جست‌وجوی استاد و پژوهشگر

• Software Development
• Computer Science
• Artificial Intelligence
• +۷ مورد دیگر

Fadi Deek is a Professor in the Department of Informatics at the New Jersey Institute of Technology. His academic career spans multiple domains, with a focus on software development, artificial intelligence, and blockchain technology. Deek’s research outputs and collaborations reflect his interdisciplinary expertise and long-standing contributions to computational fields. Current Affiliation: Department of Informatics, New Jersey Institute of Technology Former Affiliation: Office of the Provost, New Jersey Institute of Technology Deek’s research interests include collaborative software development, problem-solving in computational contexts, and the integration of AI in educational environments. He has contributed to advancements in groupware systems and information systems, with recent work focusing on blockchain-based identity management and medical informatics applications. His research trends over the past five years indicate active engagement in decentralized key management systems, AI-driven image captioning, and blockchain evaluation frameworks. Notable recent publications include work on contextual image captioning and simplifying electronic health records using large language models. Deek has secured federal grants, including a National Science Foundation (NSF) award for the C2PRISM project (2007–2013), which aimed to integrate computation and communication in science and mathematics education. His collaborations with colleagues like Bukiet and Lubliner highlight his team-based research approach. Contact: DEEK@njit.edu

Stephen Laycockمشاهده پروفایل

استاد

• Molecular Graphics
• Scientific Visualization
• Virtual Reality (VR)
• +۵ مورد دیگر

Stephen Laycock is a Professor of Computer Graphics at the University of East Anglia (UEA), affiliated with the School of Computing Sciences. He holds additional roles as Associate Dean for Admissions in the Science Faculty. His expertise spans Molecular Graphics, Scientific Visualization, Virtual Reality (VR), Haptics, and GPU programming, with applications in Cultural Heritage preservation and biomedical research. Laycock earned his PhD in 2005 and has been a faculty member since 2005, advancing to Professor in 2024. His research focuses on interactive molecular docking, haptic rendering, and GPU-accelerated algorithms. Notable projects include the development of DockIT software for molecular docking and collaborations in precision agriculture and ornithological migration tracking. Laycock’s work has been recognized with the 2017 Biophysics and Physicobiology Editors’ Choice Award. He teaches computer graphics and GPU programming, and actively supervises PhD students in interdisciplinary areas like virtual reality and haptics. Key initiatives include the Digital Preservation and Immersive Heritage project and GPU-accelerated agricultural monitoring systems.

Donghyung Leeمشاهده پروفایل

استادیار

• Statistical Genomics
• Bioinformatics
• Biostatistics
• +۳ مورد دیگر

Donghyung Lee is an Assistant Professor in the Department of Statistics at Miami University. His research focuses on statistical genomics and bioinformatics, particularly in developing computational tools for analyzing genomic data. He holds a Ph.D. in Statistics from Stony Brook University (2011). Dr. Lee’s work emphasizes applications in psychiatric genetics, single-cell RNA sequencing, and genomic imputation. He has developed influential R packages like GAUSS and ZMIX for analyzing cosmopolitan cohorts and estimating ancestry proportions. His research also addresses challenges like batch effect correction in single-cell data and detecting hidden variation in transcriptomes. His recent studies include genome-wide association studies of anxiety disorders, co-expression analyses of schizophrenia genes, and pathway methods to uncover molecular mechanisms of psychiatric disorders. His contributions to statistical frameworks for genomic data analysis have enhanced precision in psychiatric GWAS and functional genomics.

