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Huaiying ZhangView profile

Assistant Professor

• Biomolecular Condensates
• Cancer Biology
• Cellular Functions
• +3 more

Huaiying Zhang is an Assistant Professor in the Department of Biological Sciences at Carnegie Mellon University, part of the Mellon College of Science. His research focuses on the role of biomolecular condensates in cellular functions and cancer progression, particularly investigating phase transitions in telomere maintenance and cancer cell immortality. He holds a Ph.D. from McGill University and completed postdoctoral research at Dartmouth College, Princeton University, and the University of Pennsylvania. Research interests include engineering synthetic organelles, developing optogenetic tools to manipulate phase separation in live cells, and targeting phase transitions for cancer therapy. His work bridges biophysics, cell biology, and synthetic biology to address fundamental questions in nuclear organization and disease mechanisms. Education: Ph.D., McGill University Postdoctoral Fellowships: Dartmouth College, Princeton University, University of Pennsylvania Publications highlight advances in understanding telomere clustering in cancer cells, nuclear body formation, and applications of phase separation in therapeutic strategies. Collaborative projects emphasize interdisciplinary approaches, combining experimental and theoretical methods. Lab activities focus on biomolecular condensates' material properties, their roles in genomic processes, and translational applications in cancer treatment. The lab actively seeks students and researchers interested in cellular biophysics and disease biology.

David B ShackelfordView profile

Professor

• Cancer Metabolism
• Mitochondrial Biology
• Lung Cancer
• +3 more

David B Shackelford is a Professor in the School of Medicine at the University of California Los Angeles, specializing in Cancer Metabolism and Mitochondrial Biology . His research focuses on the metabolic vulnerabilities of lung and other cancers, particularly in tumors with LKB1 mutations and KRAS dependencies. Key Research Themes: Mitochondrial heterogeneity, metabolic reprogramming, and drug targeting in oncology. Grants: NIH R01CA208642 (2016–2021) for imaging mitochondrial networks in LKB1 mutant lung cancer. His recent work explores sphosphorylation pathways , amino acid metabolism , and mitochondrial membrane potential imaging . Publications highlight collaborations with multidisciplinary teams and translational studies in liposarcoma , glioblastoma , and fibrolamellar carcinoma . Trends in Publications: 2024 studies emphasize PGC-1α in neuroendocrine cancer, ASCL1 subtypes, and dsRNA trafficking . Clinical Relevance: Trials on metabolic drugs like phenformin and mTOR inhibitors for NSCLC and glioma.

Martin FergieView profile

Lecturer

• Machine Learning
• Computer Vision
• Medical Imaging
• +5 more

Martin Fergie is a Lecturer in Healthcare Sciences at the University of Manchester's Division of Informatics, Imaging & Data Sciences. His research focuses on applying machine learning and computer vision to medical imaging for disease outcome prediction, including breast cancer risk assessment via mammograms and multiplex immunofluorescence imaging for cancer outcomes. He holds a PhD in machine learning from the University of Manchester (2008–2012), followed by roles as CTO at DigitalBridge and CEO at Spotlight Pathology Ltd. He is actively involved in the InnovateUK ICURe program to reduce pathologists' workload through AI in digital pathology. Education: PhD in Machine Learning (University of Manchester, 2013), MSc/Molecular Pathology Teaching Role. Research interests include predictive modeling for disease outcomes, AI-driven pathology tools, and imaging biomarker development. Key projects include breast cancer risk prediction from mammograms and histology-based clinical outcome modeling for follicular lymphoma and head/neck cancers. Recent articles highlight advancements in AI for breast density assessment, extracellular matrix phenotyping, and H&E-to-multiplex immunohistochemistry translation. His work contributes to UN Sustainable Development Goals related to health and innovation. Awarded the 2023 Teaching Excellence Award (Highly Commended) for contributions to medical education. Collaborates on projects like the 'Developing targeted strategies for precision breast cancer prevention' initiative. External roles include Non-executive Director at VREvo Ltd and CEO at Spotlight Pathology Ltd. Associated with research platforms like Digital Futures and the Lydia Becker Institute.

