جست‌وجوی استاد و پژوهشگر

Mbita Mbaoمشاهده پروفایل

استادیار

• Behavioral Health
• Aging
• Workforce Development
• +۳ مورد دیگر

Dr. Mbita Mbao is an Assistant Professor in the School of Social Work at Salem State University, where she teaches courses including SWK 700 (Human Behavior), SWK 704/705 (Social Work Practice), and aging-focused courses like SWK 871. Her teaching philosophy emphasizes experiential learning and valuing student experiences. Dr. Mbao's research focuses on behavioral health, aging populations, workforce development, and immigrant issues. She actively works to expand aging-related curriculum and services through her involvement with the Older Adults Behavioral Health Network and Salem for All Ages initiative. Her education includes a BSW from Bowling Green State University, MSW from Rhode Island College, and PhD from Simmons University. As a Licensed Clinical Independent Social Worker, she maintains a clinical practice providing in-home therapy to older adults. Honors include: 2025 North Star Collective Fellow 2019 AGESW Pre-Dissertation Fellow 2021 GSA MCDTAW Early Career Diversity Fellow

Michael Baymمشاهده پروفایل

دانشیار

• Microbial Evolutionary Genomics
• Antibiotic Resistance
• Computational Biology
• +۷ مورد دیگر

Dr. Michael Baym is an Associate Professor of Biomedical Informatics at Harvard Medical School with affiliate appointments in Microbiology and the Laboratory of Systems Pharmacology, and as an Associate Member of the Broad Institute. He leads the Baym Lab, which studies microbial evolutionary genomics and antibiotic resistance through a hybrid of experimental, computational, and theoretical approaches. His research focuses on: Antibiotic Resistance Evolution and practical interventions Mobile Genetic Elements (plasmids, phages, transposons) Computational Genomic Algorithms for big data analysis Synthetic Biology tools and technologies Key recent publications explore phage discovery systems , phylogenetic compression of microbial genomes, and RNA-guided gene drives in plasmids. His work is supported by multiple NIH/NIGMS and NSF grants including a MIRA award. Scientific honors include: Packard Fellowship (2018) Pew Biomedical Scholarship (2020) Sloan Research Fellowship (2020) A. Clifford Barger Excellence in Mentoring Award (2021) SSQBio Mentorship Award (2022) The lab actively trains PhD students and postdoctoral fellows with alumni occupying academic and industry positions globally. Current team members include researchers from interdisciplinary backgrounds working at the intersection of experiment, computation, and theory .

• Biomedical Signal and Image Processing
• Cardiovascular and Neural Modeling
• Physiologically-interpretable Artificial Intelligence systems
• +۵ مورد دیگر

Gaetano Valenza is an Associate Professor of Bioengineering at the University of Pisa, Italy, where he leads the Neuro-Cardiovascular Intelligence Lab at the Enrico Piaggio Research Centre. He holds affiliations with the Neuroscience Statistics Research Laboratory at MIT and has served as a Research Fellow at Harvard Medical School and Massachusetts General Hospital. His academic work spans bioengineering, computational physiology, and affective computing. His research focuses on statistical and nonlinear biomedical signal and image processing , cardiovascular and neural modeling , and physiologically interpretable artificial intelligence . He develops wearable systems for physiological monitoring, with applications in autonomic nervous system assessment, brain-heart interactions, and mental health. His work has led to novel metrics such as the Sympathetic and Parasympathetic activity indices derived from ECG. The 15 most recent publications reflect a consistent trend in brain-heart interplay , complexity analysis of physiological signals , explainable AI in healthcare , and virtual reality applications in mental health . His work integrates advanced signal processing, nonlinear dynamics, and machine learning to decode emotional and cognitive states from physiological data. Dr. Valenza is a Senior Member of IEEE and serves on several technical committees. He is an active editorial leader, currently serving as Associate Editor for IEEE-EMBC , Plos One , Complexity , and Scientific Reports , and has guest-edited special issues in Philosophical Transactions of the Royal Society A and IEEE Journal of Biomedical and Health Informatics . He has led or participated in numerous international research projects, including FP7 and H2020 initiatives such as NEVERMIND and EXPERIENCE. He teaches courses in Biostatistics, Probability & Biostatistics, and Advanced Image Processing at the University of Pisa. As lab head and project coordinator, he leads a multidisciplinary team working on neuro-cardiovascular intelligence, wearable systems, and AI-driven mental health interventions.

