جست‌وجوی استاد و پژوهشگر

Pascale Daran-Lapujadeمشاهده پروفایل

استاد

• Microbial Metabolism
• Synthetic Biology
• Yeast Engineering
• +۳ مورد دیگر

Prof. Pascale Daran-Lapujade is a Full Professor at Delft University of Technology’s Faculty of Applied Sciences and Director of the Applied Sciences Graduate School overseeing ~500 PhD candidates. Her research focuses on microbial systems, particularly the yeast Saccharomyces cerevisiae and non-conventional yeasts, aiming to understand how microbes respond to environmental stimuli and engineer them into efficient biocatalysts. Her work integrates quantitative physiology, genomics, and cell biology, with a recent emphasis on synthetic biology to construct yeast platforms enabling rapid metabolic pathway remodelling. This research was supported by an ERC Consolidator Grant. Research Themes: Central carbon metabolism regulation and uncoupling growth from product formation. Techniques include molecular biology, bioreactor cultivation, transcriptomics, fluorescence microscopy, and collaborations in proteomics/metabolomics. She also leads the ENW-XL proposal on microbial electron control and is a Senior Editor at FEMS Yeast Research. Advising & Grants: Supervises numerous PhD/MSc students and postdocs. Notable grants include ERC Consolidator and ENW-XL (collaboration with Wageningen/VU). Lab activities emphasize metabolic engineering, pathway swapping, and synthetic chromosome design. Labs/Teams: Pascale Daran-Lapujade Group, collaborating with international partners (BOKU Vienna, Utrecht, Milan). Key projects include yeast platform development and glycolysis humanization.

John Coffinمشاهده پروفایل

استاد

• Retrovirology
• Viral Genetics
• Molecular Virology
• +۴ مورد دیگر

John Coffin serves as American Cancer Society Research Professor and Distinguished Professor at Tufts University School of Medicine within the Department of Molecular Biology and Microbiology, where he has held continuous appointments since 1982. His research focuses on retrovirus-host interactions, viral DNA integration mechanisms, and endogenous retroviral evolution. B.A. in Biological Sciences, Wesleyan University (1967) Ph.D. in Biochemistry, University of Wisconsin (1972) Dr. Coffin's research program investigates retroviral receptor interactions, viral DNA integration specificity, control of viral gene expression, retroviral genetic variation mechanisms, and host-virus coevolution through endogenous proviral fossils. His laboratory employs avian and murine retroviral models to dissect fundamental virological processes relevant to HIV and other retroviral pathogens. Analysis of his recent publications reveals dominant research themes in HIV reservoir dynamics, endogenous retrovirus expression in cancer, and retroviral taxonomy. His work consistently bridges molecular virology with clinical implications, particularly regarding HIV persistence mechanisms during antiretroviral therapy and the role of clonal expansion in viral reservoir maintenance. National Academy of Sciences Member American Cancer Society Research Professorship Distinguished Professor title at Tufts University Dr. Coffin directs multiple NIH-funded research programs including the Retrovirus Evolution and Cancer project (2016-2023) and previously led the NCI's HIV Drug Resistance Program. His teaching portfolio includes regular instruction in Animal Virology and graduate seminars since 2013. He maintains active roles as Scientific Advisory Board member at Aaron Diamond AIDS Research Center and serves on editorial boards for Virology and PNAS.

