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Laurynas SiksnysView profile

Researcher

• Energy Engineering
• Energy Flexibility
• Renewable Energy Sources
• +3 more

Laurynas Siksnys is an Academic Officer at the Department of Computer Science, Aalborg University, affiliated with The Technical Faculty of IT and Design. He is part of the Daisy - Center for Data-intensive Systems and the Data Engineering, Science and Systems group. His research focuses on energy systems, particularly energy flexibility, smart grids, and renewable energy integration. Education details: Not explicitly provided in the text. His work emphasizes scalable flexibility modeling in energy systems, including device-independent FlexOffer frameworks and uncertainty-aware approaches. He has contributed to projects like GOFLEX, demonstrating flexibility aggregation for 500+ prosumers across Europe. His research bridges technical systems and user expectations through participatory design studies. Notable projects include the EU-funded GOFLEX and MIRABEL initiatives addressing energy demand distribution and data collection systems. He collaborates extensively in international consortia, including the IT4BI-DC Erasmus Mundus Doctoral College. He has advised on projects involving energy flexibility trading mechanisms and participated in grant-funded research spanning 2010-2023. His lab affiliations include Daisy Center and data engineering teams focused on energy system optimization.

• Human-Computer Interaction
• Communication and Information Technologies
• Healthcare Quality
• +6 more

Farid Al Zoubi is a Research Fellow at the School of Electrical Engineering and Computer Science, affiliated with the METRICS Lab. He holds a PhD in Electrical Engineering and Computer Science from the same institution (2020–2024), under the supervision of Dr. Pascal Fallavollita. His research focuses on integrating artificial intelligence, machine learning, and prescriptive analytics to optimize healthcare delivery systems, particularly in high-volume surgical environments like operating rooms. His work emphasizes improving surgical team efficiency, reducing delays in arthroplasty procedures, and enhancing healthcare quality through data-driven decision-making frameworks. Key research interests include Human-Computer Interaction, Communication Technologies, Healthcare Analytics, and the application of AI/ML in surgical workflows. He has published in journals such as Frontiers in Digital Health , Canadian Journal of Surgery , and International Orthopaedics , addressing topics like AI-driven prescriptive models, surgical workflow optimization, and team coordination in healthcare settings. Al Zoubi’s research bridges engineering and medicine, aiming to transform healthcare operations through innovative analytical systems. His current work explores real-world deployment of AI recommendations in orthopedic surgery and the use of multidisciplinary strategies to improve surgical efficiency. He is based in Ottawa, Canada, and collaborates with interdisciplinary teams to advance healthcare technology. Future directions include expanding AI applications in prescriptive analytics for healthcare systems, developing benchmarking tools for surgical teams, and advancing machine learning models tailored to healthcare operational challenges.

Peter L. ElkinView profile

Professor

• Biomedical Informatics
• Artificial Intelligence in Healthcare
• Natural Language Processing
• +3 more

Peter L. Elkin, MD, MACP, FACMI, FNYAM, is Professor and Chair of the Department of Biomedical Informatics and Professor of Internal Medicine at the University at Buffalo's Jacobs School of Medicine & Biomedical Sciences. He leads research in biomedical informatics, focusing on AI-driven healthcare solutions, terminology standards (e.g., SNOMED CT), NLP applications for clinical data, and analytics for substance use disorders. Affiliated with UBMD for patient care, he bridges clinical practice with translational research. Education: BS, Union College, Cum Laude (1978) MD, New York Medical College (1985) Residency, Lahey Clinic Fellowship in Biomedical Informatics, Massachusetts General Hospital (1990) Certificates: Biomedical Informatics (ACMI, 2006), ACP (2009), Internal Medicine (NYAM, 2012) His research integrates AI, NLP, and big data to address clinical challenges, including opioid/alcohol use disorders, long COVID phenotyping, and equitable ML algorithms. Recent work emphasizes semantic AI chatbots, generative AI infrastructure, and RNA editing implications in disease. Publications (2021–2025) reflect interdisciplinary trends: AI validation in medical exams (USMLE), opioid epidemiology in NY State, bias mitigation in ML, and NLP-enhanced EMR analytics. Themes include clinical AI ethics, public health informatics, and scalable terminology systems. Awards: Mastership, American College of Physicians (2009) Homer R. Warner Award (1998) Mayo Laureate Award (2005) Fellowships: ACMI (2006), NYAM (2012), Royal Danish Society (2007) He co-leads NIH/VA grants (e.g., CTSA, BD-STEP) and mentors through informatics training programs. As department chair, he oversees labs advancing NLP, clinical AI, and terminology standards.