Jonathan Santoمشاهده پروفایل

استاد

• Developmental Psychology
• Peer Relations
• Child and Adolescent Development
• +۳ مورد دیگر

Jonathan Santo is a Professor of Psychology at the University of Nebraska at Omaha (UNO), where he serves as Director of the Graduate Developmental Psychology Program and as a faculty member in the Office of Latino/Latin-American Studies. His research explores peer relations, cultural differences in self-esteem, and classroom-level influences on child and adolescent development, with a focus on improving school environments and fostering positive social interactions. ORCA Faculty Fellow His research spans broad areas including Developmental Psychology , Social Support Systems , and Cross-Cultural Peer Dynamics , with specific attention to peer victimization , self-continuity , school climate , and developmental trajectories in Brazilian and Colombian youth . Recent publications analyze topics like hikikomori experiences , friendship security , and HPA axis dysregulation in adolescents. Scientific awards include the ORCA Faculty Fellow recognition. His work often involves longitudinal assessments of peer relationships cross-cultural comparisons (Brazil, Colombia, China, Nigeria, Singapore, U.S.) policy-focused blog posts on family separations and school interventions

Noman Mohammedمشاهده پروفایل

دانشیار

• Data Security
• Privacy-Preserving Techniques
• Healthcare Data Privacy
• +۷ مورد دیگر

Noman Mohammed is an Associate Professor of Computer Science at the University of Manitoba’s Faculty of Science, leading the Data Security & Privacy (DSP) laboratory. He specializes in privacy-preserving techniques for data sharing, addressing challenges in healthcare, genomic, and financial data. In 2020, he received the Terry G. Falconer Memorial Rh Institute Foundation Emerging Researcher Award for his contributions to bridging privacy and data utility gaps. His research focuses on balancing data accessibility and individual privacy through technical solutions like federated learning, differential privacy, and secure genomic data processing. He emphasizes integrating policy guidelines with advanced technologies to mitigate privacy risks from interconnected data sources. Notable achievements include developing toolkits for data anonymization and federated learning frameworks, as well as advancing methods to secure cloud-based data storage and analysis. His work aligns with societal needs for robust privacy mechanisms in an era of expanding personal data collection. Future objectives involve addressing privacy challenges in emerging technologies, such as heterogeneous data integration and scalable systems for personal data management. Despite his research focus, he notably avoids social media platforms.

Pierette Appasamyمشاهده پروفایل

مدرس

• Development and evolution of the immune system
• Skin and mucosal immune responses
• Gamma delta T cell biology
• +۷ مورد دیگر

Pierette Appasamy is a Lecturer in the Department of Biology at Chatham University’s College of Arts & Sciences. With a Ph.D. in Anatomy & Developmental Biology from Thomas Jefferson University, she has over three decades of experience in immunology research and education. Her career spans roles at the University of Pittsburgh School of Medicine, NIH-funded research, and current work at Chatham since 2007. B.S., Biology, cum laude, Xavier University (1982) Ph.D., Anatomy & Developmental Biology, Thomas Jefferson University (1988) Post-Doctoral Fellowship, Immunology, University of Pennsylvania (1987-1990) Her research focuses on the evolution and development of gamma delta T cells , IL-7 signaling pathways in amphibians, and psychosocial-immune interactions in college students . She employs Xenopus frogs as a model organism to study non-conventional lymphocyte biology and wound healing immunology. Recent publications highlight her work on cytokine evolution and stress-immune-microbiome dynamics , with collaborations at the University of Pittsburgh’s Center for Medicine and the Microbiome. Her pedagogical innovations include role-playing and analogies to enhance immunology education. NIH R29 Grant (Principal Investigator) NIH R01 Grant (Co-Investigator) MacArthur Foundation Grant (Yale Subcontract) American Cancer Society Grant Chatham University Technology Fellowship Award American Association of Immunologists Travel Grant She mentors students in laboratory research and serves as Chatham’s Pre-Med Advisor. Her lab combines molecular techniques, tadpole thymus microsurgery, and behavioral studies to explore immunological questions with clinical relevance.

Muchao Yeمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• AI Safety
• +۷ مورد دیگر

Muchao Ye is an Assistant Professor in the Department of Computer Science at the University of Iowa. He earned his Ph.D. from Pennsylvania State University's College of Information Sciences and Technology in 2024 and a Bachelor of Engineering in Information Engineering from South China University of Technology. Ph.D., Information Sciences and Technology, Pennsylvania State University (2024) B.Eng., Information Engineering, South China University of Technology His research focuses on the intersection of Artificial Intelligence, Machine Learning, and AI Safety, particularly adversarial robustness in language models and vision-language models. He designs methods to enhance the security and reliability of deep learning systems for safety-critical applications like video surveillance and healthcare. Recent publications highlight adversarial robustness frameworks (e.g., UniT , PAT ), vision-language models for explainable video anomaly detection ( VERA ), and healthcare risk prediction techniques ( MedPath , MedRetriever ). His work appears in top venues such as NeurIPS, KDD, AAAI, ACL, and CVPR. Professional experience includes Applied Scientist internships at Amazon (2022–2023) and teaching roles at the University of Iowa and Pennsylvania State University. He serves as a reviewer for conferences like NeurIPS, ICML, and journals including IEEE TPAMI.