Eduardo EyrasView profile

Professor

• RNA Biology
• Cancer Research
• Long-read Sequencing Technologies
• +4 more

Eduardo Eyras is a Professor at the Australian National University (ANU) and EMBL Australia Group Leader, leading research in computational RNA biology and cancer genomics. He directs the Centre for Computational Biomedical Sciences and is part of the Shine-Dalgarno Centre for RNA Innovation. His work focuses on transcriptome and epitranscriptome analysis using long-read sequencing, machine learning, and computational methods to study cancer mechanisms. Eyras holds a PhD in Mathematics from the University of Groningen (1999) and previously led research at the Sanger Institute and Pompeu Fabra University. Affiliations: Director, Centre for Computational Biomedical Sciences Researcher, Shine-Dalgarno Centre for RNA Innovation Member, Division of Genome Sciences and Cancer Leader, The Eyras Group - Computational RNA Biology Research Interests: Development of algorithms for long-read sequencing Machine learning applications in RNA biology Epitranscriptomic modifications and cancer Therapeutic mRNA platform steering Key Projects: Novel algorithms for transcriptome variation analysis Predictive models of RNA modifications in disease Ribosomal DNA variation analysis Advisees & Grants: Supervises PhD students (e.g., Favour Oyelami, Stefan Prodic) and leads ARC-funded projects on mRNA diagnostics and epitranscriptomic therapies. Collaborates with global teams on forensic genomics, cancer drug resistance, and AI-driven translational research. Labs/Teams: Leads the Eyras Group, collaborating with the Hannan Group (Cancer Therapeutics) and Shirokikh Group (Protein Biosynthesis).

• Computer Vision
• Machine Learning
• Image and Video Processing
• +3 more

Fouad Khelifi is an Associate Professor in the Department of Computer and Information Sciences at Northumbria University. His research focuses on computer vision, machine learning, image/video processing, biometrics, multimedia forensics, and medical image analysis. He obtained his PhD in Computing Science from Queen's University Belfast (2007) and held prior research roles at the University of Bradford (2007–2009) before joining Northumbria in 2010. He supervises PhD students in cybersecurity applications and palm-vein recognition systems. Education: PhD in Computing Science, Queen's University Belfast (2004–2007) Fellow of the Higher Education Academy (FHEA, 2014) Research Interests: Khelifi’s work spans advanced deep learning techniques for medical imaging (e.g., cancer detection, retinal disease analysis), source camera identification in digital forensics, and biometric authentication systems. He develops novel algorithms for feature extraction, fusion networks, and transformer-based models in healthcare and multimedia security. Advising: Supervising Egallekanda Perera (PhD, 2019–2025): Efficient Keypoint-based Palm-vein Recognition Co-supervising Ikechukwu Ikpeama (PhD, 2024–): Cybersecurity for Industrial Control Systems Labs/Teams: Active in Northumbria’s Digital Media and Systems Research groups, contributing to interdisciplinary projects in AI-driven medical imaging and multimedia forensics.

• Cancer Biomarkers
• Translational Cancer Research
• Digital Pathology
• +3 more

Lill-Tove Rasmussen Busund is a Professor and Consultant Pathologist at the Department of Medical Biology, UiT The Arctic University of Norway. Her research focuses on translational cancer studies with emphasis on cancer biomarkers in tissue and blood, combining molecular biology with artificial intelligence applications in pathology. She leads the Translational Cancer Research Group (TCRG) and contributes to projects like the TNM-Immune Cell Score Trial and AI–Pathology initiatives. Role: Professor/Consultant Pathologist University: UiT The Arctic University of Norway Department: Department of Medical Biology Email: lill.tove.rasmussen.busund@uit.no Rasmussen Busund's work spans epidemiological cancer research , multi-omic data integration , and machine learning applications for cancer diagnostics. She develops prognostic and predictive biomarkers using population-based cohorts like the NOWAC study, with particular attention to hormone-dependent cancers and immune microenvironment analysis . Recent publications highlight her expertise in digital pathology and AI-driven tumor classification , including studies on microRNA expression patterns in breast and colon cancer, immune cell score development for NSCLC, and computational approaches to lymphocytic infiltration assessment. Her research directly impacts precision oncology and immunotherapy response prediction . She contributes to teaching as leader of the Musculoskeletal System course at the Medical School, and maintains active participation in scientific knowledge migration projects like the transition to the National Science Archive (NVA). Her ORCID identifier is 0000-0001-8235-6163 .

