جست‌وجوی استاد و پژوهشگر

Knut Reinertمشاهده پروفایل

استاد

• Algorithmic Bioinformatics
• Genomics
• Proteomics
• +۳ مورد دیگر

Prof. Knut Reinert is a Professor of Algorithmic Bioinformatics at the Freie Universität Berlin (FU) and a Max Planck Fellow at the Max Planck Institute for Molecular Genetics (MPI). He leads the Algorithmic Bioinformatics (ABI) group at FU and the Efficient Algorithms for Omics Data group at MPI. His research focuses on developing mathematical models and algorithms for analyzing biomedical mass data, including sequence analysis, proteomics, and omics data. Reinert is a key contributor to the SeqAn C++ library, a widely used bioinformatics software tool, and has led initiatives such as the Intel® Parallel Computing Center to accelerate NGS data analysis. Education: Diploma in Computer Science (1994, Max Planck Institute for Computer Science & Universität des Saarlandes), PhD (1999, Dr. Ing., Universität des Saarlandes). Postdoctoral research at Celera Genomics (1999–2002). Research interests include algorithm engineering for genome comparison, high-throughput sequencing data analysis, and bioinformatics software development. His work emphasizes scalable solutions for omics data interpretation, with applications in metagenomics, proteomics, and computational biology. Key achievements include leadership in de.NBI (German Network for Bioinformatics Infrastructure), the development of tools like SeqAn, Lambda, Fiona, and Ganon, and collaborations with institutions like the Max Planck Society and international partners. Awards include Max Planck Fellow status and Intel® PCC leadership. Grants and collaborations: German-Turkish research initiatives, DFG-funded RNA research projects, and leadership in EU-funded projects like Predict-IV. His lab actively engages in teaching at undergraduate and graduate levels, emphasizing innovative methods like e-learning and inverted classrooms.

Daniel Dietschمشاهده پروفایل

پژوهشگر

• Static Analysis
• Software Model Checking
• Formal Methods
• +۳ مورد دیگر

Dr. Daniel Dietsch is a researcher at the Department of Computer Science, Faculty of Engineering, University of Freiburg. He specializes in Static Analysis , Software Model Checking , and Formal Methods , with focus areas including Requirements Engineering, Modeling Processes, and Software Verification. Research Trends : His recent work centers on automated verification tools for software systems, addressing bitwise operations, race conditions, and hybrid models. Key contributions include the Ultimate framework series (Automizer, Kojak, Taipan, GemCutter, Referee) for SV-COMP competitions. Scientific Output : Over 140 publications since 2011, with significant activity in 2024 (53 entries) and 2023 (39 entries). Tools developed by his team are available via GitHub and web interface . Teaching Roles : Regularly instructs courses like Automata Theory , Program Verification , and Cyber-Physical Systems since 2011, including both theoretical and practical components. Collaborations : Works closely with Matthias Heizmann, Frank Schüssele, Dominik Klumpp, and Andreas Podelski on verification technologies.

• Computer Science
• Machine Learning
• Software Engineering
• +۳ مورد دیگر

David Wilson is an academic affiliated with the University of South Wales, Severn School of Radiology, and the Severn Deanery. He has extensive research interests in Computer Science, Machine Learning, Medical Imaging, and Human-Computer Interaction. Research Interests: His work spans fields like Software Engineering, Artificial Intelligence, and Data Science, with a focus on applications in healthcare and inclusive technology. Publications: He has contributed to recent research on generative AI for medical imaging, accessible making, and deep learning applications in biomedical contexts. Collaborations: Notable co-authors include Sharon Zhang, Naira Hovakimyan, and Lisa Moseley, reflecting interdisciplinary research in healthcare technology and machine learning.

