جست‌وجوی استاد و پژوهشگر

Matthew Haleمشاهده پروفایل

دانشیار

• Cybersecurity
• Web Services
• Software Engineering
• +۷ مورد دیگر

Dr. Matthew Hale is an Associate Professor of Cybersecurity and Director of the School of Interdisciplinary Informatics at the University of Nebraska at Omaha (UNO) College of Information Science and Technology. With a PhD from the University of Tulsa, he specializes in the intersection of cybersecurity, software engineering, behavioral psychology, and compliance certification. Since 2014, he has secured $5.7 million in grants (including $1.4M as PI) from NSF, NSA, DARPA, USDoT, and others. Director, School of Interdisciplinary Informatics (2018–present) Co-Chair, UNO-UNMC Faculty Senate Coordination Committee (2019–2021) Chair, IS&T Advisory Committee (2017–2021, 2023–present) Research Interests: Focus on cybersecurity training platforms, phishing prevention, IoT security, cloud compliance frameworks, and behavioral analysis of trust-propensity in digital environments. Article Trends: Recent work emphasizes crowd-sourced phishing detection, wearable device security, and multimodal behavioral analysis. Earlier studies explore compliance standards (e.g., SecAgreement), software self-adaptation, and agile team dynamics. Service Summary: Active in university governance, including Faculty Senate President (2019–2020), Diversity & Inclusion Task Force, and multiple sustainability and safety committees. Personal: Interests include cooking analogies to software engineering, philosophy, and Dungeons & Dragons.

Xinwei Maمشاهده پروفایل

دانشیار

• Econometrics
• Causal Inference
• Machine Learning
• +۳ مورد دیگر

Xinwei Ma is an Associate Professor in the Department of Economics at the University of California San Diego . He holds a Ph.D. from the University of Michigan (2019). His research focuses on econometric methodologies, causal inference, and their applications in healthcare and policy analysis. Key areas include machine learning integration in causal analysis, Mendelian randomization, and adaptive experimental designs. Recent work explores HIV care disengagement prediction using language models, principal component analysis for mixed data types, and fair adaptive experimentation frameworks. His methodological contributions include boundary-corrected local polynomial estimators and tools for mediation analysis in genomics. He has developed R packages such as lpcde and lpdensity for statistical estimation. Xinwei's research bridges theoretical econometrics with practical policy evaluation, emphasizing methodological rigor while addressing real-world challenges in healthcare and social sciences. His work has implications for public health interventions, tax policy design, and equitable algorithmic systems.

Xiao Fuمشاهده پروفایل

پژوهشگر ارشد

• Tumor Microenvironment Organization
• Computational Oncology
• Spatial Biology
• +۴ مورد دیگر

Xiao Fu is a Beatson Research Fellow and Group Leader at the Cancer Research UK Scotland Institute (CRUK Scotland Institute), part of the University of Glasgow's School of Cancer Sciences. She leads the Integrative Modelling research group, focusing on computational approaches to understand the tumor microenvironment (TME) organization and its role in cancer progression and therapy resistance. Her research program centers on developing computational methods to map spatial features of the TME and deconstruct principles underlying its organization through three primary approaches: Mechanistic models and computer simulations to investigate dynamic delineation of TME organization (such as sculpting of tumor/stroma architecture and spatial distribution of immune cells) Quantitative analysis of molecular and spatial tumor data to characterize architectural features (such as cell communities and neighborhoods) Machine learning frameworks to infer cellular and molecular mechanisms underlying characteristic TME architectures Dr. Fu applies these computational methods to spatial and molecular data from various solid tumors, particularly colorectal and pancreatic cancers, with the goal of discovering novel spatial TME features associated with clinical outcomes and identifying mechanisms for re-sculpting TME organization to improve therapy response. A key focus area is understanding immune exclusion, where T lymphocytes are spatially excluded from tumor nests, limiting the effectiveness of immune checkpoint blockade-based immunotherapy. Her scientific contributions have been recognized through several prestigious awards: 2022 Prostate Cancer Research grant (co-led with Erik Sahai and Anna Wilkins) 2012 Eli Lilly Fellowship in Biocomplexity, Indiana University Bloomington 2008 People's Scholarship, Nanjing University Dr. Fu maintains active collaborations with multiple research groups at the CRUK Scotland Institute and leads a multidisciplinary team comprising postdoctoral researchers, a cross-disciplinary research fellow, and a PhD student, reflecting her commitment to interdisciplinary research at the interface of computation and biology.

