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Yang SongView profile

Associate Professor

• Computer Vision
• Deep Learning
• Multimodal AI
• +7 more

Yang Song is an ARC Future Fellow and Scientia Associate Professor at the School of Computer Science and Engineering , University of New South Wales (UNSW) . She serves as Associate Head of School (Research) and Co-Director of iCinema , focusing on AI and Computer Vision applications for social good. Education: BEng in Computer Engineering (Nanyang Technological University, Singapore), PhD in Computer Science (UNSW, 2013) Research Areas: Biomedical image analysis, human-centred AI, graph data modeling, neuro-symbolic learning, and AI trustworthiness. Her work develops domain-specific deep learning models for radiological segmentation, histopathology cancer analysis, and 3D reconstruction. Recent projects address explainability in LLMs, fairness in AI, and human-robot interaction frameworks. With over 200 peer-reviewed publications in top venues like CVPR , MICCAI , and NeurIPS , her research spans biomedical imaging, robotics, and general multimodal AI. Scientific Awards include: 2024: ARC Industrial Transformation Research Hub for Human-Robot Teaming 2023: Google Inclusion Research Award 2022: NHMRC Ideas Grant for computational brain imaging 2021: UNSW Engineering Research Excellence Award 2020: Scientia Fellowship (UNSW) 2019: ARC Future Fellowship She supervises 24 current PhD/MPhil students and has graduated 15 advisees, including placements at Harvard University and Siemens Healthineers. Her grants include collaborations with Surf Life Saving Australia and industry partnerships for AI-driven solutions.

Lucian SulicaView profile

Professor

• Voice Disorders
• Laryngology
• Vocal Fold Injuries
• +7 more

Dr. Lucian Sulica is the Sean Parker Professor of Laryngology and Director of the Sean Parker Institute for the Voice at Weill Cornell Medical College. He is an attending Otolaryngologist at NewYork-Presbyterian Hospital with a clinical practice exclusively focused on voice disorders. Dr. Sulica served as the 2023 President of the American Laryngological Association and is a Fellow of the American Laryngologic, Rhinologic and Otologic Society (the Triologic Society). His educational background includes: A.B. from Dartmouth College (1989) M.D. from Georgetown University School of Medicine (1993) Residency at Georgetown University Medical Center Fellowship at New York Center for Voice & Swallowing Disorders, St. Luke's-Roosevelt Hospital Center Dr. Sulica's research focuses on evidence-driven principles for treating voice conditions, with particular emphasis on vocal fold injuries from voice use (especially in performers), neurologic voice disorders (including vocal fold paralysis, spasmodic dysphonia, and tremor), and in-office procedures for voice disorders that don't require general anesthesia. His work has addressed critical aspects such as gender differences in vocal fold injury, pathophysiology of laryngeal nerve injury, and diagnostic accuracy in voice disorders. Analysis of Dr. Sulica's recent publications reveals a strong focus on advancing diagnostic techniques through artificial intelligence, improving surgical outcomes for vocal fold lesions, understanding performers' unique voice care needs, and developing evidence-based protocols for vocal fold hemorrhage and other voice disorders. His research increasingly incorporates technology-driven approaches while maintaining a strong clinical focus on patient-centered outcomes. Dr. Sulica has received numerous prestigious awards including: Casselberry Award of the American Laryngological Association (2021) Felix Semon Lectureship in Laryngology, Royal Society of Medicine (2022) American Academy of Otolaryngology – Head & Neck Surgery Honor Award (2008) Consistent recognition as one of "Best Doctors in America" (2005-2024) Designation as one of "America's Top Physicians in Voice Disorders/Laryngology" (since 2006) Inclusion in "New York Magazine Best Doctors" list annually since 2013 As an educator, Dr. Sulica has authored more than 110 journal articles and 40 book chapters, and has edited three books including "Vocal Fold Paralysis," "Classics in Voice and Laryngology," and "Patologia Laringea y Fonocirugia" (in Spanish). He is passionate about teaching and has lectured extensively across the United States, Europe, Latin America, and Australia. His clinical work at the Sean Parker Institute for the Voice represents a comprehensive approach to voice care, incorporating innovative in-office procedures that have helped establish new standards in laryngology.