Sebastian Böckerمشاهده پروفایل

استاد

• Metabolomics
• Bioinformatics
• Machine Learning
• +۷ مورد دیگر

Prof. Sebastian Böcker leads the Chair of Bioinformatics at the Institute of Computer Science, Friedrich Schiller University Jena. His lab focuses on metabolomics data analysis, computational mass spectrometry, and algorithm development for biological applications. Affiliations: HUMAN doctoral network (EU Horizon), AS-MS project (TMWWDG/ERDF), International Max Planck Research Schools Research Focus: Metabolite identification, retention order prediction, computational modeling of molecular diversity Recent publications highlight advancements in retention order index prediction, molecular diversity estimation, and large-scale query processing. The lab collaborates with Max Planck Institutes for Chemical Ecology and Biogeochemistry. Scientific Awards ERC Advanced Grant recipient (2025) His team includes PhD student Nils Haupt and the independent Bio Systems Analysis group led by Prof. Peter Dittrich. The lab develops software tools like SIRIUS+CSI:FingerID and participates in EU-funded harmonization of metabolomic analysis methods.

Michael Hildebrandمشاهده پروفایل

استاد

• Pain Research
• Neuroscience
• Translational Medicine
• +۲ مورد دیگر

Michael Hildebrand is a Professor in the Department of Neuroscience at Carleton University and an Affiliate Investigator at The Ottawa Hospital. He serves as Associate Vice-Provost (Graduate Student Affairs), overseeing graduate policies, student crisis mediation, and thesis defense processes across the university. His educational background includes a PhD in neurophysiology from the University of British Columbia (UBC), followed by an industrial R&D fellowship at NeuroMed Pharmaceuticals and an academic postdoctoral fellowship at Sick Kids Hospital. Hildebrand's research focuses on spinal mechanisms of pain processing using molecular, pharmacological, electrophysiological, and behavioral approaches. His lab bridges translational gaps between basic science and clinical needs by studying acute/chronic pain states in both rodent and human spinal cord models. Key interests include sexual dimorphism in pain pathways , T-type calcium channel functions , and NMDA receptor subunit contributions to identify novel pain treatment targets. Analysis of his 15 most recent publications reveals dominant trends in sex-specific pain mechanisms, human spinal cord translational models, and molecular targets like calcium channels and NMDA receptors. His work consistently integrates rodent and human tissue studies to address chronic pain's clinical challenges. Scientific recognition includes: Ronald Melzack, Canadian Journal of Pain Paper of the Year Award (2023) Hildebrand mentors undergraduate, graduate, and postdoctoral researchers while securing major funding from NSERC, CIHR, MITACS, and industry partners. His leadership extends to national roles including Chair of the Canadian Pain Society's Scientific Program Committee. The Hildebrand Lab operates within Carleton's Health Sciences Building, utilizing pioneering human spinal cord preclinical assays alongside animal models to investigate pain mechanisms and therapeutic interventions.

Serdar Bozdagمشاهده پروفایل

دانشیار

• Machine Learning
• Computational Biology
• Bioinformatics
• +۵ مورد دیگر

Serdar Bozdag is an Associate Professor in the Department of Computer Science and Engineering at the University of North Texas, with a joint appointment in Mathematics. He serves as Director of the Center for Computational Life Sciences, focusing on interdisciplinary research at the intersection of computational methods and biological systems. His research expertise spans machine learning applications in bioinformatics, multi-omics data integration, and network biology. Key areas include developing algorithms for disease biomarker discovery, integrating genomic, transcriptomic, and clinical data through graph neural networks, and creating computational tools for precision medicine. Notable contributions include frameworks like CanMod2 for co-regulatory module inference and CTDPathSim for pathway-based similarity analysis. Bozdag’s work bridges computer science and life sciences, addressing challenges in Alzheimer’s disease diagnosis, cancer systems biology, and plant-microbe interactions. He has pioneered methods for analyzing dynamic biological networks and temporal data patterns, with applications in drug response modeling and electronic health record analysis. His lab develops open-source software tools widely used in computational biology research. Current projects emphasize AI-driven approaches for multi-modal healthcare data fusion, predictive modeling of disease progression, and scalable solutions for big biological data. His research has implications for improving diagnostic accuracy, personalized treatment strategies, and understanding complex biological systems.