Richard Heeryمشاهده پروفایل

پژوهشگر ارشد

• Computational Biology
• Epigenetics
• Cancer Research
• +۳ مورد دیگر

Richard Heery is a Postdoctoral Research Associate in the School of Biological and Behavioural Sciences at Queen Mary University of London, working within Dr. Alexandre de Mendoza's research group. His computational biology expertise focuses on DNA methylation dynamics in cancer epigenomics and evolutionary inheritance patterns across eukaryotes. He earned his PhD in computational biology from the European Institute of Oncology (IEO) in Milan, where he developed methodologies for analyzing DNA methylation alterations and transcriptional consequences in oncological contexts. His educational background bridges oncology, epigenetics, and bioinformatics. Research centers on computational epigenomics, particularly DNA methylation variations in cancer progression and long non-coding RNA regulatory mechanisms. Key interests include epithelial-mesenchymal transition, tumour drug resistance, and cancer stem cell biology, utilizing high-throughput genomic data analysis to identify novel epigenetic drivers and therapeutic targets. Recent publications reveal a strong trajectory in cancer epigenome mapping, combining computational modeling with molecular oncology to uncover driver events in DNA methylation landscapes and lncRNA-mediated regulatory networks across multiple cancer types. As an active member of Dr. de Mendoza's team, he contributes to evolutionary epigenetics projects investigating conserved methylation patterns, utilizing the School of Biological and Behavioural Sciences' computational infrastructure within the G.E. Fogg Building.

Niko Popitschمشاهده پروفایل

پژوهشگر

• Genomics
• RNA Biology
• Transcriptomics
• +۳ مورد دیگر

Niko Popitsch is a researcher at the Max Perutz Labs, affiliated with the Department of Biochemistry and Cell Biology at the University of Vienna and Medical University of Vienna. He holds academic credentials including Dipl.-Ing. (Diplom-Ingenieur), Mag. (Magister), and Dr.techn. (Doctor of Technical Sciences). His research focuses on RNA biology, transcriptomics, and computational genomics, with a particular emphasis on RNA processing mechanisms, genome sequencing applications, and bioinformatics tool development. Key contributions include the Rnalib Python library for transcriptomics analysis and studies on RNA exosome function and immune signaling pathways. Popitsch's work spans diverse areas such as structural genomics, non-coding variants in rare diseases, and epigenetic regulation in neurons. He collaborates internationally on projects involving whole-genome sequencing diagnostics and the development of computational tools for genomic data analysis. Over 55 publications since 2008 highlight his prolific output in molecular biology, bioinformatics, and medical genetics. Awards and grants are not explicitly listed in the provided materials. His research contributes to UN Sustainable Development Goals related to health and innovation, particularly through advancements in genomic diagnostics and understanding genetic disorders. Advising activities and lab leadership are inferred from his role in collaborative research projects but specific student names or lab details remain unspecified.

Stefan Ameresمشاهده پروفایل

استاد

• RNA Biology
• MicroRNA Biogenesis
• Gene Regulation
• +۳ مورد دیگر

Stefan Ameres is a full Professor at the Max Perutz Labs, affiliated with the Department of Biochemistry and Cell Biology. His research focuses on RNA biology, particularly microRNA biogenesis, RNA silencing mechanisms, and transcriptome dynamics. He holds significant roles including Vice Dean at Max Perutz Labs since 2024. Key research interests include RNA processing pathways, epitranscriptomics, and the role of non-coding RNAs in cellular regulation. He has pioneered methods like SLAMseq and Rnalib for transcriptomics analysis, and contributed to understanding RNA exosome function and post-transcriptional regulation. Awards: DOC Award of the City of Vienna (2008) Elected Member of the Austrian Academy of Sciences (Young Academy) (2015) Diploma Award for academic excellence (2003) Recent work highlights include studies on ERH-mediated interferon signaling, RNA exosome assembly, and development of open-source diagnostic assays. His lab actively collaborates on projects like RiboTrace (RNA silencing dynamics) and RNAdeco (RNA decoration technologies). Activities include organizing Microsymposium on RNA Biology and serving in academic leadership roles.

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.