• RNA Interference
• Gene Regulation
• piRNA Pathways
• +۴ مورد دیگر

Craig C. Mello is the Blais University Chair in Molecular Medicine and a Distinguished Professor at UMass Chan Medical School, where he leads research in the RNA Therapeutics Institute. He holds multiple appointments across the T.H. Chan School of Medicine and Morningside Graduate School of Biomedical Sciences, including positions in the Cancer Center, Program in Molecular Medicine, and RNA Therapeutics and Biology Program. Brown University: BS Biochemistry Harvard University: PhD Cellular/Developmental Biology Mello's research focuses on RNA-mediated gene regulation, with groundbreaking work on RNA interference (RNAi) that earned him the 2006 Nobel Prize in Physiology or Medicine. His laboratory investigates how cells use short segments of genetic code to find and regulate matching information, with particular emphasis on piRNA pathways, germline determination, and CRISPR-mediated genome editing tools for C. elegans. His work has revealed fundamental mechanisms of epigenetic inheritance and transgenerational silencing. Analysis of Mello's recent publications (2018-2024) shows continued innovation in RNA biology and genome editing. His research spans molecular mechanisms of piRNA production, Argonaute protein function, transgenerational epigenetic inheritance, and CRISPR optimization. The work demonstrates increasing sophistication in understanding how RNA pathways maintain genome integrity and regulate gene expression across generations, with significant implications for therapeutic applications. Nobel Prize in Physiology or Medicine (2006) Howard Hughes Medical Investigator Blais University Chair in Molecular Medicine Mello has mentored numerous graduate students through UMass Chan's Interdisciplinary Graduate Program and MD/PhD Program, with his laboratory serving as a training ground for future scientists in RNA biology. His research has been supported by continuous funding from the Howard Hughes Medical Institute since 2000 and various NIH grants. The laboratory maintains strong collaborations with researchers worldwide, particularly in the fields of small RNA biology and genome editing. The Mello laboratory operates at the forefront of RNA biology research, with specialized facilities for C. elegans genetics, molecular biology, and advanced microscopy. The team includes postdoctoral researchers, graduate students, and technical staff working collaboratively to unravel the complexities of RNA-mediated gene regulation and develop novel genome editing approaches.

• Software Engineering
• Software Quality Assurance
• Data-Intensive Methods
• +۳ مورد دیگر

Morgan Ericsson is a professor at Linnaeus University's Faculty of Technology, Department of Computer Science and Media Technology. He has coordinated the Linnaeus University Centre for Data Intensive Sciences and Applications and leads the research group Data Intensive Software Technologies and Applications (DISTA). His work spans software engineering, quality assessment, and machine learning applications in system design. Research coordinator, DISA Faculty member, Linnaeus University His research focuses on defining and measuring software quality through data-driven approaches, including code metrics, documentation evaluation, and machine learning. He develops methods to balance performance, safety, and functionality in complex systems. Recent publications involve generative adversarial networks for log end identification, copula-based metrics aggregation, and graph convolution networks for code-architecture mapping. Key themes include automated classification, density analysis, and educational software tools. Ericsson has led projects like "HPC for SME" and "In-line Visual Inspection Using Unsupervised Learning," while contributing to software infrastructure for quality assessment and mobile learning frameworks.

Jan Vogesمشاهده پروفایل

پژوهشگر

• Genomic Data Compression
• DNA Data Storage
• Bioinformatics
• +۳ مورد دیگر

Dr. Jan Voges is a Research Group Leader at the Institute for Information Processing and the L3S Research Center at Leibniz University Hannover, where he leads the BioAI Lab. He has held previous research leadership positions at the same institution (2022-2024), CIMA University of Navarra (2024-2025), and maintains a visiting position at the Peter L. Reichertz Institute for Medical Informatics. Dr. Voges' research spans the intersection of computer science, genomics, and medical informatics, with a focus on: Developing AI methods for multi-omics data analysis DNA sequencing data compression and storage 3D genome reconstruction Single-cell RNA sequencing data modeling International standardization of genomic data His recent work demonstrates a strategic shift toward integrating artificial intelligence with genomic data analysis, particularly for medical applications. The development of Genie, the first open-source ISO/IEC encoder for genomic data, represents a significant contribution to genomic data standards. His research shows strong translational potential, bridging computational methods with clinical applications as evidenced by his P4D Dashboard project for depression cohort monitoring. Dr. Voges has received recognition for his work, most notably earning his Dr.-Ing. degree with distinction in 2022. His active participation in ISO/IEC standardization committees and collaborations with international institutions demonstrates the impact of his work beyond traditional academic boundaries. As a supervisor, Dr. Voges maintains a focused lab structure with 3 PhD students, emphasizing quality mentorship and opportunities for students to contribute to high-impact projects with real-world applications. His lab provides unique opportunities at the cutting edge of genomic data science, with exposure to international standardization processes and interdisciplinary collaborations.