Catherine Letondalمشاهده پروفایل

استاد

• Human-Computer Interaction
• Tangible Interaction
• Participatory Design
• +۴ مورد دیگر

Catherine Letondal is a Professor of Computer Science and Human-Computer Interaction at ENAC (University of Toulouse). She leads the HCI group within the Interactive Computing Team and holds an HDR (Habilitation à Diriger des Recherches) and PhD in Human-Computer Interaction from the University of Paris-Sud. Her research focuses on systemic approaches to sustainability in design, tangible interaction, and participatory design methodologies. Her education includes advanced degrees in computer systems, philosophy, and engineering. She has extensive industry experience, including 15 years at the Institut Pasteur where she developed bioinformatics tools through participatory programming approaches. Key research areas include tangible interaction for aviation systems (e.g., cockpit design), systemic design for sustainability, and philosophical foundations of HCI. Recent work emphasizes integrating systems thinking into interactive system design to address ecological challenges. Notable achievements include awards at CHI 2009 and CHI 2013 for contributions to music composition tools and air traffic control interfaces. She co-supervises PhDs exploring systemic participatory design and sustainable air mobility. Her advising spans projects on shape-changing interfaces, gesture-based interaction for pilots, and sustainability in aviation systems. Research collaborations involve multi-disciplinary teams from sociology, economics, and aeronautics. Current projects include the AIRTIUS ANR initiative exploring touch technologies in cockpits and systemic design frameworks for rebound effects mitigation in ICT. Labs/Teams: Core member of the Interactive Computing Laboratory at ENAC; collaborates with aerospace engineering groups and sustainability-focused research consortia.

Myra Cohenمشاهده پروفایل

استاد

• Software Engineering
• Search-Based Software Engineering
• Highly-Configurable Software Testing
• +۵ مورد دیگر

Myra B. Cohen is a Professor and the Lanh and Oanh Nguyen Chair in Software Engineering at Iowa State University's Department of Computer Science, part of the College of Engineering. She previously held the Susan J. Rosowski Professorship at the University of Nebraska-Lincoln. Her research focuses on software testing of highly-configurable systems, search-based software engineering, and applications in synthetic biology and bioinformatics. Cohen holds a Ph.D. from the University of Auckland, M.S. from the University of Vermont, and B.S. in Agriculture from Cornell University. Education: Ph.D., Computer Science, University of Auckland, 2004 M.S., Computer Science, University of Vermont, 1999 B.S., School of Agriculture and Life Sciences, Cornell University Research Interests: Testing of cyber-physical systems and scientific software Combinatorial design applications in software assurance Synergies between software engineering and synthetic biology Configuration-aware testing for safety-critical systems Recent Projects: OPERA: Rural broadband solutions through open-source ecosystems Dependable AI-driven computational biology tools for KBase Blockchain fault tolerance modeling and measurement Self-adaptive mechanisms for unmanned aerial systems Awards: NSF CAREER Award AFOSR Young Investigator Award ACM Distinguished Scientist ASE Conference Fellow Leadership Roles: Program Co-Chair: ESEC/FSE 2020, ISSTA 2025 General Chair: ASE 2015 Steering Committee: ASE, ESEC/FSE, ISSTA Labs & Affiliations: Director: LaVA-OPs (Variability-Aware Assurance Lab) Center for Wireless, Communities and Innovation (WiCI) Bioinformatics & Computational Biology Graduate Program

Oliver Eulensteinمشاهده پروفایل

دانشیار

• Computational Biology
• Phylogenetics
• Bioinformatics
• +۵ مورد دیگر

Oliver Eulenstein is an Associate Professor at Iowa State University. He holds a Ph.D. in Computer Science from the University of Bonn (1998), an M.S. and B.S. from the University of Paderborn (1991 and 1987). His primary affiliations include the Computational Biology Laboratory. His research focuses on computational complexity, discrete algorithms, and computational biology, particularly phylogenetics. He explores topics such as phylogenetic networks, gene tree reconciliation, and genomic duplication models. Key research contributions include developing algorithms for phylogenetic analysis (e.g., RF-Net 2 for virus reassortment networks) and tools like Phylo-rs. His work bridges computer science and biology, addressing challenges in evolutionary genomics and biodiversity analysis. He has authored over 60 peer-reviewed articles, with recent emphasis on machine learning applications in phylogenetics and bioinformatics. Professional service includes editorial roles in computational biology journals and conference organization. His lab actively pursues interdisciplinary projects at the intersection of algorithms, data science, and biological systems.