Tao Jiangمشاهده پروفایل

استاد

• Algorithms
• Computational Molecular Biology
• Genomics
• +۳ مورد دیگر

Tao Jiang is a Distinguished Professor in the Department of Computer Science and Engineering at the University of California, Riverside (UCR). He holds academic affiliations with the Algorithms and Computational Biology Lab, Genetics Graduate Program, Institute for Integrative Genome Biology, and Center for Plant Cell Biology. His research focuses on algorithm design, computational molecular biology, and finite automata complexity. He has held visiting positions at Tsinghua University and the Shanghai Center for Bioinformation Technology. Education: B.S. from University of Science and Technology of China (1984), Ph.D. from University of Minnesota (1988). Former faculty at McMaster University (1989–2001). Research Interests: Algorithmic techniques for string/tree/graph problems, approximation algorithms, Kolmogorov complexity applications, computational genomics, isoform inference, metagenomics, and algorithmic bioinformatics tools like PedPhase, TISHunter, MSOAR, and IsoLasso. Grants: Funded by NSF (EAGER, ABI) and NIH (NIDDK). Collaborations with Frances Sladek, Thomas Girke, and James Borneman. Teaching: CS 141 (Intermediate Data Structures), CS 238 (Algorithmic Techniques in Computational Biology), CS 150 (Automata/Formal Languages), and CS 260 (Bioinformatics Seminar). Office hours in Winston Chung Hall. Professional Contributions: Editorial board roles at Journal of Combinatorial Optimization, BMC Bioinformatics, and Algorithmica. Recent conference involvement at RECOMB 2023 and ISMB/ECCB 2023.

David Harris-Birtillمشاهده پروفایل

مدرس ارشد

• Medical technology
• Image analysis
• Signal processing
• +۱۱ مورد دیگر

Dr. David Harris-Birtill is a Senior Lecturer in the School of Computer Science at the University of St Andrews, where he conducts interdisciplinary research in medical technology and artificial intelligence. He is affiliated with the Centre for Research into Ecological & Environmental Modelling and actively supervises postgraduate research students. Research Interests: His work spans medical imaging, signal processing, ambient sensing, remote pulse oximetry, photoacoustics, photothermal therapy, and machine learning—particularly deep learning applications in digital pathology and healthcare diagnostics. His research contributes to UN Sustainable Development Goals related to health and well-being. Recent Research Trends: His recent publications (2023–2024) focus on AI-driven medical diagnostics, including automated cervical biopsy reporting, colorectal cancer biomarker detection using foundation models, and remote photoplethysmography for non-invasive vital sign monitoring. These works demonstrate a strong emphasis on applying deep learning to small and complex biomedical datasets. Scientific Awards: Best Paper Award, LABELS @ MICCAI 2020 Winner, Converge Challenge KickStart Award, 2016 Grants and Projects: He has led or co-investigated multiple funded projects, including I-CAIRD (Industrial Centre for AI Research in Digital Diagnostics), EPSRC Global Challenge Research Fund initiatives, and collaborations on millimetre wave radar sensing. He has also contributed to open datasets and software tools in medical imaging and human motion tracking. Labs and Teams: He is involved in AI and medical imaging research groups at St Andrews, collaborating with experts in digital pathology and clinical medicine, including Professor David Harrison. His work is highly collaborative, involving interdisciplinary teams across computer science and medicine.

• Cardiology
• Physiology
• Nutrition
• +۱۲ مورد دیگر

Dimitrios Chaniotis is a Professor of Cardiology & Physiology-Nutrition at the Department of Biomedical Sciences, School of Health Sciences, University of West Attica, where he also serves as Head of Department and Director of the Research Lab “Anatomy, Pathology & Physiology-Nutrition”. He has been actively contributing to academic and clinical research since at least 2019 and continues in his role currently. His research interests are highly interdisciplinary, spanning cardiology, physiology, nutrition, molecular biology, dermatology, public health, and medical genetics . He investigates topics such as non-coding RNA regulators, oxidative stress, aging biomarkers, autoimmune diseases like ankylosing spondylitis, lifestyle impacts on metabolism, and the role of microbiota in skin and systemic health. His work often bridges clinical observations with molecular mechanisms, aiming to identify biomarkers and therapeutic targets. The recent publications of Dimitrios Chaniotis reflect a strong trend toward translational and interdisciplinary research. His articles span fields including genomics, dermatology, neurology, infectious diseases, and sports medicine, often integrating molecular insights with clinical applications. Many studies employ systematic reviews, clinical trials, and biomarker analyses, suggesting a focus on evidence-based medicine and practical healthcare solutions. While no formal scientific awards are listed in the available data, his extensive publication record in high-impact journals such as Genes , Journal of Clinical Medicine , and Viruses underscores his active contribution to science. Dr. Chaniotis leads a research laboratory and collaborates with multidisciplinary teams across Greece, particularly in areas involving clinical pharmacology, molecular diagnostics, and public health. Although specific grant funding is not mentioned, his involvement in diverse research projects implies active participation in funded research initiatives and academic mentorship.