Nicolle T ClementsView profile

Associate Professor

• Applied Statistics
• Agricultural Data Analysis
• Data Mining
• +3 more

Nicolle T. Clements is an Associate Professor at Saint Joseph's University's Department of Decision and System Sciences and serves as Academic Coordinator for the MS in Business Intelligence & Analytics program. She holds a PhD in Statistics from Temple University, an M.S. in Statistics from Virginia Tech, and a B.S. in Mathematics from Millersville University. Her research focuses on applied statistical analysis in Pennsylvania's agricultural sector, including projects funded by the PA Department of Agriculture to evaluate initiatives like PA Preferred branding, urban agriculture trends, and small meat processing capacity. She teaches courses on statistics, data mining, and R programming across undergraduate, graduate, and executive education levels. Her research expertise spans statistical methodologies, agricultural data analysis, and interdisciplinary applications in public health and environmental science. Recent work addresses consumer perceptions of industrial hemp, vegetation monitoring via spatio-temporal models, and ethical dimensions of business intelligence storytelling. Dr. Clements has published extensively in journals like Journal of Criminal Justice , International Journal of Remote Sensing , and Journal of Addictive Behaviors . Her 2024 study on industrial hemp perceptions highlights her ongoing commitment to bridging statistical rigor with real-world agricultural challenges. She collaborates actively with policymakers and industry partners to translate statistical insights into actionable strategies.

Thanigavelan JambulingamView profile

Professor

• Pharmaceutical Supply Chain Management
• Healthcare Marketing Strategy
• Entrepreneurial Process in Healthcare
• +3 more

Thanigavelan Jambulingam, PhD is a Professor in the Department of Food, Pharma and Healthcare at Saint Joseph's University. His professional career spans over three decades, with extensive experience in academic research, industry advisory roles, and pharmaceutical supply chain management. He holds a PhD in Pharmacy Administration from the University of Wisconsin-Madison (2001), along with multiple advanced degrees in pharmacy and pharmaceutical technology. Dr. Jambulingam's research focuses on pharmaceutical supply chain dynamics, healthcare marketing strategies, entrepreneurial processes in healthcare, and regulatory economics. He has published extensively in journals such as Journal of Commercial Biotechnology , International Journal of Pharmaceutical and Healthcare Marketing , and Harvard Health Policy Review . Notable contributions include studies on buyer-supplier coordination in pharmaceutical supply chains, regulatory compliance impacts, and CRM strategies in the pharmaceutical sector. His awards include the 2019 Emerald Literati Network Excellence Award, multiple teaching and research awards from Saint Joseph's University, and the American Association of Pharmaceutical Scientists Best Paper Award (2003). He currently serves on advisory boards for Virpax Pharmaceuticals and AMT Medical. His professional experience includes roles at Pfizer, the University of Wisconsin's Center for Supply Chain Management, and teaching at the undergraduate and graduate levels. Dr. Jambulingam has secured significant research funding, including grants from the Centers for Disease Control and Prevention (CDC), Pfizer Inc., and the American Association of Retired People (AARP). His work often bridges academic research with real-world healthcare challenges, emphasizing policy implications and practical applications of pharmaceutical marketing strategies.

Jangwon ChoiView profile

Assistant Professor

• Digital Marketing
• Online Advertising
• Marketing Analytics
• +3 more

Jangwon Choi is an Assistant Professor of Marketing at the Leavey School of Business. He teaches undergraduate courses in Principles of Marketing and Pricing Strategy. His research focuses on modeling digital marketing interventions, such as promotions of digital content and online advertising, and developing prescriptive strategies for optimization. He employs Bayesian nonparametrics and Natural Language Processing in his work, with publications in the Journal of Marketing Research . Education: PhD in Business Administration, Ross School of Business, University of Michigan MS in Statistics, University of Chicago BBA, BA in Economics, and BS in Statistics, Seoul National University His research interests span digital marketing analytics, econometric modeling, and consumer behavior in digital spaces. His recent work explores topics like consumption-decelerating promotions and the impact of politically biased moderation on social media echo chambers. No scientific awards are explicitly listed in the provided text. Advising and grants details are not available here. He has no listed lab affiliations or teams mentioned in the current profile.

