جست‌وجوی استاد و پژوهشگر

• Computational Biology
• Biophysical Modeling
• Cancer Modeling
• +۱۲ مورد دیگر

João Carlos Lopes de Carvalho is a Full Professor at the Faculty of Science and Technology of the University of Coimbra, Portugal, where he has held academic positions since 1987. He was promoted to Associate Professor in 2003 and attained Full Professor status in 2022. His research spans computational biology, biophysical modeling of cancer, and experimental particle physics, with extensive participation in international collaborations including CERN (CPLEAR, ATLAS) and DESY (HERA-B). PhD in Experimental Particle Physics, University of Liverpool (1994) Aggregate Title (Habilitation), University of Coimbra (2003) Bachelor’s Degree in Physics, University of Coimbra (1987) His research focuses on the computational modeling of biological systems, particularly the bioelectric mechanisms underlying cancer initiation and progression. He develops discrete models such as cellular automata and cellular Potts models to simulate tissue dynamics in 2D and 3D, with applications in bladder and prostate cancer. Earlier in his career, he contributed to particle detector development, data acquisition, and physics analysis in high-energy experiments. The recent trends in his publication record show a strong emphasis on multiscale modeling of tumor growth, angiogenesis, and the role of bioelectricity in carcinogenesis. His work integrates computational simulations with biological insights, targeting early cancer detection and therapeutic strategies. Articles are published in high-impact journals such as Scientific Reports , PLOS Computational Biology , and Bulletin of Mathematical Biology . Supervised or co-supervised 4 PhD theses and 19 master’s dissertations Participated in over 50 research projects, coordinating 9 Principal investigator on grants including FCT projects PTDC/EMD-TLM/7289/2020 and PTDC/BIA-CEL/31743/2017 Involved in major collaborations: CERN (ATLAS, CPLEAR), DESY (HERA-B), SNO+ João Carlos Lopes de Carvalho has been a key figure in advancing computational approaches in oncology and biophysics. His work bridges physics, engineering, and life sciences, contributing to both fundamental understanding and potential clinical applications in cancer research.

Hironori Washizakiمشاهده پروفایل

استاد

• Systems Engineering
• Software Engineering
• Machine Learning
• +۳ مورد دیگر

Hironori Washizaki is a Professor at Waseda University 's School of Fundamental Science and Engineering and a Visiting Professor at the National Institute of Informatics. He serves as IEEE Computer Society 2025 President and has led initiatives in software engineering, ML design patterns, and IoT systems. His work bridges academia and industry through roles at SYSTEM INFORMATION CO.,LTD. and eXmotion Co., LTD. Research Interests: His work spans software engineering, quality assurance, ML/IoT design patterns, and education innovation. He leads the SmartSE professional education program and standardizes software engineering bodies of knowledge through ISO/IEC/JTC1/SC7/WG20 . Scientific Awards: Golden Core Member (IEEE CS) Spirit of Computer Society Award KDDI Foundation Award Science and Technology Award, MEXT Best Paper Awards at ICSE, CSEE&T, and IWESEP Leadership & Grants: He has secured major grants (JSPS, MEXT) and held editorial roles at IEEE Transactions on Emerging Topics in Computing, IJSEKE, and IEICE journals. As IEEE CS Japan Chapter Chair and SEMAT Japan Chapter Chair , he fosters international collaborations. Labs & Teams: He leads the Global Software Engineering Laboratory at Waseda, focusing on traceability, reuse, and quality. This lab drives projects like ProMeTA (program metamodel taxonomy) and Trace ANY (software maintenance metrics).