• Machine Learning
• Bioinformatics
• Deep Generative Models
• +3 more

Anders Krogh is a Professor at the Department of Computer Science, University of Copenhagen, and also holds a position at the Department of Public Health in the Section for Health Data Science and AI. He serves as the head of the Center for Health Data Science (HeaDS) in the Faculty of Health and Medical Sciences. Previously, he was affiliated with the Department of Biology at the University of Copenhagen until 2020. Dr. Krogh earned his PhD in theoretical physics but transitioned into machine learning and bioinformatics during his doctoral studies. His research spans both theoretical foundations and practical applications in these fields. He is particularly renowned for his pioneering work on hidden Markov models for biological sequences, which has had significant impact in computational biology. In recent years, Krogh's research has focused on deep generative models applied to gene expression data and other biomedical applications. His work bridges computer science with healthcare, developing AI-driven approaches for precision medicine, cancer diagnostics, and analysis of complex biological systems. His current research integrates machine learning with quantum computing applications in biomolecular modeling. Analysis of his recent publications reveals a strong trend toward applying artificial intelligence to healthcare challenges, particularly in rare diseases, cancer diagnostics, and personalized medicine. His work increasingly incorporates federated learning approaches to address privacy concerns while enabling collaborative research across institutions. There's also a growing emphasis on quantum computing applications in biomolecular modeling and drug discovery. As head of the Center for Health Data Science, Krogh leads interdisciplinary research efforts that bring together computer scientists, medical researchers, and clinicians. His team develops novel computational frameworks like MOSAIC for multimodal analysis of rare cancers and multiDGD for multi-omics data integration. These tools are designed to translate AI innovations into clinical practice while addressing the unique challenges of medical data.

• Database Systems
• Data Science
• Machine Learning
• +3 more

Dr. H.V. Jagadish is a Professor in the Computer Science and Engineering department, focusing on database systems, data science, and ethical AI. He emphasizes mentorship and independence in research, guiding students to become colleagues through collaborative growth. Research Focus His work spans Data integration and fairness in machine learning Query processing and knowledge graph analysis Reproducibility and ethical data management Advising and Research Dr. Jagadish encourages open communication, frequent feedback, and proactive student-driven research. He supports internships and conference attendance, prioritizing SIGMOD and VLDB for presentations.

Vicki L. Plano ClarkView profile

Professor

• Mixed Methods Research
• Research Methodology
• Qualitative Research
• +3 more

Vicki L. Plano Clark is a Professor in the Research Methods area of the School of Education at the University of Cincinnati, where she advises students in the Quantitative and Mixed Methods Research Methodologies (QMRM) concentration of the Educational Studies doctoral program and the Applied Research Methods (ARM) track of the Educational Studies master's program. She joined the University of Cincinnati in 2012 after serving as the director of the Office of Qualitative and Mixed Methods Research at the University of Nebraska-Lincoln. Dr. Plano Clark earned her Ph.D. in Quantitative and Qualitative Methods in Education from the University of Nebraska-Lincoln (2005), M.S. in Physics from Michigan State University (1993), and B.A. in Physics from Kalamazoo College (1990). Her academic journey transitioned from physics education to research methodology, bringing a unique interdisciplinary perspective to her work. As a leading methodologist specializing in mixed methods research, Dr. Plano Clark's scholarship focuses on delineating useful designs for conducting mixed methods research, examining procedural issues associated with these designs, and exploring the contexts for the adoption and use of mixed methods. Her research spans diverse application areas including cancer pain management, STEM graduate student identity development, teacher professional development, and the well-being of rural low-income families. Her work demonstrates how mixed methods approaches can effectively address complex research questions across multiple disciplines. Dr. Plano Clark has made significant contributions to the field through her editorial leadership and publications. She was the founding Managing Editor for the Journal of Mixed Methods Research and currently serves as an Associate Editor. In 2011, she co-led the development of Best Practices for Mixed Methods in the Health Sciences for NIH's Office of Behavioral and Social Sciences Research. In 2012, she became a founding co-editor of the Mixed Methods Research Series with Sage Publications. She has authored numerous influential books including 'Designing and Conducting Mixed Methods Research' (now in its 3rd edition) and 'Mixed Methods Research: A Guide to the Field.' Founding Managing Editor for the Journal of Mixed Methods Research Co-developer of NIH's Best Practices for Mixed Methods in the Health Sciences (2011) Founding co-editor of the Mixed Methods Research Series with Sage Publications (2012) Chair of the Mixed Methods Research Special Interest Group of AERA As an active researcher, Dr. Plano Clark has secured multiple grants including a Department of Education grant evaluating Ohio Network of Education Transformation (ONET) Schools (as Principal Investigator) and a UC University Research Council grant on reducing mass incarceration by improving public defense (as Collaborator). Her recent publications continue to advance methodological understanding in mixed methods research, with a focus on integration techniques, terminology challenges, and applications across health sciences and education. Dr. Plano Clark maintains an active role in the research community through invited presentations and workshops worldwide, helping to train the next generation of researchers in mixed methods approaches and contributing to the ongoing development of methodological standards and practices.