Dena Schulman-Greenمشاهده پروفایل

دانشیار

• Palliative Care
• Chronic Illness Management
• Self- and Family Management of Chronic Illness
• +۱۵ مورد دیگر

Dena Schulman-Green, PhD, is an Associate Professor at NYU Rory Meyers College of Nursing and Director of the Florence S. Downs PhD Program. Her research focuses on integrating palliative care into patient and family management of serious, chronic illness, particularly in cancer and dementia populations. She is renowned for her co-development of the Middle Range Theory of Self- and Family Management of Chronic Illness, a foundational framework in nursing science. Her educational background includes a PhD and MS in gerontology from the University of Massachusetts Boston, an EdM and MA in counseling psychology from Columbia University, and a BA in psychology and religion from Boston University. She completed a postdoctoral fellowship in breast cancer and palliative care at Yale School of Nursing under the mentorship of Drs. Ruth McCorkle and Elizabeth Bradley. Her research interests span palliative care, chronic illness self-management, health-illness transitions, psychosocial oncology, and qualitative and mixed methods. She has led numerous federally funded studies from agencies including the NIH, American Cancer Society, and Palliative Care Research Cooperative. Her work emphasizes patient-centered care, shared decision-making, and equity in serious illness management. Her recent publications examine hospice transitions in dementia, care disparities during the COVID-19 pandemic, delirium severity measurement, and genomic testing in prostate cancer. These works reveal a consistent commitment to improving end-of-life care through rigorous qualitative and mixed-methods research, with strong attention to social determinants of health and system-level barriers. Scientific Awards: Suzanne Feetham Nurse Scientist Family Research Award (2019) American Academy of Hospice and Palliative Medicine Poster Award (2017, 2016, 2010) Annie W. Goodrich Award for Excellence in Teaching, Yale (2017) National Hospice and Palliative Care Organization Research Award (2004) Induction into Sigma Phi Omega and Psi Chi honor societies She actively mentors PhD and postdoctoral trainees and serves on the editorial board of the Journal of Pain and Symptom Management . Prior to NYU, she was faculty at Yale School of Nursing for 18 years, where she contributed to palliative care research development and education. She is a member of the American Academy of Hospice and Palliative Medicine and other leading professional societies. Her current projects include optimizing prostate cancer care and addressing racial equity in lung cancer care.

Ivan G. Costaمشاهده پروفایل

استاد

• Computational Biology
• Genomics
• Single-Cell Analysis
• +۶ مورد دیگر

Ivan G. Costa is a Professor at the Institute for Computational Genomics, University Hospital RWTH Aachen since 2017. Previously, he held roles as Group Leader in Computational Biology (2012–2017) at the Interdisciplinary Clinical Research Center Aachen, and Assistant Professor positions (2009–2016) at the Federal University of Pernambuco. His research focuses on computational genomics, integrating single-cell technologies to study complex biological systems such as bone marrow niches, fibrosis mechanisms, and cancer progression. Key projects include developing algorithms like scACCorDiON for cell communication analysis and PILOT-GM-VAE for patient-level disease modeling. Education: Ph.D. in Computational Biology from the Max Planck Institute for Molecular Genetics, Berlin (2004–2008). Research interests emphasize single-cell omics, epigenetic regulation, and translational applications in myeloproliferative neoplasms. His work bridges computational methods with experimental models, including 3D iPSC-based systems to study disease mechanisms. Recent studies explore SARS-CoV-2's impact on kidney organoids and fibrosis pathways in chronic conditions. Collaborations include the Helmholtz Institute for Biomedical Engineering and the Clinical Research Unit Aachen (CRU344). Methodological contributions span tools like sc2marker, MOJITOO, and scOpen for data integration and analysis.