Michael L. Collardمشاهده پروفایل

استادیار

• Software Engineering
• Source Code Analysis
• Program Comprehension
• +۵ مورد دیگر

Michael L. Collard is an Assistant Professor of Computer Science at the Department of Computer Science , Buchtel College of Arts and Sciences , The University of Akron . He teaches courses in iOS Development and Software Engineering , focusing on modern programming languages like Swift and Objective-C. Research Interests: His work centers on software engineering , source code analysis , and iOS development . Key areas include forward static slicing, code stereotyping, traceability, and tools like srcML for mixed-language software infrastructure. Publications: Recent publications address scalable static slicing ( srcSlice ), source code modeling with XML, stereotype-based feature location, and tools for software visualization. Awards: Recipient of NSF grants (CISE CRI 2013, REU Supplement 2013) and the Most Influential Paper Award at ICPC'13 for his 2003 work on C++ fact extraction. Students: Mentored undergraduate researcher Brian Kovacs through NSF-funded REU. Labs: Cofounder of SDML, LLC , commercializing research tools for source code analysis.

Jonathan I. Maleticمشاهده پروفایل

استاد

• Software Engineering
• Software Evolution and Maintenance
• Program Comprehension
• +۶ مورد دیگر

Dr. Jonathan I. Maletic is a Professor in the Department of Computer Science at Kent State University , where he has been since 2001. He served as Interim Chair in 2010 and has a secondary role as Principal at srcML LLC , providing software solutions for code analysis. Education: Ph.D. in Computer Science from Wayne State University (1995) M.S. in Computer Science from Wayne State University (1989) B.S. in Computer Science from University of Michigan-Flint (1985) His research spans software evolution , program comprehension , software visualization , and eye tracking studies . He is a leading figure in the srcML and iTrace projects. Recent publications focus on quantum programming analysis , code naming semantics , and eye-tracking data correction . Notable trends include the integration of NLP in code analysis and quantum software engineering . Scientific Awards: Kent State President’s Faculty Excellence Award (2025) Most Influential Paper at SCAM (2021) Kent State Outstanding Research Award (2021) IEEE TCSE Distinguished Paper (2020) Mining Software Repositories Foundational Contribution (2020) Dr. Maletic has advised 40+ graduate students , including Ph.D. and M.S. candidates, with notable alumni in academia and industry. He has secured multiple NSF grants for projects like srcDiff.org (2023, $750K) and expanding srcML language support (2020, $652K). He leads the Software Development Laboratory (SDML) and iTrace teams, fostering collaborative research in code analysis and eye-tracking infrastructure.

• Computational Mechanics
• Numerical Simulation
• Shape Optimization
• +۱۲ مورد دیگر

Stefanie Elgeti is Associate Professor and Private Lecturer at the Chair for Computational Analysis of Technical Systems (CATS), Faculty of Mechanical Engineering, RWTH Aachen University. She previously held a professorship in lightweight design at TU Vienna starting in 2019. Her research integrates computational mechanics with manufacturing process optimization, focusing on plastics extrusion, injection molding, and high-pressure die casting. Diploma in Mechanical Engineering, majoring in 'Manufacturing Techniques for Microsystems' PhD (2011): 'Free-Surface Flows in Shape Optimization of Extrusion Dies' Habilitation (2016): 'CAD-Conforming Finite Element Methods in Engineering Design' Her research centers on solving inverse problems in manufacturing through numerical simulation. She employs advanced techniques such as free-surface flow modeling, non-Newtonian material models, spline-based finite elements, and PDE-constrained shape optimization. Her group simulates entire process chains from filling to solidification and warpage prediction, enabling design optimization of cavities and cooling systems. The recent publications (2022–2024) reveal a strong trend toward integrating artificial intelligence—particularly physics-informed neural networks and Bayesian optimization—into traditional simulation workflows. There is increasing emphasis on warpage compensation, shape optimization of extrusion dies, and modeling of biomedical and environmental systems, showcasing a broadening scope from industrial manufacturing to interdisciplinary applications. She is actively involved in academic service, having served as vice-spokesperson of GAMM-Juniors (2013–2014) and currently co-chairing the ECCOMAS Young Investigator Group. While no formal awards are listed, her leadership roles and editorial contributions reflect significant recognition in the computational mechanics community. Prof. Elgeti advises students and leads multiple research initiatives at CATS, including work groups focused on production engineering, fluid-structure interaction, and INTERESST. Her team develops model hierarchies and digital twins for industrial processes, aiming to bridge simulation and real-world manufacturing through intelligent, adaptive systems.