Weilu ZhangView profile

Assistant Professor

• Digital Marketing
• Social Media Advertising
• Artificial Intelligence in Communication
• +4 more

Weilu Zhang serves as Assistant Professor in the Department of Integrated Strategic Communication within the College of Communication and Information at the University of Kentucky. Her office is located in 230B McVey Hall, and she maintains professional correspondence via weiluzhang@uky.edu. Her research program critically examines digital communication interfaces through computational lenses, with emphasis on: AI-driven consumer engagement in DEI initiatives Ethnic/racial targeting dynamics in algorithmic advertising Gender stereotype manifestations in health campaigns Political ideology's role in social media persuasion Human versus machine source credibility in influencer marketing Computational analysis of crisis communication during pandemics Analysis of her 2021-2025 publications reveals methodological innovation through deep learning applications and large-scale social media data mining. Recurring themes include ethical tensions in AI-powered targeting, ideological polarization in brand activism, and intersectional identity factors shaping consumer responses. Her work consistently bridges theoretical communication frameworks with industry-relevant digital marketing challenges. Available records contain no documentation of doctoral advisees, research grants, or formal awards. No information regarding laboratory facilities or collaborative research teams appears in current institutional sources.

Gabriele RomanoView profile

Assistant Professor

• Cancer drug resistance
• Tumor suppressor genes
• Immune evasion
• +5 more

Gabriele Romano, PhD, is an Assistant Professor in the Department of Pharmacology & Physiology at Drexel University College of Medicine. His research focuses on cancer drug resistance mechanisms, leveraging mouse modeling, functional genomics, and computational biology. He leads the Romano Lab, which explores tumor-stroma interactions in minimal residual disease, tumor suppressor roles in therapy resistance, and HIV-cancer comorbidity. Education: PhD - Molecular and Translational Medicine, University of Milan, Bicocca (2015) MS - Medical Biotechnology, University of Milan, Bicocca (2012) BS - Biotechnology, University of Milan, Bicocca (2010) Research Interests: Cancer drug resistance mechanisms Immune evasion and tumor microenvironment Therapeutic strategies for HIV-associated cancers Functional genomics and nanoparticle delivery His work emphasizes developing novel therapies targeting residual tumor cells and improving outcomes for immunocompromised cancer patients. Key Awards: 2023 WW Smith Trust nominee (Cancer Research) 2022 Pew Biomedical Scholars competition nominee 2019 Maryanne Rosenstein Family Fellowship in Cancer Research Grants & Collaborations: Recipient of multiple institutional and foundation grants Collaborations with global institutions on translational projects Focus on mouse models, CRISPR screens, and bioinformatics Labs & Teams: Romano Lab at Drexel University Partnerships with MD Anderson Cancer Center and The Jackson Lab

Burak SarsilmazView profile

Assistant Professor

• Distributed Control
• Adaptive Control
• Trajectory Optimization
• +2 more

Dr. Burak Sarsilmaz is an Assistant Professor in the College of Engineering at Utah State University, specializing in Electrical and Computer Engineering. His research focuses on distributed control of multi-agent systems, adaptive control, and trajectory optimization for aerospace applications. Education: PhD in Mechanical Engineering, University of South Florida (2020) MA in Mathematics, University of South Florida (2020) MS in Aerospace Engineering, Middle East Technical University (2016) BS in Aerospace Engineering, Middle East Technical University (2013) Research: His work bridges control theory and practical applications in autonomous systems, with emphasis on robustness under uncertainty. Recent publications explore novel approaches to cooperative control and optimization in constrained environments. Students: Actively mentors graduate students including Akalu Desta Teklu and Kursad Metehan Gul. Leads the Autonomy, Robotics, Control, and Optimization (ARCO) research group. Awards: Holds a Canada Research Chair in Translational Cancer Research.

• Chemical Biology
• Fluorescence Guided Surgery
• Drug Delivery
• +5 more

Prof. Donal O'Shea is a Professor in the Department of Chemistry at the Royal College of Surgeons in Ireland (RCSI). Previously, he held roles including Head of Pharmaceutical & Medicinal Chemistry at RCSI and Associate Professor/Senior Lecturer at University College Dublin (UCD). He earned a PhD (1993) and BSc (1990) in Chemistry from University College Galway. His research focuses on synthesizing complex molecules for applications in fluorescence-guided surgery , light-activated anti-cancer agents , and nanomedicine . Key areas include near-infrared fluorophores , drug delivery systems , and collaborations with medical imaging. He has led initiatives like the Centre for Synthesis & Chemical Biology at UCD and contributed to projects on exosome imaging and anti-microbial agents. Recent publications highlight innovations in fluorescence imaging probes , vaping health risk modeling , and bioorthogonal reactions . His work aligns with UN Sustainable Development Goal 3 (Good Health). Awards include the 2012 North/South Ireland Lectureship , Teacher of the Year (2008, 2011), and multiple visiting professorships. He has secured grants totaling millions, including SFI-funded projects on super-resolution imaging and colorectal cancer diagnostics . Prof. O'Shea oversees RCSI's Chemistry Department and collaborates internationally. His lab develops tools for real-time cellular imaging and targeted drug delivery , with applications in surgery and oncology.

