoxiang Zhu on interdisciplinary projects. Research Focus: Deep learning, sequence analysis, and remote sensing. Key Contributions: Advancing video object segmentation, Earth observation models, and anonymization techniques. Collaborations: Partnered with international researchers across multiple institutions. Publications span top venues like eLife , ICCV , NeurIPS , and CVPR , with a focus on: Deep learning architectures for multi-modal tasks Image and video analysis in remote sensing and anonymization Tracking and segmentation algorithms Her work bridges foundational computer vision research with applications in Earth science and privacy-preserving technologies.

• Digital Signal Processing
• Speech Communication
• Acoustic Signal Processing
• +۳ مورد دیگر

Peter Vary is a Professor at the Faculty of Electrical Engineering and Information Technology of RWTH Aachen University, serving as Director of the Institute for Communication Systems. His work focuses on speech and audio signal processing for communication systems. Digital Signal Processing Speech Enhancement Acoustic Echo Control Microphone Array Beamforming Communication Systems Audio Compression His recent publications (2023–2024) emphasize speech coding, noise reduction, and bandwidth extension for hearing aids and mobile devices, with technical innovations in Kalman filters, hybrid digital-analog transmission, and wind noise detection. He holds a leadership role in the Institute for Communication Systems and serves as Ombudsperson for teaching in his faculty. Contact: vary@iks.rwth-aachen.de

Jan-Hendrik Heinrichsمشاهده پروفایل

پژوهشگر

• Neuroethics
• AI Ethics
• Philosophy of Mind
• +۱ مورد دیگر

PD Dr. Jan-Hendrik Heinrichs is a researcher at the Institute of Neuroscience and Medicine (Brain and Behavior - INM-7) at Research Center Jülich. His work explores philosophical and ethical dimensions of neuroscience and artificial intelligence. Research Focus His research examines neuroethical frameworks, moral responsibility in technology development, and philosophical aspects of cognitive enhancement. Recent publications analyze ethical boundaries of neurotechnologies and AI applications. Publication Trends Recent work addresses conceptual challenges in moral responsibility, ethical implications of neuroprosthetics, and limitations of cognitive scaffolding. Publications consistently bridge philosophy, neuroscience, and technology ethics.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Sio Kei Im is an active researcher with a focus on computer science, machine learning, and human-computer interaction. His recent work spans multiple domains including image processing, quantum computing, and virtual reality. Publications address advanced data augmentation (LogicMix), multi-modal quantum watermarking (MMQW), and efficient neural decoding algorithms (TRHyper). Research interests include time series optimization, dialogue summarization, and haptics in VR environments. Collaborations with experts in linguistics, electrical engineering, and software development indicate interdisciplinary expertise. Key contributions involve adaptive algorithms for AI model protection, speaker recognition systems, and real-time 3D rendering techniques.

Irene I. Bouwمشاهده پروفایل

استاد

• Algebraic Geometry
• Number Theory
• Arithmetic Geometry
• +۵ مورد دیگر

Prof. Irene I. Bouw is a full professor at the University of Ulm's Institut für Algebra und Zahlentheorie, specializing in algebraic geometry and number theory. Her research focuses on arithmetic geometry, coding theory, and the interplay between algebraic curves and Galois groups. She teaches advanced courses such as Algebra (Master's), Algebraic Geometry, and Coding Theory, with consultations available by appointment. Her work includes studies on superelliptic curves, L-functions, and modular curves, with notable projects like the DFG-funded 'Quotient singularities and semistable reduction.' She serves on editorial boards for Research in Number Theory and Journal de Théorie de Nombres de Bordeaux . Bouw's publications explore topics like conductor-discriminant inequalities, dynamical Belyi maps, and semistable reduction techniques. Her research often bridges theoretical insights with computational methods, contributing to both pure mathematics and applications in cryptography.

Michel Besserveمشاهده پروفایل

پژوهشگر

• Causal Machine Learning
• Complex Systems
• Neuroscience
• +۴ مورد دیگر

Michel Besserve is a Senior Research Scientist in the Empirical Inference department at the Max Planck Institute for Intelligent Systems in Tübingen, Germany. His research bridges machine learning theory with applications in neuroscience and complex systems analysis. He leads a research group focused on developing causal machine learning tools to uncover the internal structure and transformations of complex artificial, physical, and socioeconomic systems. Dr. Besserve's primary research interests center on causal machine learning and its applications to understanding complex systems. His work investigates how causality can provide principled ways to study and improve AI algorithms, particularly focusing on the identifiability of causal models and the principle of Independence of Causal Mechanisms (ICM). He develops theoretical frameworks and practical tools for causal inference in complex equilibrium systems, neural circuits, and socioeconomic contexts. His research has significant implications for building trustworthy and interpretable AI systems that can reliably handle real-world complexity. Analysis of Dr. Besserve's recent publications reveals a strong focus on causal representation learning, with significant contributions to independent mechanism analysis and the identifiability of nonlinear generative models. His work spans both theoretical foundations and practical applications, connecting machine learning with neuroscience to understand brain function through causal inference. The interdisciplinary nature of his research is evident in publications spanning top machine learning conferences (NeurIPS, ICML, ICLR) and leading neuroscience journals (Nature, PLOS Biology). Dr. Besserve has established productive collaborations across multiple institutions, particularly with researchers at the Max Planck Institute and ETH Zurich. His work demonstrates how integrating causal principles with machine learning can address fundamental challenges in AI robustness and interpretability, with applications ranging from brain network analysis to economic modeling. His research group focuses on developing the Causal Computational Model (CCM) framework, which aims to create digital representations of real-world systems that integrate data, domain knowledge, and interpretable causal structure. This work has potential applications in climate modeling, industrial digital twins, and economic simulation.