Kim A. Sharpمشاهده پروفایل

دانشیار

• Computational Biophysics
• Protein-Ligand Interactions
• Molecular Dynamics
• +۷ مورد دیگر

Kim A. Sharp is an Associate Professor in the Department of Biochemistry and Biophysics at the Perelman School of Medicine, University of Pennsylvania. He is also Chair of the Graduate Group in Biochemistry and Molecular Biophysics and affiliated with the Genomics and Computational Biology program. Education: BSc.Hons. in Biophysics, Leeds University, 1978 Ph.D. in Chemistry, University of British Columbia, 1985 Dr. Sharp's research centers on understanding molecular recognition processes involving proteins, ligands, drugs, and nucleic acids using theoretical and computational methods. His work emphasizes Poisson-Boltzmann electrostatics , molecular and Brownian dynamics , and Monte Carlo simulations . Key areas include protein-ligand binding energy calculations, simulation of proteins in reverse micelles, viral genome packaging, and novel computational approaches to analyze protein shape. The published works reflect a strong focus on computational biophysics and molecular energetics , particularly in quantifying electrostatic contributions to binding, solvation effects, and macromolecular shape descriptors. His research bridges physical chemistry principles with biological applications, especially in nucleic acid interactions and drug binding. Scientific Awards: No awards explicitly listed in the source text. Dr. Sharp advises graduate students through the Biochemistry and Molecular Biophysics Graduate Group. While specific grants are not mentioned, his sustained publication record in top-tier journals indicates active funding and research leadership. He maintains a laboratory focused on developing and applying advanced computational tools to fundamental problems in molecular biophysics.

• Condensed Matter Theory
• Computational Physics
• Materials Science
• +۳ مورد دیگر

Walter Lambrecht is a Perkins Professor of Physics at Case Western Reserve University. His research focuses on first-principles computational methods in condensed matter theory, particularly density functional theory (DFT) and many-body perturbation theory (GW method), applied to novel materials such as semiconductor nitrides, halide perovskites, and layered ultra-thin materials. Education: Lic. Sc., University of Gent (1977) Dr. Sc., University of Gent (1980) Research Interests: Theoretical modeling of electronic and vibrational properties in complex materials. Defects and doping effects in semiconductors. Development of computational tools for band structure and optical property analysis. Collaborations: Works closely with experimental groups, including a team at Victoria University in Wellington, New Zealand, on rare-earth nitrides. Collaborates with Mark van Schilgaarde at Arizona State University on computational method development. Key Projects: Investigation of II-IV-N2 semiconductors and their defect physics. Stability and electronic behavior of halide perovskites for solar cells. Spin-orbit effects in layered materials like MoS2 and V2O5. Magnetic exchange interactions in Mn-doped ScN and gadolinium pnictides.

Gangadhar Andaluriمشاهده پروفایل

استادیار

• Emerging Contaminants
• Advanced Oxidation Processes
• Environmental Remediation
• +۱۲ مورد دیگر