• Virtual Reality
• Human-Computer Interaction
• Affective Computing
• +۴ مورد دیگر

Matias Volonte is a researcher affiliated with Northeastern University , Boston, MA, USA, focusing on virtual reality, human-computer interaction, and affective computing. His work investigates visual attention, emotion contagion, and behavioral modeling in VR environments. Key research areas: Virtual Human behavior, gaze analysis, user perception, and AI-driven interactions Collaborates with experts like Andrew T. Duchowski, Sabarish V. Babu, and Deyrel Diaz Research Trends : Recent publications (2025-2018) emphasize VR-based studies on embodied agents, including path modeling of attention , demographic bias evaluation , and emotional contagion in digital crowds . His work spans healthcare applications, educational AI, and cognitive modeling in immersive environments. Notable Contributions : Co-developed the HeadBox toolkit for facial blendshape animation in VR and explored trust dynamics with AI instructors. He also contributes to standardization of gaze analysis and multimodal interaction frameworks.

Erika Roldan Roaمشاهده پروفایل

استادیار مهمان

• Stochastic Topology
• First Passage Percolation
• Extremal Topological Combinatorics
• +۳ مورد دیگر

Erika Roldán Roa is a mathematician with academic affiliations at Ohio State University (Visiting Assistant Professor, 2019-2020) and Technische Universität München (Marie Skłodowska-Curie Fellow, 2020-2022). She holds a Ph.D. in Probability and Statistics from CIMAT (2018) and has conducted postdoctoral research at institutions like EPFL and Ohio State. Her work bridges stochastic topology, combinatorics, and educational technology, focusing on topics like cubical sliding puzzles, Eden growth models, and extremal topological problems in polyominoes. Education: Ph.D. in Probability and Statistics, CIMAT (2018) M.Sc. in Mathematics, CIMAT (2014) B.Sc. in Mathematics, Universidad de Guanajuato (2010) Research Interests: Her research spans stochastic topology, extremal combinatorics, and applications of discrete geometry to puzzles and games. She explores configuration spaces, topological properties of random structures, and innovative educational approaches like the Music Math Project, which integrates music and mathematics. Awards: Includes the Marie Skłodowska-Curie Fellowship (2020-2022), Arana-Ordaz Prize (2019), and Sofia Kovalevskaia Prize (2019). She has also received grants from CONACYT and CIMAT. Grants & Outreach: Developed workshops in marginalized communities using music and math, and contributed to software tools like the Eden Model analysis package. Active in science popularization through articles and outreach programs. Labs/Teams: Collaborated on projects like the Eden Model (topology analysis software) and extremal animal configurations, often involving interdisciplinary teams in mathematics and computer science.

Salim Ullahمشاهده پروفایل

پژوهشگر

• Approximate Computing
• FPGA-Based Hardware Accelerators
• Embedded Systems Design
• +۳ مورد دیگر

Salim Ullah is a researcher in the Department of Embedded Systems at Ruhr University Bochum. His work focuses on FPGA-based approximate computing, hardware accelerators, and embedded systems design. He leads the Embedded Systems Team, contributing to advancements in reconfigurable logic and neuromorphic computing. Research Interests: Approximate arithmetic circuits, FPGA design methodologies, neural network implementation on FPGAs Key Projects: AxOCS (approximate operator scaling), AxOMaP (mathematical programming for arithmetic operators), AxOSpike (spiking neural networks for operator design) Publications (2024-2020) highlight innovations in error resilience, quantization techniques, and hardware-software co-design. Collaborations include work on RISC-V emulation (NvMISC), energy-efficient multipliers, and embedded AI acceleration frameworks.