• Collective Intelligence
• Robotics
• Animal Behavior
• +۴ مورد دیگر

Liang Li is a Group Leader at the Max Planck Institute of Animal Behavior , leading the Embodied Collective Intelligence Lab . Her research bridges biology and robotics to study collective behavior through physical agent-environment interactions. Current position: Group Leader, Department of Collective Behavior Past roles: Project Leader at University of Konstanz and MPI Education: Ph.D. in Robotics and Control, College of Engineering, Peking University Research Interests Dr. Li's work focuses on embodied cognition , swarm intelligence , and fluid dynamics in biological and robotic systems. Key areas include hydrodynamic interactions in fish schooling, bio-inspired robotics design, and translating biological principles into robotic applications. Article Trends : Recent publications emphasize energy efficiency in swimming systems, hydrodynamic modeling for collective behavior, and virtual reality tools for behavioral studies. Interdisciplinary themes span robotics, fluid dynamics, neuroscience, and evolutionary ecology. Collaborations & Grants Her research involves international collaborations with institutions like University of Konstanz and Peking University. Grants include funding for robotic platforms (RoboTwin) and advanced pose estimation tools (DeepPoseKit). Labs & Teams The Embodied Collective Intelligence Lab is a small, interdisciplinary team specializing in bio-robotic systems. The group develops experimental robotic platforms and computational models to decode collective behavior rules.

Maria A. Martinمشاهده پروفایل

پژوهشگر

• Climate Change Modeling
• Glaciology
• Numerical Simulation
• +۳ مورد دیگر

Dr. Maria A. Martin has been affiliated with the Potsdam Institute for Climate Impact Research (PIK) since 2008, initially as a doctoral student and later transitioning to a post-doctoral researcher. Since 2014, she has served as a Research Analyst within the Scientific Directors' Staff department. Her academic background includes a physics degree from the University of Potsdam and Université Pierre-et-Marie-Curie in Paris, where her doctoral thesis focused on synchronization in quantum-optical resonators. At PIK, she co-developed the Parallel Ice Sheet Model and conducted pioneering research on Antarctic ice-flow dynamics using numerical modeling techniques. Dr. Martin's research interests span climate modeling, glaciology, and environmental science, with a particular emphasis on understanding the mechanisms driving ice-sheet dynamics and their implications for sea-level rise. Her work integrates advanced computational models with observational data to address critical questions in climate science. Beyond technical contributions, she has engaged in science communication through initiatives like the children's podcast Pinselohr . Her professional network and collaborations are reflected in her participation in interdisciplinary projects at PIK, including contributions to policy advice and software development related to climate impact research. She holds an ORCID identifier (0000-0002-1443-0891) and maintains active involvement in academic discourse through peer-reviewed publications and institutional outreach activities.

• Natural Language Processing
• Graph Neural Networks
• Large Language Models
• +۷ مورد دیگر

Liang Zhao is a Professor in the Department of Computer Science at Harbin Institute of Technology's School of Computer Science and Technology. His research spans multiple areas of natural language processing, artificial intelligence, and machine learning, with a particular focus on large language models, graph neural networks, and explainable AI systems. His research interests include natural language processing, graph neural networks, large language models, model explainability, federated learning, sparse attention mechanisms, hallucination mitigation, transformer length extrapolation, and uncertainty quantification. His work addresses fundamental challenges in modern AI systems, particularly in improving the reliability, efficiency, and interpretability of large language models. Professor Zhao's research output shows a clear trend toward addressing critical limitations in large language models, with recent work focusing on hallucination mitigation, model attribution, uncertainty quantification, and efficient attention mechanisms. His publications demonstrate strong interdisciplinary connections between NLP, machine learning theory, and practical system implementation. Through his extensive collaboration network with researchers including Xiaocheng Feng, Bing Qin, Weihong Zhong, and Yuntong Hu, Professor Zhao has established himself as a leading researcher in the Chinese NLP community. His work appears consistently in top-tier conferences including ACL, EMNLP, and NAACL.