Gangadhar Andaluri is an Assistant Professor (tenure track) in the Department of Civil and Environmental Engineering at Temple University's College of Engineering. He earned his PhD in Engineering from Temple University in 2011, an MS in Chemical Engineering from Villanova University (2006), and a BS in Chemical Engineering from Osmania University (2003). Prior to his current role, he served as an NTT faculty member, Senior Lab Manager, and post-doctoral fellow within the same department. His research is centered on emerging contaminants , including PFAS, microplastics, and antibiotic resistance genes, with a strong emphasis on advanced oxidation technologies , thermal treatment , and advanced analytical methods such as LC/MS/MS and GC/MS/MS. He also investigates reverse and forward osmosis , chemical sensors , and applies artificial neural networks and computational quantum chemistry to environmental problems. He leads the Thermal Technologies and Analytical Methods Laboratory and serves as the faculty advisor for the Society of Environmental Engineers and Scientists (SEES) at Temple. The recent publications (2023–2025) reflect a consistent focus on environmental contaminants in urban watersheds, particularly in the Delaware and Schuylkill Rivers. Key themes include the detection and degradation of PFAS using sonochemical methods, monitoring of microplastics and 6PPDQ, fate of antibiotic resistance genes in biofilm reactors, and development of rapid extraction techniques (FaEx) for contaminants in food and environmental matrices. These works span disciplines of environmental engineering, analytical chemistry, and materials science, with methodologies emphasizing innovation in detection, modeling, and remediation. Scientific Awards: No formal scientific awards listed in the provided text. Advising and Grants: Dr. Andaluri advises the Society of Environmental Engineers and Scientists (SEES) student chapter. While no specific grant funding is detailed in the text, his active research program and publication record suggest ongoing project support. There is no explicit mention of graduate student advising or formal mentorship roles beyond the SEES chapter. Labs and Teams: He leads the Thermal Technologies and Analytical Methods Laboratory , which focuses on experimental and computational approaches to environmental contamination. His collaborative work, evident in co-authorship with researchers like R. Suri, Y. Lin, and V.K. Ponnusamy, indicates strong interdisciplinary team engagement across environmental engineering, chemistry, and biomedical applications.

• Additive Manufacturing
• Sustainable Manufacturing
• Polymer Engineering
• +۱۲ مورد دیگر

Alberto Giubilini is a Research Fellow in the Department of Management and Production Engineering (DIGEP) at Politecnico di Torino, where he also serves as an external lecturer and teaching assistant. He is a member of the Interdepartmental Center IAM@PoliTo – Integrated Additive Manufacturing, contributing to cutting-edge research in sustainable and advanced manufacturing technologies. His academic affiliations span multiple programs, including Mechanical Engineering, Materials Science, Automotive Engineering, and Design and Communication. His research is centered on additive manufacturing , with a strong emphasis on environmental sustainability and the use of biopolymers, bioresorbable composites, nanocellulose, and recycled polymers . Key technologies in his work include fused filament fabrication, selective laser sintering, twin-screw extrusion, and high-pressure homogenization. His expertise bridges materials science and industrial process engineering, particularly in polymer and metal additive manufacturing. The recent publications (2024–2025) highlight a clear trend toward sustainable material development and process optimization in 3D printing. His work explores biocomposite fabrication, energy efficiency in filament production, laser processing of reflective metals like copper, and simulation of metal printing distortions. These studies reflect a multidisciplinary approach combining materials innovation, process scalability, and environmental impact assessment. Alberto Giubilini actively contributes to teaching across various degree programs. He has served as a course collaborator in subjects such as Additive Manufacturing and Reverse Engineering , Additive Manufacturing Systems and Materials , and Advanced Computer-Aided Mold Design , demonstrating his commitment to engineering education. He is also a recipient of the Open Badge Learning to Teach (L2T), underscoring his pedagogical development. He is involved in the IAM@PoliTo research center, which fosters interdisciplinary collaboration in additive manufacturing, integrating materials, design, and production engineering. This environment supports innovation in both academic and industrial applications of 3D printing technologies.