David BrodbeltView profile

Professor

• Companion Animal Epidemiology
• Veterinary Anaesthesia
• Antimicrobial Stewardship
• +3 more

David Brodbelt is a Professor of Evidence-Based Veterinary Medicine at the Royal Veterinary College (RVC), University of London. He leads the VetCompass program, a companion animal surveillance initiative, and chairs the VeNom Coding Group , which standardizes veterinary clinical terminology. His research focuses on epidemiology, antimicrobial stewardship, and veterinary practice data analytics. Education: Graduated from Cambridge Vet School (1993), completed a residency in Veterinary Anaesthesia, and earned an RCVS Diploma in Veterinary Anaesthesia (1998). His PhD (2006) investigated perioperative complications in veterinary anaesthesia. Teaching: Leads the Research Skills Module for RVC's MSc programs in Veterinary Epidemiology and contributes to undergraduate and postgraduate education in epidemiology, statistics, and evidence-based veterinary medicine. Key Research: Explores companion animal health using electronic health records, with a focus on diabetes mellitus, cardiovascular disorders, and breed-specific health risks. Collaborates on projects like antimicrobial usage analysis and disease burden assessments in dogs and cats. Awards: Fellow of the Higher Education Academy. Active in professional organizations, including the Society for Veterinary Epidemiology and Preventive Medicine (SVEPM). Administrative Roles: Deputy Principal of the RVC, overseeing clinical affairs. Previously Chair of Small Animal Studies and Head of the Department of Veterinary Clinical Sciences.

Zoran GajicView profile

Professor

• Control Systems
• Energy Systems
• Wireless Communications
• +4 more

Zoran Gajic is a Professor of Electrical and Computer Engineering at Rutgers University, where he has taught since 1984. He holds academic leadership roles including Graduate Program Director for the Electrical and Computer Engineering Department and President of the Rutgers AAUP-AFT Faculty Union. His expertise spans controls systems, energy systems (including solar, wind, and smart grids), wireless communications, and networking. Education: B.S. and M.S. in Electrical Engineering from University of Belgrade, followed by M.S. in Applied Mathematics and Ph.D. in Systems Science Engineering from Michigan State University (1984). Research focuses on control theory applications for energy systems and communication networks. He has authored/coauthored nearly 100 journal papers and eight books, including best-selling titles like Linear Dynamic Systems and Signals (translated into Chinese) and Lyapunov Matrix Equation in Systems Stability and Control (republished by Dover). His work includes innovations in multirate control systems, singular perturbation methods, and reinforcement learning applications. Professional recognitions include editorial roles across nine journals, five guest-edited special issues, and plenary lectures at international conferences. Ten of his 17 Ph.D. advisees hold faculty positions globally. Beyond academia, he is a chess master with Life Master ranking from the U.S. Chess Federation and World Chess Federation certification. Key contributions include foundational work on optimal control for renewable energy systems, sliding mode control algorithms, and system decomposition techniques. His research has been supported by NSF and industry partners like AT&T Bell Labs. He leads the Rutgers Center for Systems and Controls (SYCON) as Associate Director and actively contributes to standards through IEEE and IEC initiatives, particularly in power system protection and control system reliability.