• Computational Pathology
• Medical Image Analysis
• Deep Learning
• +4 more

Nasir M. Rajpoot is a Professor in the Department of Computer Science at the University of Warwick, UK. His research focuses on computational pathology, medical image analysis, and deep learning applications in histology. He leads interdisciplinary projects integrating artificial intelligence with healthcare, particularly in cancer diagnostics and pathology workflows. Rajpoot’s work emphasizes developing robust algorithms for histology image analysis, including nuclear segmentation, tumor classification, and domain generalization in computational pathology. His contributions include the TIAToolbox, an open-source framework for tissue image analytics, and the CoNIC Challenge to advance nuclear detection and counting in histology images. He collaborates with clinicians and biologists to translate AI models into clinical practice, addressing challenges like tumor heterogeneity and staining variability. Rajpoot’s research spans colorectal, lung, and oral cancers, with a focus on predicting clinical outcomes via histological features and genomic data integration. Notable projects include the development of Handcrafted Histological Transformer (H2T) for unsupervised representations of whole slide images and the SAFRON framework for histology image synthesis. His work addresses domain adaptation, robustness evaluation, and explainability in AI-driven pathology systems.

• Cancer Research
• Gastrointestinal Tumorigenesis
• Colorectal Cancer
• +3 more

Ari Ristimäki is a Professor in the Department of Pathology at the Clinicum, University of Helsinki, specializing in gastrointestinal tumorigenesis. He serves as a Supervisor in the Doctoral Programme in Biomedicine and maintains strong connections with HUS Radiology and Pathology. His research spans fundamental cancer biology to clinical applications, particularly in colorectal cancer and related gastrointestinal malignancies. Professor Ristimäki's research interests focus on gastrointestinal tumorigenesis, with particular emphasis on colorectal cancer mechanisms, molecular pathways, and clinical applications. His work bridges basic science and clinical practice, investigating the molecular underpinnings of gastrointestinal cancers while developing diagnostic and therapeutic approaches. His research portfolio includes studies on tumor biomarkers, cancer metabolism, epigenetic modifications, and translational applications for improved cancer diagnosis and treatment. His recent publications demonstrate a strong focus on colorectal cancer research, with particular attention to molecular characterization of BRAF-mutated tumors, liquid biopsy technologies for mutation profiling, and population-based studies of surgical outcomes in gastrointestinal cancer patients. His work shows consistent productivity with 311 publications to date, reflecting sustained research activity since the early 2000s. Professor Ristimäki has supervised doctoral theses, serving as both supervisor and opponent for PhD candidates. His academic service includes manuscript reviewing, committee memberships, and editorial work. His current research is supported by multiple active projects from prestigious funding bodies including the Academy of Finland (SA_2024-2028), Sigrid Jusélius Foundation, Cancer Foundation, and Liv och Hälsa Foundation, indicating strong recognition of his research program's significance and potential impact.