Xiaojing DongView profile

Associate Professor

• Quantitative Marketing
• Econometrics
• Bayesian Statistics
• +3 more

Xiaojing Dong is an Associate Professor of Marketing and Business Analytics at the Leavey School of Business, Santa Clara University. She directs the MS in Marketing program and teaches core courses like 'Principles of Marketing' and electives such as 'Marketing Analytics.' Her research focuses on understanding customer responses to marketing strategies, leveraging quantitative methods like econometrics and Bayesian statistics, with applications in pharmaceutical, high-tech, and retail industries. Dr. Dong holds a PhD from Northwestern University (Alden G. Clayton Award recipient), an MS from MIT, and a BS from Tsinghua University. She serves as a reviewer for Marketing Science and International Journal of Research in Marketing . Her research explores preference heterogeneity, user-generated content motivation, and satisfaction spillovers. Notable work includes analyzing bid-pulsing in search engines and physicians' sample-dispensing decisions. She has contributed to over 20 peer-reviewed articles and book chapters, emphasizing empirical rigor and practical insights. Awards: Alden G. Clayton Doctoral Dissertation Proposal Award (2014). Teaching and Grants: Develops data-driven curricula and collaborates on projects involving marketing analytics and consumer behavior modeling. Labs/Teams: Engaged with the AIMES Program and interdisciplinary research in marketing science.

Rebecca LodwickView profile

Academic

• Civil Engineering
• Statistical Modeling
• Epidemiology
• +3 more

Dr. Rebecca Lodwick is a Senior Teaching Fellow at the University of Portsmouth's School of Civil Engineering and Surveying . She joined the faculty in 2016, teaching mathematics and statistics to Civil Engineering undergraduates. Her academic background includes a PhD in Mathematical Sciences from Queen Mary, University of London, an MSc in Medical Statistics from the London School of Hygiene and Tropical Medicine, and an MMath from the University of Oxford. Research Interests Her research focuses on adapting statistical modeling and epidemiological methods to address challenges in Civil Engineering and the built environment . She applies quantitative approaches to analyze structural data, risk assessment, and healthcare-infrastructure interactions, bridging her expertise in mathematical sciences and public health . Key Articles Her peer-reviewed work spans HIV epidemiology , dementia healthcare disparities , and palliative care practices . Recent contributions include 2023 studies on spiritual care in palliative medicine , 2017 analyses on bereavement mortality , and 2016 methodological papers on HIV population estimation . Teaching She leads Engineering Analysis (Level 4) and Numerical Skills & Economics (Level 5) modules, integrating mathematical rigor into civil engineering education.

Edward LobarinasView profile

Professor

• Hearing Loss
• Auditory Perception
• Tinnitus
• +7 more

Edward Lobarinas is a Professor and Department Head of Speech, Language, and Hearing Sciences at the University of Texas at Dallas (UTD), concurrently serving as Assistant Dean of Graduate Studies. His primary affiliation is with the School of Behavioral and Brain Sciences. Dr. Lobarinas leads the Translational Auditory Perception Lab, focusing on auditory neuroscience and clinical audiology. His research integrates animal models (chinchillas, rats) with human studies to understand hearing loss mechanisms, particularly noise-induced cochlear damage, tinnitus, and hyperacusis. Key innovations include Bayesian machine learning approaches for personalized hearing aid amplification and smartphone-integrated clinical tools. His work bridges basic science and translational medicine, with emphasis on otoprotective strategies and audiological rehabilitation. Education details are not explicitly provided in the text, though his academic roles suggest advanced training in audiology or neuroscience. His lab specializes in studying inner hair cell dysfunction, cochlear synaptopathy, and the middle ear reflex's role in hearing assessment. He has pioneered methodologies for evaluating auditory perception deficits in animal models and translating findings to human clinical applications. Notable projects include studies on carboplatin-induced hearing loss, impulse noise effects, and the efficacy of antioxidants (e.g., ebselen) in preventing noise-induced hearing loss. Dr. Lobarinas' translational research emphasizes practical solutions like adaptive dynamic range optimization (ADRO) for hearing aids and real-time smartphone apps for DSLv5 prescription fitting. His work frequently addresses gaps between audiometric thresholds and functional hearing deficits, particularly in pediatric hyperacusis and noise-exposed populations. Collaborations involve investigating blast wave effects on hearing and developing low-cost hearing conservation tools for shooters. Laboratory facilities include specialized equipment for behavioral audiometry in animals and advanced metabolic imaging techniques for tinnitus neural correlates. His publication trends since 2020 highlight machine learning applications in audiology, personalization of hearing devices, and refining animal models to better predict human auditory outcomes. While no scientific awards are listed, his prolific output and leadership roles indicate significant contributions to the field. His research also extends to dietary influences on hearing (e.g., magnesium/vitamin effects) and interdisciplinary projects integrating pharmacology, bioengineering, and computational modeling.