• Biomaterials
• Peripheral Nerve Injury
• Neuromuscular Modeling and Repair
• +۲ مورد دیگر

Suradip Das is a Research Assistant Professor in the Department of Neurosurgery at the Perelman School of Medicine, University of Pennsylvania, where he serves as a Senior Research Investigator. His work bridges neural engineering and regenerative medicine to address critical challenges in nerve and muscle repair. His academic training includes: B.Tech in Biotechnology from Heritage Institute of Technology (2010) PhD in Biosciences and Bioengineering from Indian Institute of Technology Guwahati (2016) Dr. Das specializes in biomaterials development , peripheral nerve injury models , neuromuscular interface engineering , and stem cell-based regeneration . His research pioneers innervated tissue-engineered muscle constructs, demonstrating how motor neurons and endothelial cells synergistically enhance skeletal myocyte maturation. He innovates custom mechanobioreactors that apply tensile forces to guide nanofiber alignment for optimal myofiber formation, significantly advancing volumetric muscle loss treatments. Analysis of his 15 most recent publications reveals a dominant focus on neuromuscular regeneration (75% of articles), with emerging exploration of psychedelic compounds in neural repair. His work consistently integrates human iPSC-derived models , multi-cellular co-cultures , and large-animal validation to address translational gaps. Key trends include optogenetic control of motor units (2023), porcine nerve injury models (2020), and the critical role of pre-innervation in creating pro-regenerative microenvironments (2020-2022). As a core member of the Cullen Lab, Dr. Das collaborates on developing biofabricated neural microtissues for delayed nerve fusion and rapid functional recovery. His research directly informs clinical strategies for peripheral nerve repair and muscle regeneration through rigorous mechanistic studies and innovative engineering solutions.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۷ مورد دیگر

Professor Thomas Lukasiewicz is a Full Professor and Head of the Artificial Intelligence Techniques research group at the Faculty of Informatics, Vienna University of Technology (TU Wien). His research focuses on enabling machines to mimic human-like intelligence through techniques spanning deep learning, symbolic reasoning, and predictive coding. Key areas include explainable AI, hybrid neurosymbolic systems, and applications in healthcare and law. He teaches courses such as Deep Learning for Natural Language Processing, Scientific Research and Writing, and multiple seminars in artificial intelligence and knowledge representation. His research projects include Explainable AI in Healthcare (2023–2027) and foundational work on predictive coding networks. His publications (15+ recent articles) address medical image segmentation, neurosymbolic frameworks, and language model evaluation in mathematics. Notable work includes neurosymbolic hybrid models (CCN⁺), reinforcement learning for medical report generation, and theoretical foundations of predictive coding networks.

Max Lauمشاهده پروفایل

استادیار

• Infectious Disease Dynamics
• Machine Learning
• Artificial Intelligence

Max Lau is an Assistant Professor in the Department of Biostatistics and Bioinformatics and the Department of Epidemiology at Emory University. His research focuses on integrating machine learning and computational methods with epidemiological and genomic data to study infectious disease dynamics. He teaches courses such as BIOS 790R (Advanced Seminar in Biostatistics) and DATA 534 (Applied Machine Learning). Dr. Lau's work emphasizes scalable Bayesian inference, graph neural networks, and stochastic modeling to address challenges in disease transmission, outbreak control, and pathogen evolution. His recent research includes developing tools like ScITree and Epilearn, and he has contributed to understanding measles dynamics, tuberculosis treatment, and livestock disease management. His academic contributions span over 30 publications since 2010, with a particular focus on phylodynamics, epidemic modeling, and vaccine strategy evaluation. His interdisciplinary approach bridges computational methods with public health applications, aiming to enhance disease prediction and intervention efficacy.

• Extreme Environmental Physiology
• Human Adaptation to Stressful Environments
• Environmental Health
• +۳ مورد دیگر

Edward Ashworth is a Postdoctoral Research Associate at the Sydney School of Health Sciences, University of Sydney. He is affiliated with the Thermal Ergonomics Laboratory and the Heat and Health Research Incubator. His research focuses on human adaptations to extreme environments, including heat, altitude, hyperbaric conditions, and space-related stressors. Key projects include improving sleep quality in hot environments and enhancing physical work capacity for outdoor workers. Edward's research interests span environmental physiology, with a focus on thermal tolerance, radiation injury mitigation, and the physiological effects of extreme conditions. He has contributed to studies involving nitrogen kinetics tracking using PET imaging, hyperbaric oxygen therapy, and robotic surgery applications. Awards: Young Investigator Award (2023), Art of Science Contest 1st Prize (2024), Australia Space Biology Summit 1st Place (2022), and Sporting Blue (Auckland University of Technology). Associations: The Physiological Society and American Physiological Society. His work integrates clinical trials, statistical research design, and translational approaches to address challenges in environmental health, cardiovascular disease, and healthy ageing. Current projects aim to optimize thermal tolerance strategies for military and occupational settings.