Martin Brieschمشاهده پروفایل

پژوهشگر

• Program Synthesis
• Genetic Programming
• Machine Learning
• +۳ مورد دیگر

Martin Briesch is a Research and Teaching Assistant at the Chair of Information Systems and Business Administration under Prof. Dr. Franz Rothlauf at Johannes Gutenberg University Mainz since March 2020. He holds a Master of Science in Management (2020) and a Bachelor of Science in Economics (2017), both from JGU Mainz. Roles: Research and teaching responsibilities, course coordination, and thesis supervision. Education: 2017–2020: M.Sc. Management, JGU Mainz 2014–2017: B.Sc. Economics, JGU Mainz Research Interests: Focuses on Program Synthesis , Genetic Programming , Machine Learning , Deep Learning , and Large Language Models . His work explores optimization techniques, evolutionary algorithms, and AI applications in problem-solving and decision support. Teaching: Leads courses such as "Introduction to Software Engineering" and "Introduction to Artificial Intelligence" since 2020. Supervises bachelor's and master's theses in information systems and business administration. Publications: Active researcher with contributions to genetic programming, program synthesis, and AI ethics. His work appears in venues like MKWI and Google Scholar.

Ruediger Ehlersمشاهده پروفایل

استاد

• Formal Methods
• Reactive Synthesis
• Automated Reasoning
• +۴ مورد دیگر

Ruediger Ehlers is a Professor for Embedded Systems at Clausthal University of Technology, focusing on formal methods , automated reasoning , and cyber-physical systems . His research aims to bridge formal methods and artificial intelligence to enhance the efficiency and reliability of computational systems. University: Clausthal University of Technology Institute: Institute for Software and Systems Engineering Research Interests: His work centers on making correct-by-construction design processes more efficient, particularly through reactive synthesis , verification of finite- and infinite-state systems , and runtime monitoring . He has developed tools like slugs and planet for synthesis and neural network verification. Publications Trends: Recent articles emphasize temporal logic , reinforcement learning under constraints , and algorithm engineering for practical applications in manufacturing and quantum computing. Scientific Awards: Volkswagenstiftung Momentum endeavor (2023) Grants and Projects: He leads the EU/H2020 Project SAFE-10-T (2021) and secured funding from the German Science Foundation (2016) for synthesizing GUI code. His Open-MPW-6 program (2023) involves hardware implementation of runtime monitoring.

Salar Mohtajمشاهده پروفایل

پژوهشگر

• Transfer Learning for Natural Language Processing
• Text complexity/readability prediction
• Evaluation of Large Language Models
• +۱ مورد دیگر

Dr. Salar Mohtaj is a senior researcher at the German Research Center for Artificial Intelligence (DFKI) and affiliated with TU Berlin's Quality and Usability Lab. He holds a PhD from TU Berlin (2024), specializing in transfer learning for harmful content detection. His work focuses on NLP applications in fake news/hate speech detection, LLM evaluation, and text complexity analysis. Education: Bachelor's: Information Technology, Shahrood University of Technology (Iran) Master's: Information Technology, Amirkabir University (Iran) PhD: TU Berlin (2024), supervised by Prof. Sebastian Möller Research Interests: Transfer learning for NLP, LLM evaluation, text complexity prediction, and detection of harmful content. He leads projects on multimodal fake news detection and semantic text similarity models. Recent Contributions: Developed the Hamtajoo plagiarism detection system, contributed to the KIALOPRIME dataset, and led EU-funded projects on AI ethics and disinformation. His work bridges NLP techniques with societal challenges like misinformation. Awards & Grants: Received Software Campus funding (2019-2024) for projects on sentiment analysis in fake news. Collaborates with Holtzbrinck Publishing Group and Deutsche Telekom. Labs & Affiliations: Speech & Language Technology group at DFKI and Quality and Usability Lab at TU Berlin. Teaches Natural Language Processing courses at TU Berlin and KI Campus.