Davide Mandelliمشاهده پروفایل

پژوهشگر

• Computational Biomedicine
• Molecular Dynamics Simulations
• Drug Design
• +۵ مورد دیگر

Dr. Davide Mandelli is a Researcher at the Research Center Jülich's Institute of Neuroscience and Medicine (INM-9), specializing in Computational Biomedicine. His work focuses on advancing computational methods for drug design, molecular dynamics simulations, and material science. Key areas include the development of QM/MM algorithms, exascale computing frameworks, and enhanced sampling techniques to study ligand-receptor interactions and material behavior at atomic scales. He contributes to high-performance computing projects like the JUWELS Booster supercomputer, optimizing algorithms for distributed systems. His research bridges computational chemistry, bioinformatics, and engineering, addressing challenges in pharmaceutical applications and nanotechnology. Notable projects include the MiMiC toolkit for multiscale simulations and studies on superlubricity in layered materials. Mandelli's work spans from fundamental physics to applied drug discovery, emphasizing interdisciplinary collaboration. His publications highlight innovations in parallel computing, free energy calculations, and the integration of machine learning into molecular simulations.

Norberto Díaz-Díazمشاهده پروفایل

استاد

• Artificial Intelligence
• Bioinformatics
• Computational Biology
• +۴ مورد دیگر

Dr. Norberto Díaz-Díaz is a Full Professor in the Department of Computer Science at Pablo de Olavide University. With expertise in Artificial Intelligence and Bioinformatics, he focuses on knowledge extraction and validation from biological databases, semantic similarity in gene networks, and educational technologies. His research spans computational methods for gene network validation, leveraging metabolic pathways and indirect gene-gene relationships. He has developed tools like GFD-Net and GRNCOP2 for Cytoscape, enhancing biological coherence analysis. Recent work explores AI in education, including student performance prediction models and competency development frameworks. Publications from 2011–2025 reflect interdisciplinary trends: 2011–2018: Bioinformatics tools and gene network validation 2019–2022: Semantic similarity, fuzzy gene associations, and digital health observatories 2023–2025: AI ethics, educational analytics, and social interaction analysis

• High-Performance Computing (HPC)
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Murali Emani is a researcher affiliated with Argonne National Laboratory, IL, USA. His work focuses on High-Performance Computing (HPC), machine learning, and artificial intelligence acceleration. Emani holds a PhD in Computer Science from the University of Edinburgh (2015). He specializes in optimizing large-scale systems, including performance evaluation of AI accelerators, transformer models, and neural architecture search. His research bridges HPC infrastructure with AI applications, addressing challenges in resource allocation, inference efficiency, and cross-architecture benchmarking. Key contributions include frameworks for GPU memory optimization (XUnified) and holistic performance evaluation of large language models across diverse hardware (e.g., BaKlaVa, Centimani). He collaborates extensively with institutions like the University of Chicago, NVIDIA, and MLCommons on initiatives such as DeepSpeed4Science and GenSLMs for genome-scale language models. His work frequently appears in top venues like IPDPS, SC, and Euro-Par. Emani’s research emphasizes practical system-level innovations, with applications spanning bioinformatics (SARS-CoV-2 evolutionary analysis), protein design, and exascale computing. He advocates for FAIR principles in HPC data management and contributes to open benchmarks like MLPerf HPC.