Violetta Wegerمشاهده پروفایل

استادیار

• Cryptography
• Algebraic Coding Theory
• Post-Quantum Cryptography
• +۳ مورد دیگر

Prof. Dr. Violetta Weger is a Rudolf Mößbauer Tenure Track Assistant Professor in Applied Algebra at the Technical University of Munich (TUM), within the Department of Mathematics (M11) and the TUM School of Computation, Information, and Technology (CIT). Her research focuses on cryptography, algebraic coding theory, and number theory, with a particular emphasis on post-quantum cryptographic solutions. She has held fellowships at TUM and Eindhoven University of Technology, working under Prof. Antonia Wachter-Zeh and Prof. Alberto Ravagnani. Weger’s work includes developing code-based cryptographic systems like the CROSS signature scheme, submitted to NIST’s post-quantum standardization call. She actively contributes to conferences such as CBCrypto and publishes in leading journals like Designs, Codes and Cryptography. Her academic journey includes a PhD in Mathematics from the University of Zurich under Prof. Joachim Rosenthal. Research highlights include advancements in Lee metric decoding, information set decoding, and cryptographic applications of structured codes. Weger mentors students such as Anmoal Porwal and Sebastian Bitzer, and collaborates with international researchers. She also engages in educational initiatives, teaching courses on coding theory and cryptography.

Hanna Ehlertمشاهده پروفایل

پژوهشگر

• Artificial Intelligence in Speech Therapy
• Dynamic Assessment
• Language Development Disorders
• +۴ مورد دیگر

Hanna Ehlert is a researcher at Leibniz University Hannover, affiliated with both the Institute for Special Education (Faculty of Philosophy) and the Institute for Information Processing (TNT/Phonomatics spin-off). Her work bridges artificial intelligence with speech therapy, focusing on automated diagnostics and dynamic assessment for child language development. PhD in Special Education (2020, Leibniz University Hannover) M.Sc. & B.Sc. in Speech and Language Therapy/Logopedics (HAWK Hildesheim) State-certified speech therapist (Hannover Medical School) Her research integrates: Artificial Intelligence in speech therapy Dynamic Assessment for multilingual children Language development disorders Voice disorder prevention Technology for inclusive education Key research projects include: TALC (Tool for Analyzing Language and Communication) Phonomatics spin-off AI-LIT (AI-supported Literacy Development)

• Neuroengineering
• Brain-Computer Interfaces (BCI)
• Human-Robot Interaction (HRI)
• +۳ مورد دیگر

Stefan Ehrlich is a Researcher at the Institute for Cognitive Systems (ICS) at the Technical University of Munich (TUM). His work focuses on neuroengineering, particularly non-invasive brain-computer interfaces (BCI) for human-robot interaction (HRI), neuroadaptive systems, and EEG-based neurotechnology. He collaborates closely with Prof. Gordon Cheng and contributes to projects involving error-related potentials (ErrPs), affective neurofeedback, and neuroprosthetics. His research integrates cognitive neuroscience principles with robotics to enhance human-machine collaboration and adaptive systems. Key research areas include: Development of passive BCI systems for real-time robotic adaptation Design of co-adaptive human-agent interfaces using neural signals EEG-based assessment of exoskeleton and humanoid robot performance Neuroimaging techniques for music-brain interactions His publications emphasize interdisciplinary approaches, combining neuromorphic engineering, machine learning, and social robotics. Ongoing work explores low-power neuromorphic hardware for EEG decoding and neurophysiological mechanisms underlying human-robot trust dynamics. Collaborations involve institutions like the Bernstein Center for Computational Neuroscience and industry partners in wearable robotics. Labs/Teams: Active contributor to the EEG Laboratory and projects like the Soft Wearable Robotics initiative. Engages in international conferences (IROS, IEEE EMBC) and co-organizes workshops on HRI and neurotechnology.

Francesca Lanzariniمشاهده پروفایل

پژوهشگر ارشد

• Neuroethology
• Neural Decoding
• Motor Control
• +۳ مورد دیگر

Francesca Lanzarini is a Research Fellow at Goethe University Frankfurt, affiliated with the Laurens Lab. Her work focuses on neuroethology and neural mechanisms underlying motor control and decision-making in primates. She investigates natural behaviors such as foraging and reach-and-grasp movements, leveraging computational methods like clustering algorithms and unsupervised learning to decode neural activity patterns. Her research integrates experimental neuroscience with machine learning to understand how premotor cortex activity translates into complex actions. She has contributed to studies on aging effects in decision-making processes in primates and developed methodologies for behavioral analysis. Education details are not explicitly provided in the text. Her affiliations include the Laurens Lab, located at Deutschordenstr. 46, Frankfurt am Main, Germany. She can be reached at francesca.lanzarini@esi-frankfurt.de . Research interests span neuroethology, neural decoding, motor control, and primate cognition. Her recent work (2023-2025) emphasizes real-time decoding of premotor activity and the dynamics of naturalistic behaviors in freely moving monkeys. She has also explored methodological tools for online research and generative vocabulary testing. No scientific awards or grants are mentioned in the provided text. Francesca collaborates within the Laurens Lab team, which includes researchers like Jean Laurens, Farzad Ziaie Nezhad, and Deepak Surendran, and is managed by Sogand Ghiasi.