Lydia Contrerasمشاهده پروفایل

استاد

• Biomolecular Engineering
• Biotechnology
• RNA Biology
• +۵ مورد دیگر

Lydia Contreras is the Paul D. and Betty Robertson Meek Centennial Professor in Chemical Engineering at the University of Texas at Austin, and Associate Dean of Postdoctoral Studies. She holds affiliations with the Molecular Biophysics Portfolio Program and the Institute for Cellular and Molecular Biology. Her expertise spans biomolecular engineering, RNA-protein interactions, and environmental health. Contreras earned a B.S.E. from Princeton University (2003), a Ph.D. in Chemical and Biomolecular Engineering from Cornell University (2008), and completed postdoctoral fellowships at the Wadsworth Center and Vienna’s Max F. Perutz Laboratories. Her research explores RNA and protein engineering to address health challenges, including diagnostics for RNA-related diseases and understanding environmental chemical impacts (e.g., formaldehyde exposure). She leads a lab with over 20 researchers and has pioneered studies on molecular recognition and extremophile adaptations. Awards include the American Academy of Microbiology Fellowship (2023), NSF CAREER Award, and multiple equity-in-engineering recognitions. Contreras is a vocal advocate for diversity in STEM, contributing to initiatives like the Annual Biomedical Research Conference for Minority Students and editorial roles at mSystems and Proceedings of the National Academy of Sciences . Her work bridges molecular biology, environmental science, and education to drive interdisciplinary innovation.

Mehmet Emreمشاهده پروفایل

استادیار

• Programming Languages
• Software Engineering
• Program Analysis
• +۳ مورد دیگر

Mehmet Emre is an Assistant Professor in the Department of Computer Science at the University of San Francisco, where he focuses on programming languages and software engineering. He earned his PhD and MS in Computer Science from UC Santa Barbara (2022, 2021) and a BS in Computer Engineering from Boğaziçi University (2015). PhD, Computer Science, UC Santa Barbara (2022) MS, Computer Science, UC Santa Barbara (2021) BS, Computer Engineering, Boğaziçi University (2015) His research centers on program analysis with a focus on memory and thread safety, formal verification, and compiler design. Key areas include: Automated reasoning about memory safety in C programs Formalizing theoretical computer science in Lean Efficient parsing algorithms Programming language tooling for education His publications reflect work on C-to-Rust translation safety, cross-language clone detection, JavaScript analysis optimization, and compiler-related education tools. Research trends emphasize bridging formal verification with practical software transitions and improving program analysis efficiency. He directs the PL Lab at USF and coordinates the CS Tutoring Center, supporting students in courses like Programming Languages (CS 345) and Automata Theory (CS 411).

• Software Testing
• Real-Time Systems
• Embedded Software
• +۳ مورد دیگر

Wafa Hasanain is a Contract Instructor at Carleton University's School of Computer Science (SCE), within the Faculty of Engineering and Design. She holds a Ph.D. and focuses on software testing methodologies, real-time embedded systems, and automated testing frameworks. Her research emphasizes clone detection in industrial test code, state-based online testing, and software verification using tools like SPIN Model Checker and RTEdge frameworks. Education: Ph.D. (exact discipline unspecified) Research Interests: Hasanain’s work bridges software engineering and embedded systems. She explores automation in testing complex systems, leveraging clone detection to improve test code maintainability and applying formal verification techniques to real-time software. Her methodologies aim to enhance software reliability through systematic analysis and tool-driven validation. Article Trends: Her publications (2013–2020) concentrate on testing challenges in real-time embedded systems and industrial test code. Key themes include state-based approaches, clone analysis for code maintenance, and integration of model checkers like SPIN with frameworks like RTEdge. These contributions address scalability and accuracy in automated testing environments. Awards & Grants: No scientific awards or grants explicitly mentioned in the text. Advising & Labs: No formal advisees or labs listed, though her research may involve collaborations with teams focused on embedded systems testing.

Jim Buckleyمشاهده پروفایل

استاد

• Software Reengineering
• Empirical Software Engineering
• Information Seeking in Software Engineering
• +۷ مورد دیگر

Jim Buckley is a Professor in the Department of Computer Science & Information Systems at the University of Limerick, and a Principal Investigator at Lero – the Irish Software Research Centre. He holds a BSc in Biochemistry from the National University of Ireland, Galway (1989), followed by an MSc (1994) and PhD in Computer Science (2002) from the University of Limerick. His research focuses on software reengineering, empirical software engineering, and source code analysis, with notable contributions to clone detection, software architecture recovery, and AI-driven code generation. He led the TREES Centre, a €6M industry-funded initiative, and currently oversees three research teams at Lero investigating large-scale clone detection, deep learning architecture recovery, and AI-generated source code. His work intersects technical innovation with societal impact, such as ethical software engineering and pandemic response technologies like contact tracing apps. Key research themes include software architecture consistency, feature location, and developer experience optimization. He has published over 118 peer-reviewed articles and received a Research Impact award from Lero. His contributions span open-source tool development, empirical studies in software practices, and interdisciplinary projects addressing global challenges like public health and cryptocurrency equity. Education: BSc Biochemistry, National University of Ireland, Galway (1989) MSc Computer Science, University of Limerick (1994) PhD Computer Science, University of Limerick (2002) Awards: Research Impact Award, Lero (2021) Labs/Teams: TREES Centre (Trustworthy, Responsible, Efficient Engineering of Software) Three core Lero teams: Clone Detection, Architecture Recovery, and AI-Code Generation