• Ultra-Wideband Technology
• Indoor Localization
• Ranging Systems
• +۵ مورد دیگر

Laura Flueratoru is a researcher at the University of Tampere, Finland, specializing in ultra-wideband technology for indoor localization systems. Her work focuses on developing robust, energy-efficient positioning solutions with particular expertise in non-line-of-sight mitigation and cross-platform implementations. She has established a strong publication record since 2017, with significant output between 2020-2023, indicating active ongoing research in wireless communications and localization technologies. Her research interests center around ultra-wideband communications for precise positioning, with emphasis on energy efficiency for constrained devices, platform independence across different UWB hardware, and innovative solutions for non-line-of-sight conditions that commonly degrade localization accuracy. She has developed self-learning approaches for detecting and mitigating signal interference, contributing to more reliable indoor positioning systems applicable in various real-world scenarios. Analysis of her publication trends shows consistent focus on ultra-wideband technology since 2017, with increasing specialization in energy efficiency and robustness from 2020 onward. Her work spans theoretical algorithm development, practical implementation challenges, and creation of open datasets for community validation. The research bridges electrical engineering, computer science, and practical applications in indoor positioning and wireless communications. Laura frequently collaborates with Elena Simona Lohan and Dragos Niculescu, with whom she has co-authored multiple publications across journals like IEEE Internet of Things Journal and conference venues including IPIN and MobiCom. Her collaborative network extends to researchers across Europe, particularly in Finland, Romania, and Switzerland, reflecting the international nature of her research in wireless communications. She has contributed significantly to open science through publicly available datasets, including ultra-wideband ranging measurements across multiple hardware platforms and BLE signal strength data for contact tracing applications. Her work on the FlexTDOA framework represents a notable contribution to robust time-difference of arrival localization techniques using ultra-wideband devices.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۶ مورد دیگر

Matthew Watson is a researcher at Durham University , Department of Computer Science, UK. His work spans Computer Science , Artificial Intelligence , and Human-Computer Interaction , with a focus on autonomous systems , semantic search , and pedagogical tools . Research Trends : Recent publications include applications of machine learning in adaptive cruise control , UAV-based wildlife tracking , and deep learning frameworks like KerasCV/KerasNLP. Earlier work involved mathematical combinatorics and cognitive modeling in dialogue systems. Collaborations : Co-authored with Navid Mohajer, Darius Nahavandi, Ashok K. Krishnamurthy, and others in domains like robotics, bioinformatics, and software engineering. Publications include 13 peer-reviewed articles from 2008–2025, covering topics in control systems , knowledge graphs , and algorithm design .

• Grid federation
• Utility and Cloud Computing
• Distributed Virtualization Management
• +۳ مورد دیگر

Constantino Vázquez Blanco is a Researcher in Grid & Virtualization Technology at the Distributed Systems Architecture Group, affiliated with the Department of Computer Architecture and Automatic Control at Universidad Complutense de Madrid. He holds a PhD in Distributed Computing Architecture and has extensive experience in Grid computing, cloud infrastructure, and open-source projects like OpenNebula and GridWay. His work focuses on distributed systems, virtualization, and resource management. He has contributed to major EU projects such as RESERVOIR and BEinGRID, advancing cloud and grid technologies. Education: M.E. in Computer Science (2002, UCM), MSc in Computing & Internet Systems (2003, King's College London), PhD in Distributed Computing Architecture (2012, UCM). Professional experience includes roles at Altien Solutions, British Telecom, and leadership in academic research projects. Research interests include Grid federation, cloud computing, utility computing, and distributed virtualization management. He has published on grid benchmarking, workflow execution, and middleware integration. His work emphasizes scalable resource provisioning and interoperability in distributed systems. Grants and Projects: Involved in EU-funded initiatives like RESERVOIR (cloud computing), BEinGRID (Grid experiments), and OpenNebula development. His contributions span academic-industry collaborations and open-source tool development. Contact: Located at the Facultad de Informática in Madrid, reachable via email tinova@fdi.ucm.es.