Torumoy Ghoshalمشاهده پروفایل

عضو هیئت علمی

• Machine Learning
• Deep Learning
• Natural Language Processing
• +۳ مورد دیگر

Torumoy Ghoshal is an Assistant Teaching Professor of Data Science at Worcester Polytechnic Institute (WPI). Previously, he held a Visiting Assistant Professor position at Lyon College, where he pioneered their data science program. He earned his Ph.D. in Engineering Science (Computer Science major) from the University of Mississippi in 2020. His research focuses on feature engineering, deep learning, natural language processing, and bioinformatics applications. Dr. Ghoshal has industry experience at Dow Jones, developing machine learning models for journalists and the ad-tech team. He advises undergraduate and graduate students on interdisciplinary data science and computer science projects. His work bridges computational methods with real-world applications in healthcare and journalism. His recent publications explore expanding CNN usability beyond images, gene expression analysis for cancer subtypes, and bioinformatics methodologies. While no scientific awards are explicitly listed, his contributions to data science education and interdisciplinary research are notable. Dr. Ghoshal collaborates across disciplines and actively engages in curriculum development. His office is located in Unity Hall 354 at WPI.

Charles F Aquadroمشاهده پروفایل

استاد

• Evolutionary Biology
• Genetics
• Population Genetics
• +۳ مورد دیگر

Charles F Aquadro is the Charles A. Alexander Professor of Biological Sciences at Cornell University, affiliated with the College of Arts and Sciences. He holds joint appointments in the Departments of Ecology and Evolutionary Biology and Molecular Biology and Genetics. His research focuses on evolutionary patterns and processes, particularly using Drosophila as a model to study genomic diversity and its applications in human health and agriculture. He also teaches courses in population genetics, comparative genomics, and personal genomics and medicine. Education: Ph.D. in Genetics (University of Georgia, 1981), M.S. in Zoology (University of Vermont, 1978), B.S. in Biology (St. Lawrence University, 1975). Research interests include understanding genetic diversity in populations, symbiotic interactions (e.g., Wolbachia-Drosophila), and the molecular evolution of genes regulating germline stem cells. His work bridges fundamental research with outreach, including advising science media (e.g., NOVA) and promoting diversity in STEM through lab initiatives. Awards include honorary degrees and recognition for contributions to population genetics. The Aquadro Lab emphasizes fostering an inclusive environment, particularly supporting racial and cultural diversity in scientific fields.

Eray Tüzünمشاهده پروفایل

دانشیار

• Software Analytics
• Mining Software Repositories
• Empirical Software Engineering
• +۳ مورد دیگر

Eray Tüzün is an Associate Professor of Computer Engineering at Bilkent University, leading the BILSEN Research Group focused on Software Engineering and Data Analytics. He holds a PhD in Information Systems alongside bachelor's and master's degrees in Computer Science. With over 20 years of industry experience, he previously worked at Havelsan, Microsoft, Howard Hughes Medical Institute, and CWRU Genomics Center in roles spanning software engineering and project management. His research emphasizes software analytics, mining software repositories, and empirical software engineering practices. He actively contributes to the International Software Engineering Research Network (ISERN) and holds certifications such as PSM, PSPO, and MCSD. Tüzün advocates for bridging educational and industrial gaps through interactive teaching methods and serious games for developer training. His work on code review practices, traceability tools (e.g., RSTrace+), and bus factor estimation (BFSig, Bus Factor Explorer) highlights practical software engineering challenges. He explores applications of AI in code generation evaluation and process improvement. Tüzün's BILSEN Lab engages in projects like BugCraft (bug reproduction) and SmartDelta (automated QA). He maintains active IEEE and ACM SIGSOFT memberships and contributes to conferences like ICSSP and ICGSE. His educational initiatives include board games (ToolStackers) and plugins for teaching DevOps and version control. Current research trends focus on LLM applications in code review, data cleaning impacts, and developer productivity metrics. Grants and collaborations involve industrial partnerships and national/international research networks. He supervises graduate students in masters/PhD programs and undergraduate volunteers, emphasizing empirical studies and tool development. Future work includes expanding AI-driven software analytics and educational technology integration.