Caetano Reis e SousaView profile

Professor

• Immunology
• Infectious Disease
• Cancer Immunotherapy
• +3 more

Caetano Reis e Sousa is a Professor of Immunology at Imperial College London and Senior Group Leader/Assistant Research Director at the Francis Crick Institute. He leads the Immunobiology Laboratory, focusing on dendritic cell biology, immune responses to pathogens, and cancer immunotherapy. His research explores how dendritic cells detect pathogens and dying cells, triggering adaptive immunity. Key roles include investigating cross-presentation mechanisms, C-type lectin receptors (e.g., DNGR-1), and vaccine development strategies. Education: BSc (Hons) Biology from Imperial College London (1989), DPhil in Immunology from University of Oxford (1992). Postdoctoral training at NIH under Ron Germain. Career milestones include founding the Immunobiology Lab at CRUK London Research Institute (1998–2015) before joining the Crick. Awards & Recognition: Highly Cited Researcher (Thomson Reuters), BD Biosciences Prize (2002), Liliane Bettencourt Award (2008), Louis-Jeantet Prize (2017), Fellowships at Royal Society (2019), Academy of Medical Sciences (2006), and EMBO (2006). Named Officer of the Order of Sant'Iago da Espada (Portugal, 2009). Research Themes: Dendritic cell activation pathways, cross-presentation of tumor antigens, microbiome-cancer immunity links, and immune evasion mechanisms. Collaborations involve institutions like UCL, King's College London, and global health networks. Labs/Teams: Head of Immunobiology Lab at Crick, with expertise in immunology, cell biology, and virology. Facilities include Flow Cytometry, Genomics, and Light Microscopy cores. Active in pandemic response (e.g., SARS-CoV-2 testing initiatives).

Fnu AakashView profile

Assistant Professor

• Hematopathology
• Oncology
• Cancer Diagnostics
• +2 more

Dr. Fnu Aakash serves as Interim Director of Hematopathology and Assistant Professor in the Department of Pathology at the University of Texas Medical Branch. His research focuses on hematopathology, oncology diagnostics, and clinical significance of neoplastic disorders. With an h-index of 55, Aakash has contributed significantly to cancer classification systems through publications in Modern Pathology and American Journal of Surgical Pathology. His recent work includes developing international consensus guidelines for myelodysplastic neoplasms and characterizing non-neoplastic changes associated with breast implants. Research collaborations span multiple institutions including MD Anderson Cancer Center, with specialization in malignant hematology and lymphoma diagnostics.

Jaime S. CardosoView profile

Associate Professor

• Computer Vision
• Machine Learning
• Decision Support Systems
• +3 more

Jaime S. Cardoso is an Associate Professor with Habilitation at the Faculty of Engineering of the University of Porto (FEUP) and a Senior Researcher in the 'Information Processing and Pattern Recognition' Area at INESC TEC's Telecommunications and Multimedia Unit. He has been serving as Research Coordinator since September 15, 1998, and is a Senior Member of IEEE as well as co-founder of ClusterMedia Labs. His educational background includes a Licenciatura in Electrical and Computer Engineering (1999), an MSc in Mathematical Engineering (2005), and a Ph.D. in Computer Vision (2006), all from the University of Porto. Cardoso's research focuses on three major areas: computer vision, machine learning, and decision support systems. His work spans medical image analysis, explainable AI, semantic audio-visual analysis, and pattern recognition. He has co-authored over 150 papers, with more than 50 published in international journals, and has accumulated over 6,500 citations. His recent publications demonstrate expertise in cell nuclei segmentation, ordinal regression for CNNs, semantic segmentation with ordinal relationships, face recognition using synthetic data, and explainable vision language models for medical applications. Honorable Mention in the Exame Informática Award 2011 for 'Semantic PACS' First Place in the ICDAR 2013 Music Scores Competition Cardoso has supervised numerous graduate students at UP-FEUP, with recent theses focusing on multimodal explanations, autonomous driving, medical diagnosis, and explainable AI. His research group works at the intersection of computer vision, machine learning, and practical applications in healthcare and autonomous systems.