Karl Grieshopمشاهده پروفایل

مدرس

• Evolutionary Genetics
• Genomics
• Bioinformatics
• +۱۲ مورد دیگر

Karl Grieshop is a Lecturer in Genomics and Bioinformatics at the School of Biological Sciences, University of East Anglia, where he also leads the Grieshop Lab. He is an active member of the Centre for Ecology, Evolution and Conservation and currently accepting PhD students through the ARIES DTP program. University: University of East Anglia School: School of Biological Sciences Position: Lecturer in Genomics and Bioinformatics Lab: grieshoplab.com Education and Career Background: Lecturer (2023–present), University of East Anglia Postdoctoral Fellow (2019–2023), University of Toronto & Stockholm University Ph.D., Uppsala University (2012–2017) M.S. and B.S., University of Cincinnati Karl Grieshop's research centers on evolutionary genetics, particularly the causes and consequences of genetic variation maintained through fitness trade-offs across sexes, environments, and life stages. His work integrates experimental evolution, quantitative genetics, genomics, and modeling in Drosophila melanogaster , with broader implications for conservation, pest management, and understanding genetic disease. His interdisciplinary approach spans lab experiments, bioinformatics, and mathematical modeling. His 15 most recent publications (with 5 most recent shown) demonstrate a strong focus on sexual conflict, dominance reversals, gene expression divergence, and the genomic architecture of adaptation. These studies frequently involve experimental evolution, transcriptomics, and population genetic simulations, often using Drosophila as a model system. Scientific Awards: Benzelius Award (2022) John Maynard Smith Prize (2019) Karl actively mentors students and collaborates internationally, with research extending to birds, plants, and other arthropods. He has been involved in securing PhD funding through the ARIES DTP and provides extensive training in Drosophila husbandry, bioinformatics, statistics, and scientific writing. His lab contributes significantly to understanding how genetic constraints shape evolutionary trajectories and adaptation in changing environments. Lab and Research Group: The Grieshop Lab (grieshoplab.com) conducts interdisciplinary research on evolutionary trade-offs, using experimental and computational approaches. The lab fosters collaboration and offers opportunities for postgraduate research in evolutionary genomics and adaptation.

Nimer Murshidمشاهده پروفایل

استاد آموزشی

• Nanomaterials
• Chemistry
• Environmental Science
• +۳ مورد دیگر

Nimer Murshid is an Assistant Teaching Professor in the Department of Chemistry at Carnegie Mellon University in Qatar. His research focuses on nanomaterials, environmental science, and computational chemistry, with a particular emphasis on aerogels, nanofluids, and machine learning applications in material characterization. He has contributed to studies on oil and dye removal using advanced materials, thermal radiation analysis, and sustainable energy solutions. His work frequently employs principal component analysis (PCA) and other computational tools to optimize material performance and environmental remediation strategies. Research Interests include: Development and application of nanomaterials for biomedical and environmental uses Thermal and fluid dynamics analysis in nanofluid systems Machine learning-driven material optimization Sustainable energy integration in desalination and wastewater treatment Environmental remediation using advanced composites Recent articles highlight innovations in aerogel efficiency evaluation, nanotube functionalization for cancer diagnosis, and wind energy applications for desalination. Collaborative efforts emphasize sustainable technologies and interdisciplinary approaches to global environmental challenges. Grants and advising activities are not explicitly detailed in the provided information, though his role as a teaching professor suggests active involvement in academic mentorship within the Department of Chemistry.

Daniel Pageمشاهده پروفایل

مدرس ارشد

• Cryptography
• Cryptographic Engineering
• Side-Channel Attacks
• +۶ مورد دیگر

Dr. Daniel Page is a Senior Lecturer in Computer Science at the University of Bristol, specializing in Cryptography and Information Security. His research bridges cryptographic engineering, hardware/software security, and programming language design. Research interests: Cryptographic engineering (hardware and software implementation of cryptographic primitives), side-channel attacks, fault attacks, secure processor architectures, domain-specific compiler optimizations for cryptography (e.g., AES, ECC), and cross-disciplinary studies in software defects and game glitch analysis. Recent research trends focus on hardware/software co-design for security, including novel instruction set extensions (ISEs) to mitigate leakage in masked implementations and protect against cache-based side-channel attacks. His work spans both theoretical and applied domains, with collaborations in digital security policy and embedded systems. Projects include DiScriBe (Digital Security by Design Social Science Hub, 2020–2024) and EPSRC-funded initiatives (2019–2022/2023). He has contributed datasets like GMOPST14 (University of Bristol, 2014).