Jean-Guy Schneiderمشاهده پروفایل

استاد

• Software Engineering
• Quantum Computing
• Cloud Computing
• +۴ مورد دیگر

Prof. Jean-Guy Schneider is a Professor and Associate Dean (Education) in the Faculty of IT at Monash University. He holds a PhD in Computer Science from the University of Bern, Switzerland, and has over 20 years of experience in higher education. His research focuses on reliable software technologies, including component-based systems, cloud/mobile computing, quantum software, and agile methodologies. He actively contributes to software engineering education and industry-relevant research. His key research areas include energy-efficient IoT architectures, machine learning model security (e.g., MLGuard project), and quantum computing abstractions. Recent work emphasizes optimizing workflows for energy/performance trade-offs and addressing challenges in open-source ML projects. Prof. Schneider has published extensively on topics like service virtualization, Docker container monitoring, and anomaly detection in cloud systems. He supervises PhD candidates in software engineering for machine learning and quantum computing.

Katalin Fejes Tóthمشاهده پروفایل

دانشیار مهمان

• Molecular Biology
• Genetics
• RNA Biology
• +۳ مورد دیگر

Katalin Fejes Tóth is a Visiting Associate Professor in the Department of Molecular Biology and Genetics AG at Cornell University's College of Agriculture and Life Sciences (CALS). She leads research at the interface of chromatin and RNA biology, employing interdisciplinary methods including biochemistry, molecular/cellular biology, genetics, and computational approaches to study gene expression regulation and ribonucleoprotein complex functions. Education: Medical Degree (2001): Semmelweis University, Budapest, Hungary PhD in Biochemistry and Biophysics (2004): University of Heidelberg, Germany (lab of Karsten Rippe) Research Focus: Her work explores how chromatin influences transcription and how RNA-protein complexes regulate chromatin dynamics. Notable contributions include discovery of promoter/body-associated small non-coding RNAs in mammals and an alternative RNA capping mechanism (7mG capping). Contact: 358 Biotechnology Building, Ithaca, NY 14853 Email: kft@caltech.edu Professional Background: Postdoctoral training (with Gregory Hannon at Cold Spring Harbor Lab) focused on small RNA regulation and RNA cloning strategies for transcript analysis. Established an independent lab at Caltech in 2010 before joining Cornell.

• Machine Learning
• Artificial Intelligence
• Reinforcement Learning
• +۳ مورد دیگر

Alexander Ilin is a Visiting Professor and part-time teacher in the Department of Computer Science at Aalto University, specializing in Artificial Intelligence and Machine Learning. He holds roles in both the Computer Science - Artificial Intelligence and Machine Learning (AIML) research area and the Professors of Practice group. His research focuses on Machine Learning, Reinforcement Learning, and Deep Learning applications, with contributions to areas like neural networks, generative models, and healthcare informatics. Dr. Ilin earned a Doctoral degree in Engineering and Technology from Helsinki University of Technology in 2006. His work aligns with UN Sustainable Development Goals, particularly in advancing education and innovation. Key projects include the Finnish Center for Artificial Intelligence (FCAI) and the APPIA project on privacy-aware AI applications. His research explores cutting-edge topics such as diffusion models for dynamical systems, reinforcement learning for robotics, and self-supervised forecasting in healthcare. He has led projects like APPIA (2020–2021) and FCAI (2020–2026), securing grants from the Academy of Finland and Business Finland. His work bridges theory and practice, with applications in autonomous systems, nanotechnology, and medical diagnostics. Notable activities include visiting research at the UK Met Office Hadley Centre and presentations at top conferences like NeurIPS and AAMAS. His lab focuses on scalable AI solutions for real-world challenges, emphasizing ethical AI and privacy-preserving techniques.