Matloob KhushiView profile

Senior Lecturer

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +7 more

Dr. Matloob Khushi serves as a Senior Lecturer in Computer Science at Brunel University London's College of Engineering, Design and Physical Sciences. With over 25 years of combined academic and industry experience, his work bridges theoretical AI advancements with practical applications in finance, healthcare, and public health domains. His research has established significant collaborations with international banks, healthcare institutions, and technology startups. Dr. Khushi earned his PhD in AI and Data Science from the University of Sydney, developing novel algorithms for genomic data analysis. His postdoctoral research at the Children's Medical Research Institute (2014-2017) pioneered AI-based diagnostic tools for medical condition detection. More recently, he developed bioinformatics tools for environmental assessment under a UKRI NEC grant. Research Focus FinTech Innovation : Creator of the SS Ratio (incorporating volatility and drawdown sensitivities), advanced portfolio optimization models, and synthetic data generation techniques for fraud detection and credit risk assessment Bioinformatics Leadership : Developer of AI tools for genomic analysis and early cancer detection, featured in SBS News and The Daily Telegraph Public Health NLP : Architect of systems for vaccine misinformation detection, mental health monitoring, and health surveillance on social media His publication portfolio shows consistent growth from foundational bioinformatics work to current multimodal AI applications, with increasing interdisciplinary collaboration across finance and healthcare sectors. Awards and Recognition Ranked among Stanford/Elsevier's top 2% of global AI scientists Recipient of Best Paper Awards from IEEE Transactions on Computational Social Systems and PeerJ Media recognition for cancer detection research by major news outlets Mentorship and Teaching Dr. Khushi has supervised six PhD candidates to completion and over 100 postgraduate dissertations. He teaches CS3002 Artificial Intelligence and mentors students in Final Year Projects. His supervision focuses on Deep Learning/NLP for FinTech prediction and Public Health Surveillance applications, emphasizing practical implementation of theoretical concepts.

Christine ClarkView profile

Assistant Professor

• Otolaryngology
• Laryngology
• Voice Disorders
• +5 more

Christine Clark, MD, MSc is an attending laryngologist at Weill Cornell Medicine’s Sean Parker Institute for the Voice and Assistant Professor in the Department of Otolaryngology-Head and Neck Surgery at Weill Cornell Medical College. She earned her B.A. from the University of Pittsburgh (2011) and her M.D. from Pennsylvania State University College of Medicine (2017), followed by residency at Georgetown University Medical Center and a fellowship in Laryngology at Weill Cornell, where she also obtained a master’s degree in Clinical and Translational Science. B.A. - University of Pittsburgh (2011) M.D. - Pennsylvania State University College of Medicine (2017) Residency - Georgetown University Medical Center Fellowship - Sean Parker Institute for the Voice (Laryngology) Master’s - Clinical and Translational Science at Weill Cornell Dr. Clark specializes in evaluating and treating swallowing, voice, and airway disorders. Her research focuses on chronic cough, laryngeal hypersensitivity, and benign phonotraumatic vocal fold lesions. She has developed clinical tools like the 3D-printed injection laryngoplasty simulator and quality improvement initiatives for surgical airway management. Her clinical work and research span topics such as vocal fold hemorrhage management, pharyngeal residue quantification in dysphagia, and granuloma as markers of malignancy. Recent publications emphasize global otolaryngology capacity building and performer-specific voice injury care. Scientific awards include: Teaching awards for excellence in medical student education during residency Dr. Clark is affiliated with the Sean Parker Institute for the Voice at Weill Cornell Medicine and serves as an Assistant Professor of Otolaryngology.