• Healthcare Analytics
• Operations Research
• Health Policy
• +3 more

Guihua Wang is an Assistant Professor of Management at the Naveen Jindal School of Management, University of Texas at Dallas. His research focuses on healthcare analytics, operations research, and health policy, with particular emphasis on improving healthcare system efficiency and patient outcomes through data-driven approaches. Key research themes include analyzing the impact of telemedicine on clinical decisions, evaluating policy measures like stay-at-home orders during pandemics, and optimizing organ transplantation logistics. He has contributed to understanding how public health interventions affect mobility patterns and healthcare access disparities between rural and urban areas. His work frequently employs advanced analytical methods such as instrumental variable forests and causal inference techniques to study heterogeneous treatment effects. Notable studies include examining Medicaid expansion effects on emergency department wait times and analyzing the economic implications of distant referrals for cardiac surgeries. While no formal awards are listed, his active research portfolio demonstrates engagement with critical issues in healthcare operations and policy. Advising and grant details are not specified in available materials. He is affiliated with the Jindal School's Management department and contributes to interdisciplinary projects at the university.

Metin ÇelikView profile

Professor

• Human Reliability Analysis
• Reliability Analysis
• Maritime Transportation
• +3 more

Metin Çelik is a Professor at the Department of Fundamental Sciences, Istanbul Technical University. His research focuses on human reliability analysis, maritime transportation systems, and AI applications in engineering and education. He has led projects on ship machinery monitoring, competency evaluation systems, and data-driven maritime safety solutions. His work bridges theoretical frameworks like fuzzy axiomatic design with practical implementations in maritime training and predictive maintenance. Key research interests include fault detection in marine systems, serious game design for maritime education, and deep learning-based analysis of inspection reports. His recent studies explore generative AI in competency assessment and prescriptive models for machinery failure prediction. He has received multiple Above Threshold Rewards for academic excellence (2015, 2018) and a Best Student Paper Award (2008). Active Projects : Network-Based Design of Ship Crew Competency Monitoring System (2020) Holistic Data Analytics for Ship Inspections (2022-2024) Failure Analysis Model Using GANs (2024) Grants & Funding : BAP and TUBITAK-funded projects on maritime safety systems His interdisciplinary approach integrates human factors, AI, and engineering principles to improve maritime operational reliability and training efficacy.

• Nonlinear Partial Differential Equations
• Fluid Mechanics
• Mathematical Biology
• +3 more

Yao Yao is an Associate Professor at the Department of Mathematics, National University of Singapore (NUS), and the Vice Dean of the NUS Graduate School. He holds a Ph.D. in Mathematics from UCLA (2012), with postdoctoral work at the University of Wisconsin-Madison under mentors Alexander Kiselev and Andrej Zlatoš. His research focuses on nonlinear partial differential equations (PDEs) in fluid mechanics and mathematical biology, complemented by recent work in AI applications for healthcare, including disease prediction and medical data analysis. Before joining NUS, he was an Assistant Professor at Georgia Tech's School of Mathematics. Yao Yao serves as an associate editor for several prestigious journals: Analysis and Applications , Kinetics and Related Models , Nonlinear Analysis , Nonlinearity , and SIAM Journal on Mathematical Analysis . His academic contributions span theoretical mathematics and applied AI, with a strong emphasis on interdisciplinary research bridging PDE analysis and healthcare informatics. His work in AI includes explainable deep learning models for Alzheimer’s disease prediction, graph-based patient trajectory modeling, and cybersecurity for medical survival models. He has also explored ontology-driven frameworks for personalized medicine and EHR data analysis. While no awards are explicitly listed, his editorial roles and prolific publication record highlight his influence in mathematical and computational sciences. Yao Yao’s lab focuses on mathematical modeling of biological systems and AI-driven healthcare solutions. His research has applications in cardiology, oncology, and chronic pain management, leveraging both classical PDE theory and modern machine learning techniques.