• Software Engineering
• Software Testing
• Machine Learning Systems
• +۴ مورد دیگر

Dr. Iftekhar Ahmed is an Associate Professor in the Department of Informatics at the University of California, Irvine’s Donald Bren School of Information & Computer Sciences. His research focuses on software engineering methodologies, emphasizing software testing, analysis, and accessibility. He holds a Ph.D. in Computer Science from Oregon State University (2018) and a B.S. in Computer Science and Engineering from Shahjalal University of Science and Technology, Bangladesh (2007). Education: Ph.D., Computer Science, Oregon State University, 2018 B.S., Computer Science and Engineering, Shahjalal University of Science and Technology, Bangladesh, 2007 His research integrates artificial intelligence, data mining, and empirical software engineering to improve software quality and safety. Key areas include: Automated testing frameworks for large systems Bug prediction models for code vulnerabilities Accessibility testing tools (e.g., Ma11y mutation framework) Safety-critical systems like autonomous vehicles Recent work explores AI-driven code generation, prompt engineering, and mitigating biases in software tools. His team received a $1.2M grant in 2022 to enhance accessibility testing tools. Ahmed also investigates human factors in software development, including developer mental health and tool adoption challenges. His publications address critical issues like code smells in quantum computing, commit message quality, and Jupyter notebook bug patterns. He actively participates in industry-academia collaborations, such as the 2023 Southern California Software Engineering Symposium.

Christof Ferreira Torresمشاهده پروفایل

استادیار

• Blockchain Security
• Smart Contract Analysis
• Decentralized Finance (DeFi)
• +۴ مورد دیگر

Christof Ferreira Torres is an Assistant Professor at the Department of Computer Science and Engineering (DEI) at Instituto Superior Técnico (IST), University of Lisbon, and a researcher at INESC-ID in the Distributed, Parallel and Secure Systems (DPSS) group. His research focuses on program analysis, software security, and blockchain systems, particularly addressing vulnerabilities in smart contracts and decentralized finance (DeFi). He holds a Ph.D. from the University of Luxembourg and Technical University of Munich under Professors Radu State and Claudia Eckert. Education: Ph.D. in Computer Science, 2022 (University of Luxembourg & TU Munich) Postdoctoral Fellow at ETH Zurich (2022–2023) His research interests include blockchain security, MEV (Maximal Extractable Value) analysis, cross-chain interoperability, and privacy in Web3. Notable contributions include frameworks like Horus for attack detection in smart contracts and Elysium for automatic vulnerability patching. He actively participates in academic service, serving on program committees for major conferences like S&P, CCS, and USENIX. Recent work highlights cross-chain arbitrage dynamics, privacy leaks in web wallets, and centralized risks in blockchain infrastructure. His findings emphasize the need for decentralized solutions to counteract threats to blockchain liveness and finality. Key Awards: TLDR Research Fellowship (2024) Excellent Doctoral Thesis Award (2022) UBRI Impact Award (2022) He teaches courses on information security, dependable systems, and computer science foundations at IST and ETH Zurich. His work bridges theoretical computer science with practical blockchain security challenges, addressing both academic and industry needs.

Esa Pitkänenمشاهده پروفایل

استاد مدعو

• Machine Learning
• Biomedicine
• Computational Biology
• +۴ مورد دیگر

Esa Pitkänen is a Senior Researcher at the Institute for Molecular Medicine Finland (FIMM) and holds an Adjunct Professorship in the Department of Computer Science at the University of Helsinki. He is actively involved in the Doctoral Programme in Integrative Life Science, supervising doctoral research. His work bridges computational methods with biomedical applications, focusing on machine learning, genomics, and systems biology. His research interests include developing predictive models using neural networks for medical imaging (e.g., amyloid PET analysis), genomic studies of cancer subtypes (e.g., AML and B-cell lymphomas), and bioinformatics tools for variant discovery. He leads projects funded by the Juselius Foundation and the Academy of Finland, emphasizing personalized medicine and translational oncology. Pitkänen’s recent publications highlight advancements in automated medical coding via deep learning, genomic insights into iron metabolism disorders, and single-cell transcriptomic approaches to cancer therapy optimization. His contributions span computational biology, precision medicine, and multi-omics integration in healthcare. He manages the Meilahti Biodata facility and has supervised doctoral student Kaasinen. His work often involves collaborations across disciplines, addressing challenges in liquid biopsy, mutational signatures, and AI-driven diagnostics.