Cathy WuView profile

Professor

• Computational Biology
• Bioinformatics
• Data Science
• +8 more

Cathy Wu is a distinguished academic holding the Unidel Edward G. Jefferson Chair in Engineering and Computer Science at the University of Delaware. She serves as Director of the Center for Bioinformatics & Computational Biology (CBCB), Data Science Institute (DSI), and Protein Information Resource (PIR). Her roles include professorships in the Departments of Computer & Information Sciences and Biological Sciences. Education: BS in Plant Pathology (National Taiwan University, 1978), MS and PhD in Plant Pathology (Purdue University, 1982–1984), and a second MS in Computer Science (University of Texas at Tyler, 1989). She completed postdoctoral training in Molecular Biology at Michigan State University (1985–1986). Research interests focus on computational biology, bioinformatics, and data science with emphasis on protein informatics, biological text mining, ontology development, gene-disease-drug networks, and machine learning applications. She leads initiatives in integrating FAIR principles into biological databases like UniProt and InterPro. Her work bridges computational methods with biomedical challenges, including cancer genomics, epigenetic regulation, and proteomic analyses. She has spearheaded educational programs such as the Online Graduate Certificates in Applied Bioinformatics and Biomedical Informatics and Data Science. Her contributions include over 290 peer-reviewed publications (48,000+ citations, h-index 71) and authored/co-authored four books on bioinformatics. She directs multidisciplinary research teams and collaborates internationally on projects like the HALO study on ovarian cancer genetics. Awards and recognition are implied through her leadership roles and academic appointments, though specific prizes are not listed here. Her grants and funding support large-scale initiatives in bioinformatics infrastructure and translational research.

• Medical Image Understanding
• Radiology Report Generation
• Deep Learning
• +3 more

Chantal Pellegrini is a Lecturer and PhD student at the Chair of Computer Aided Medical Procedures (Prof. Navab) at Technical University of Munich (TUM). Her research focuses on Deep Learning applications in medical imaging, including explainable AI for radiology report generation and Vision-Language Models for clinical decision support. She actively contributes to the DHM, NARVIS Lab, and RobUSt research groups. Teaching responsibilities include courses such as 'Computer Aided Medical Procedures', 'Medical Augmented Reality', and 'Surgical Robotics'. She supervises student projects in medical AI and healthcare innovation, with recent projects involving multimodal report generation and graph pretraining for medical applications. Education: BSc/MSc Computer Science (TUM), current PhD student since 2022 Labs: DHM (German Heart Center), NARVIS Lab, RobUSt Robotics & Ultrasound Research Keywords: Medical Image Understanding, Radiology Reports, LLMs in Healthcare Her publications span surgical OR dataset development, reinforcement learning for clinical decisions, and explainable X-ray diagnosis systems. She mentors MA/BA students in medical AI and project management for healthcare applications.

Steven A. SoperView profile

Professor

• Bioanalytical Chemistry
• Microfluidics
• Nanofluidics
• +7 more

Steven A. Soper is a Foundation Distinguished Professor in the Department of Chemistry and Mechanical Engineering at the University of Kansas. He serves as Director of the NIH-funded Center for BioModular Multi-Scale Systems for Precision Medicine and leads international collaborations with institutions like UNIST in South Korea. His career spans faculty roles at LSU, UNC, and KU, with interdisciplinary research bridging chemistry, biomedical engineering, and materials science. Ph.D. in Bioanalytical Chemistry, University of Kansas (1989) Postdoctoral Fellow, Los Alamos National Laboratory (1991) B.S. in Chemistry and Psychology, University of Nebraska (1980-1982) Research Interests focus on micro-/nanofabricated biochemical analysis systems for clinical diagnostics, particularly circulating tumor cell analysis , cell-free DNA detection , and single-molecule fluorescence applications. His work integrates polymer microfabrication, FRET-based assays, and thermoplastic nanofluidics for cancer, stroke, and infectious disease diagnostics. Scientific Awards include: R&D 100 Award (2010) Shannon Award (NIH) (1994) Distinguished Research Master, LSU (2002) Fellow, AAAS/RSC/SAS (2010) Sutton Family Research Impact Award (2021) Teaching & Collaboration involves mentoring 39 professional-degree recipients, organizing multidisciplinary research teams, and co-teaching courses in Biofluid Mechanics and Nanotechnology . His lab partners with institutions in South Korea and UNC/NCSU, while hosting international students and professionals. Labs & Centers : Leads the Soper Research Group and the Center for BioModular Multi-Scale Systems , which provides access to state-of-the-art nanofabrication tools and collaborative expertise across 12 institutions.