• Immunology
• Infection Immunology
• Respiratory Viral Infections
• +6 more

Prof. Dunja Bruder is a university professor of infection immunology at the Institute of Medical Microbiology and Hospital Hygiene at Otto von Guericke University (OVGU) and Head of the Immune Regulation Research Group at the Helmholtz Center for Infection Research (HZI). She obtained her PhD in immunology from TU Braunschweig and completed postdoctoral training at Harvard Medical School and Yale University School of Medicine. Her research focuses on immune regulation in respiratory viral infections, chronic inflammatory lung diseases, and mucosal immunity. She leads two research groups and holds leadership roles in the Research Focus on Respiratory Viral Infections (HZI), the CRC 854, and the Otto-von-Guericke Graduate Academy. Her work integrates innate and adaptive immunity, with particular emphasis on T-cell responses, microbiota interactions, and vaccine development. She also contributes to teaching in master's programs and human medicine. Education Bachelor/Master: Biotechnology, Technical University of Braunschweig PhD (1996–1999): Immunodominance and T-cell responses to bacterial toxins, HZI Habilitation (2009): Immunology, Hannover Medical School Research Interests Bruder’s work examines immune responses to respiratory pathogens like influenza and SARS-CoV-2, the role of epithelial-T-cell interactions in asthma, and the modulation of immune defenses by microbiota. She investigates vaccine strategies using defective interfering particles and antigen-targeting approaches. Her studies also address antitumor immune training via viral infections and metabolic control of T-cell function in asthma endotypes. Key Contributions She pioneered the analysis of alveolar macrophage dysfunction in chronic lung diseases and demonstrated the protective role of IL-33 in microbiota-mediated antibacterial defenses. Her team developed predictive models for influenza infection using hematological data and identified CD47 as a critical regulator of antiviral macrophage activity. Labs/Teams Leads the Immune Regulation Group at HZI and collaborates with the Institute of Medical Microbiology at OVGU. Active in the HZI’s Respiratory Viral Infections Research Focus and the CRC 854.

Mohamed H. DoweidarView profile

Professor

• Computational Biomechanics
• Cell Simulation
• Hyperelastic Materials
• +7 more

Mohamed H. Doweidar is a Full Professor in the Mechanical Engineering Department at the University of Zaragoza, Spain. He is affiliated with the School of Engineering and Architecture (EINA), the Bioengineering Division of the Aragón Institute of Engineering Research (I3A), and the CIBER-BBN (Bioengineering, Biomaterials, and Nanomedicine). His academic career spans over three decades, with teaching roles since 1994 and significant contributions to computational biomechanics and biomedical engineering. Education: Ph.D. in Computational Fluid Mechanics (2004), University of Zaragoza M.Sc. in Engineering Mathematics (2001), Ain Shams University Bachelor's in Statistics & Computer Science (1997), Mansoura University Industrial Engineering Degree (1993), Benha Higher Institute of Technology Research Interests: Focus on Computational Biomechanics , Cell Simulation , Hyperelastic Materials , Finite Element Method , and Error Estimation . His work integrates computational models to study cellular behavior, tissue regeneration, and biomedical applications. Key Contributions: Authored/co-authored books on biomechanics and computational modeling, including "Digital Human Modeling and Medicine: The Digital Twin" (2022). Supervised numerous doctoral students, some of whom received university awards. Active in editorial boards, project evaluations (ANEP), and international conferences. Labs & Groups: Member of the Applied Mechanics and Bioengineering Group (AMB), CIBER-BBN, and I3A. Research spans cell migration , biomaterials , and computational oncology .

• Matrix Metalloproteases
• Biophysics
• Enzymology
• +4 more

Susanta Sarkar is a Research Professor at Arizona State University's School of Molecular Sciences, affiliated with the Tempe campus. His email is Susanta.Sarkar@asu.edu. He holds a NIH R01 GM145210 grant as the sole PI ($1.1 million), focusing on MMP1's role in collagen degradation. His research integrates biophysics, enzyme dynamics, and drug development to target matrix metalloproteases (MMPs) in diseases like cancer and neurodegeneration. He employs single-molecule techniques to study enzyme-substrate interactions, aiming to develop precision therapies with minimal side effects. Education : Ph.D. in Physics, University of Oregon (2006) M.S. in Physical Sciences, Indian Institute of Science (2000) Postdoctoral Associate, Cornell University (2008), NIH Research Fellow (2013) Research Interests : MMPs' role in human health, single-molecule biophysics, allosteric modulation, and drug screening for Parkinson’s/Alzheimer’s. His work bridges fundamental biology and translational medicine, funded by NIH. Publications : Recent work includes substrate-specific MMP dynamics, alpha-synuclein interactions, and biofilm inhibition. His 2020 Biophysical Journal study was cover-selected and F1000-recommended. Over 15 publications since 2016 address enzyme activity, thermodynamics, and imaging. Grants & Awards : NIH R01 GM145210 (2022-2026), $2.25 million in total funding. Recognized for innovative methodologies in single-molecule studies. Advising & Training : Supervised 54 trainees, including 3 PhDs securing >$1.5M in grants post-graduation. Emphasizes financial literacy alongside science, with students averaging $30K+ retirement savings. Service : Served on 12 NSF/NIH panels, reviewer for 20+ journals including Nature Communications and Biophysical Journal. Labs/Teams : Integrates personal finance education in group meetings to boost focus and career readiness. Lab focuses on MMPs, antimicrobial biopolymers, and fluorescent nanodiamond imaging.