Anita Hubleyمشاهده پروفایل

استاد

• Adult Development and Aging
• Applied Measurement and Psychometrics (test development & validation)
• Assessment
• +۷ مورد دیگر

Anita Hubley is a Professor at the University of British Columbia's Faculty of Education, Department of Educational and Counselling Psychology, and Special Education (ECPS). She serves as MERM Program Coordinator and directs the Adult Development and Psychometrics Lab. Her work focuses on psychometric test development/validation and quality of life research across adult populations. Education: Ph.D. in Psychology (Human Assessment specialization), Carleton University (1995) M.A. in Psychology (Lifespan Development and Aging), University of Victoria (1991) Pre-doctoral training at Geriatric Assessment Unit (Ottawa) and Neuropsychological Assessment Unit (Ottawa) Her research integrates psychometric theory with practical applications in aging populations, homeless/vulnerably housed individuals, and neuropsychological assessment tools. Key contributions include developing the Memory Test for Older Adults (MTOA), Hubley Depression Scale for Older Adults (HDS-OA), Quality of Life in Homeless and Hard-to-House Individuals (QoLHHI), and Subjective Age Identity Scale (SAIS). Scientific Awards: Killam Teaching Prize (2017) Distinguished Reviewer, Buros Institute of Mental Measurements (2013) She has taught graduate courses in Psychological Assessment, Measurement Principles, Scale Development, and Applied Neuropsychology, emphasizing ethical testing practices and response process research. Her lab's work on test adaptation for marginalized populations has informed international measurement standards.

Brent Pageمشاهده پروفایل

دانشیار

• Medicinal Chemistry
• Chemical Biology
• Drug Discovery and Development
• +۱۳ مورد دیگر

Brent Page is an Associate Professor (tenured) in the Faculty of Pharmaceutical Sciences at the University of British Columbia (UBC) and maintains a research group at the Karolinska Institute , Department of Oncology and Pathology. His dual affiliation underpins a trans-Atlantic program that integrates cutting-edge chemical biology with medicinal chemistry for anti-cancer drug discovery. Education & Training PhD in Chemistry – University of Toronto (2013) HBSc in Chemistry (Honours) – University of British Columbia (2008) CIHR Postdoctoral Fellow – Karolinska Institute, Sweden (2008–2016) Assistant Professor (non-independent) – Karolinska Institute, Department of Oncology-Pathology (2017–2021) Research Focus Dr. Page’s laboratory operates at the interface of medicinal chemistry and chemical biology , aiming to identify and optimize small-molecule inhibitors for proteins previously considered “undruggable.” Core targets include STAT3, CLIC3, NUDT5/15 and SRPK3 . The group employs cellular thermal shift assays , isothermal ligand-induced resolubilization (ILIRA) , and CeTEAM technologies to quantify target engagement and refine structure–activity relationships in physiologically relevant models of breast cancer, triple-negative breast cancer, leukemia and atopic diseases . Funding & Collaborations His program is supported by Canadian Institutes of Health Research (CIHR) and other national and international agencies. Dr. Page actively participates in UBC’s Accelerated Translational Opioid Research Cluster and welcomes interdisciplinary collaborations and undergraduate research involvement. Equity, Diversity & Inclusion Committed to fostering an inclusive environment, Dr. Page mandates EDI training for all lab members and actively encourages participation from equity-deserving groups.

• Medical Image Understanding
• Radiology Report Generation
• Deep Learning
• +۳ مورد دیگر

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.

• Computational Linguistics
• Natural Language Processing (NLP)
• Dependency Parsing
• +۵ مورد دیگر

Joakim Nivre is a Professor at Uppsala University's Department of Linguistics and Philology. He is a leading researcher in computational linguistics, with a focus on dependency parsing, Universal Dependencies (UD) framework development, and multilingual NLP applications. His recent work explores LLMs in climate change discourse analysis, pharmacovigilance explainability, and historical text processing. Key research areas: Dependency parsing theory, Universal Dependencies standardization, LLM evaluation Collaborations: SweSAT-1.0 benchmark development, ClimateEval project, PARSEME integration His 2025-2023 publications demonstrate expertise in explainable AI for healthcare, synthetic data generation for idioms, and multilingual benchmark design. Notably, he co-developed SweSAT-1.0 to evaluate Swedish LLMs and contributed to typology-informed UD revisions. Despite extensive work in NLP, no scientific awards are mentioned in available texts.