• Programming Languages
• Reversible Computation
• Quantum Computing
• +۷ مورد دیگر

Robin Kaarsgaard Sales is an Assistant Professor on the tenure track in the Department of Mathematics and Computer Science at the University of Southern Denmark, Faculty of Science and Engineering. His research focuses on the theoretical foundations of programming languages, with an emphasis on reversible computation, quantum programming, and categorical semantics. His research interests span Programming Languages , Reversible Computation , Quantum Computing , Categorical Semantics , Functional Programming , and Formal Methods . He investigates how invertibility and reversibility can be integrated into programming models, particularly in the context of quantum computation, using tools from category theory and mathematical logic. His recent publications, appearing in high-impact venues such as POPL and ICFP, demonstrate a consistent focus on compositional models of reversible and quantum computation. Key themes include invertible functional programming, quantum semantics via groupoids and morphisms, and program transformations for tail recursion in reversible settings. These works reflect a deep integration of theoretical computer science with mathematical structures. Robin was a participant in the research project Landauer Meets von Neumann: Reversibility in Categorical Quantum Semantics (2020–2022), funded by the Danish Research Council, which underscores his active role in advancing foundational aspects of quantum computing. He has collaborated extensively with prominent researchers including Jacques Carette, Chris Heunen, and Amr Sabry. His work has been featured in public media, including TV2 News and regional press, highlighting both his research impact and community engagement. He is also referenced on Wikipedia and has a presence on academic platforms such as ORCID, Scopus, and Mendeley. He is affiliated with a research group active in programming language theory and quantum computation, contributing to a growing international network in reversible and quantum computing. His ongoing work continues to explore the mathematical underpinnings of computation, aiming to bridge theory with practical language design.

• Artificial Intelligence
• Cybersecurity
• Programming Languages
• +۹ مورد دیگر

Sandra Greiner is an Assistant Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), where she conducts research in artificial intelligence, cybersecurity, and programming languages. Her work is centered on improving the reliability and adaptability of control software in cyber-physical production systems through advanced software engineering techniques. Her research interests include software variability modeling , design by contract , and the application of generative AI in automating software development tasks. She focuses on ensuring high reliability in software-intensive systems, particularly in industrial automation contexts. Her work bridges theoretical computer science with practical software engineering challenges. The recent publications highlight a strong trend in leveraging AI for software contract generation, enhancing feature tracing with reliable knowledge, and managing variability in complex production systems. Her research contributes to model-driven engineering, software product lines, and intelligent software assistance, with a consistent emphasis on empirical validation through case studies. Sandra actively collaborates with researchers across Europe, particularly in Austria and Germany, contributing to top-tier conferences such as SPLC, MODELS, and GPCE. Her work has been published in high-impact journals and conference proceedings, reflecting active engagement in the global software engineering community. She is affiliated with the IMADA research center at SDU, as evidenced by her institutional email. No formal awards or fellowships are mentioned in the provided data. Sandra advises no publicly listed students, and there is no indication of lab leadership or team management in the text. However, her collaborative publications suggest participation in research teams focused on software product lines and AI-driven software engineering.

Charles A. DiMarzioمشاهده پروفایل

دانشیار

• Optics
• Microscopy
• Coherent Detection
• +۱۰ مورد دیگر

Charles A. DiMarzio is an Associate Professor in the Department of Electrical and Computer Engineering at Northeastern University , with affiliations in Mechanical and Industrial Engineering and Bioengineering. His research spans advanced optical imaging techniques for biomedical applications. Education: PhD in Electrical and Computer Engineering, Northeastern University (1996) MS in Physics, WPI BS in Engineering Physics, University of Maine Research interests focus on optics , microscopy , coherent detection , hyperspectral imaging , and collagen studies . His group develops hardware and computational methods for multi-modal biomedical imaging , including the Keck 3-D Fusion Microscope . Recent publications highlight innovations in: Collagen monomer orientation measurement Super-resolution structured illumination Ultrasound-modulated light imaging Coded-illumination Fourier ptychography Awards include: SPIE Fellow (2022) SPIE Senior Member (2021) Optica Senior Member (2021) He supervises capstone design projects and teaches graduate courses in Optics for Engineers and undergraduate classes in Circuits and Signals , Electronics , and Subsurface Sensing . Collaborations include the Gordon Center for Subsurface Sensing , ALERT , and institutions like Memorial Sloan Kettering Cancer Center.