Rainer Dyckerhoffمشاهده پروفایل

استاد

• Multivariate Statistics
• Data Depth
• Central Regions
• +۳ مورد دیگر

Rainer Dyckerhoff is an apl. Professor at the Department of Economic and Social Statistics within the WiSo Faculty (Faculty of Management, Economics and Social Sciences) at the University of Cologne. He holds a PhD in Economics (Dr. rer. pol.) from Helmut Schmidt University Hamburg (1994) and a Diploma in Mathematics from Technical University Darmstadt (1988). His research focuses on multivariate statistics, data depth, computational statistics, and decision theory. He has held academic positions at the University of Cologne since 1995, including roles as Scientific Assistant (1995–2001), Academic Council member (2001–2006), and Akademischer Oberrat (since 2006). His work emphasizes methodological advancements in statistical depth functions, central regions, and computational algorithms for multivariate data analysis. Notable contributions include exact computation of halfspace depth and depth-based nonparametric tests. His publications span top journals like Computational Statistics and Data Analysis and Annals of the Institute of Statistical Mathematics . No scientific awards are explicitly mentioned in the provided text. Rainer Dyckerhoff has been affiliated with the Department of Economics at Helmut Schmidt University Hamburg during his early career (1989–1995). His current role combines research leadership and academic service in statistical methodology.

Wong, Su Leenمشاهده پروفایل

پژوهشگر

• Materials Science
• Crystal Plasticity Modeling
• Twinning-Induced Plasticity (TWIP)
• +۴ مورد دیگر

Dr. Wong Su Leen is a researcher at the Max-Planck-Institut für Eisenforschung GmbH under the Max Planck Society . Her work focuses on crystal plasticity modeling of advanced high-strength steels and aluminum alloys, particularly investigating TRIP (transformation-induced plasticity) and TWIP (twinning-induced plasticity) effects. Key research areas: Multi-scale material simulation, ab-initio guided flow stress models, and microchemistry-dependent strengthening mechanisms. Co-developer of the DAMASK simulation toolkit , a widely used software for crystal plasticity and damage modeling in polycrystals. Her publications emphasize computational approaches to understanding deformation mechanisms, stacking fault energy effects, and stress distribution in face-centered cubic metals. She has presented at international conferences including Thermec , ICAA , and COMPLAS . While no students or awards are explicitly listed, her collaborative work with institutions like National Institute for Materials Science (Japan) and University of Düsseldorf highlights her interdisciplinary impact.

• Gravitational Wave Astronomy
• Precision Interferometry
• Instrumental Noise Modeling
• +۳ مورد دیگر

Dr. Olaf Hartwig is a Senior Scientist at the Albert Einstein Institute (AEI) in both Potsdam and Hannover. His research focuses on precision interferometry and fundamental interactions, specifically for the Laser Interferometer Space Antenna (LISA) project. He holds a PhD in Physics from the University of Hannover (2021) and has held postdoctoral positions at SYRTE - Observatoire de Paris and AEI. His work bridges instrumental modeling, data processing, and noise reduction for space-based gravitational wave detection. Education: BSc and MSc in Physics (University of Hannover), PhD in Physics (University of Hannover via AEI Potsdam) Current Roles: Split post-doctoral position between AEI Potsdam (global fit for LISA) and AEI Hannover (Performance and Operations team) Research Interests revolve around space-based gravitational wave detectors, with emphasis on: Instrumental Modeling - Refining noise models, addressing data gaps, and mitigating glitches in LISA data Data Processing - Developing simulations, performance models, and software tools like PyTDI Detector Optimization - Clock synchronization, light-travel time estimation, and onboard optical delay compensation Publication Trends (15 most recent) show a focus on LISA instrumentation, with key topics including time-delay interferometry (TDI), stochastic gravitational wave background reconstruction, instrumental noise characterization, and intersatellite ranging. His work frequently integrates GPU acceleration, Python-based toolchains, and end-to-end simulation pipelines.

Juliane Siegerisمشاهده پروفایل

استاد

• Software Engineering
• Business Information Systems
• Workflow Modeling
• +۳ مورد دیگر

Juliane Siegeris is a Professor of Computer Science in the field of Software Engineering at the Berlin University of Applied Sciences (HTW) , where she has taught since 2010. She is renowned for founding and leading the women's degree program in Computer Science and Business Administration, and for initiating the PROFIT mentoring program in 2012 to support female students in IT careers. Since 2020, she has been a board member of the Einstein Center Digital Future . Education: Studied Computer Science at Humboldt University of Berlin; earned a doctorate from Technical University of Berlin (TU). Research Interests focus on software engineering, workflow modeling, and addressing gender disparities in STEM. She has pioneered single-sex education initiatives and explored digital participation frameworks. Publications highlight interdisciplinary work blending technical rigor with social innovation, particularly in workflow model compositions and gender-sensitive educational strategies. Awards: 2021: Exhibition panel in 'Berlin – Capital of Female Scientists'. Leadership and Advocacy: Siegeris has consistently advocated for practical training in academia and co-developed the women's bachelor program at HTW Berlin, emphasizing hands-on learning and industry alignment. Labs and Collaborations: She contributes to the Einstein Center Digital Future , advancing research at the intersection of technology and societal impact.

Daniel Sonntagمشاهده پروفایل

استاد

• Intelligent User Interfaces
• Natural Language Processing
• Information Retrieval
• +۷ مورد دیگر

Prof. Dr.-Ing. Daniel Sonntag serves as Scientific Director of Interactive Machine Learning at the German Research Center for Artificial Intelligence (DFKI) and holds an Endowed Chair of Applied Artificial Intelligence at University of Oldenburg. He leads multiple significant research initiatives including No-IDLE (Interactive Deep Learning Enterprise), MASTER (Mixed reality ecosystem for teaching robotics), Ophthalmo-AI (intelligent eye care diagnostics), pAItient (AI applications in medicine), and XAINES (explainable AI with narratives). His research spans intelligent user interfaces, natural language processing, information retrieval, dialogue systems, common-sense modeling, and explainable machine learning methods for cognitive computing. His work particularly focuses on multimodal-multisensor interfaces for medical and health systems and Industry 4.0 applications. His research has had industrial impact, with SmartWeb's multimodal interaction design forming the technical infrastructure for Apple's Siri. His recent publications demonstrate strong trends in medical AI applications, particularly in eye tracking, radiology report generation with enhanced interpretability, and interactive federated learning frameworks. His work consistently bridges theoretical AI advances with practical medical and industrial applications. German High Tech Champion Award (2011) As a principal investigator, Sonntag leads national and European projects funded by the Federal Ministry of Education and Research, Federal Ministry for Economic Affairs and Energy, Federal Ministry of Health, and Horizon Europe. He has supervised numerous researchers including Michael Barz, Jan Zacharias, and Alexander Prange across multiple projects. His research group has successfully transitioned technologies to industry, with former researchers joining companies like Apple, Wacom, and Semvox. Sonntag's laboratory work centers on the Interactive Machine Learning department at DFKI, with strong connections to medical institutions and industry partners. His team develops cognitive assistance systems, mixed reality applications for smart factories, and AI-based diagnostic support tools, particularly in ophthalmology and radiology.

• Robotics
• Machine Learning
• Electrical Engineering
• +۳ مورد دیگر

Xinyu Qin is a Professor at the Department of Electrical and Computer Engineering within the School of Information Engineering at Guangdong University of Technology. His research focuses on advanced robotics, signal processing, and integrated circuit design, contributing to fields like multi-manipulator systems and Delta-Sigma modulators. Education: Affiliated with prestigious institutions through collaborative research Research Interests: Robotics, Machine Learning, Electrical Engineering His recent publications (2023-2025) demonstrate expertise in robotic task allocation, high-speed circuit design, and explainable AI for healthcare. Award-winning work includes Interactive Explainable Deep Survival Analysis (2024) and SVP: Safe and Efficient Speculative Execution Mechanism through Value Prediction (2023). Key collaborations involve Guoxing Wang and Liang Qi across 16 records. Current projects involve optimizing convolutional neural network accelerators, analyzing atmospheric river impacts on Greenland's crustal deformation, and advancing MASH Delta-Sigma modulator architectures. His work bridges theoretical innovation with practical applications in smart energy systems and autonomous robotics.