Charles VincentView profile

Senior Lecturer

• Artificial Intelligence
• Machine Learning
• Big Data Science
• +6 more

Charles Vincent is a Senior Lecturer in the Department of Information Technology, Analytics, and Operations at Queen's Business School, Queen's University Belfast. He holds multiple academic and professional fellowships, including Senior Fellow of the Higher Education Academy (SFHEA), Fellow of the British Computer Society (FBCS), and Fellow of the Royal Statistical Society (FRSS). His research focuses on the intersection of Artificial Intelligence, Machine Learning, and Management Science, emphasizing applications in business productivity, regional competitiveness, and societal welfare. Dr. Vincent has published extensively, with over 146 peer-reviewed articles, and has been recognized with awards such as the Best Developmental Paper Award (2023). He actively supervises doctoral students in areas like AI-driven innovation and blockchain technology for social impact. His work spans topics including predictive/prescriptive analytics, emotional analytics, and responsible AI governance. He is an AWS Academy Accredited Educator and serves as AWS Central Point-of-Contact for Queen's University. His professional activities include keynote speaking at global conferences, editorial roles, and advisory work for industry and government. Media engagements highlight his expertise in AI ethics, pandemic preparedness, and retirement policy. Key research interests include leveraging machine learning for efficiency assessment in manufacturing, data governance frameworks, and cross-border economic dynamics. His interdisciplinary approach bridges technical innovation with societal and policy implications.

Daniel MunizView profile

Senior Lecturer

• Exercise Physiology
• Endurance Exercise
• Physiological Thresholds
• +3 more

Dr. Daniel Muniz is a Senior Lecturer in Exercise Physiology at the University of Hertfordshire, affiliated with the Department of Psychology, Sport and Geography and the School of Life and Medical Sciences. He joined the university in 2016 and specializes in endurance exercise physiology, focusing on physiological thresholds as markers of performance and health. His research explores exercise tolerance, critical power models, and applications in marathon performance. Research interests include the role of anaerobic energy production during high-intensity exercise and the implications of physiological thresholds on endurance capacity. Current projects involve exercise intensity prescription using physiological markers, critical power models for intermittent exercise, and big data analysis in marathon performance. External roles include serving as an Affiliate Member and Rep for The Physiological Society and an External Examiner for the MSc Exercise Physiology at the University of East London. His work bridges theoretical physiology with practical applications in sports performance and health.

• Exercise Physiology
• Respiratory Medicine
• Chronic Disease Rehabilitation
• +5 more

Emily Hume is an Assistant Professor in the Sport Exercise and Rehabilitation Department at Northumbria University. Her research focuses on respiratory physiology, chronic disease rehabilitation, and digital health technologies. She specializes in gait assessment, mobility disorders, and the impact of conditions like COPD and long COVID on physical function. Hume leads studies on wearable sensor validation, exercise physiology interventions, and patient-centered outcome measures. She collaborates internationally on projects such as the Mobilise-D consortium, advancing real-world mobility monitoring technologies. Her work emphasizes translating physiological insights into clinical practice through rigorous validation and interdisciplinary approaches. Research Interests: Cardiopulmonary exercise testing in chronic diseases Wearable sensor validation for gait analysis Long-term outcomes of post-COVID-19 rehabilitation Clinical trial design for COPD interventions Recent Contributions: Hume's recent studies include validating the Late-Life Function and Disability Instrument in COPD patients and developing protocols for submaximal exercise testing in long COVID. Her 2024 work on wrist-worn gait detection and 2023 Mobilise-D consortium protocols highlight her leadership in digital health innovation. Her research bridges clinical needs with technological advancements, emphasizing practical solutions for mobility-limiting conditions. Grants & Collaboration: International multicenter studies on long-COVID rehabilitation Mobilise-D consortium for wearable sensor validation Labs/Teams: Active member of Northumbria’s Respiratory Physiology and Rehabilitation research group, focusing on translational research in chronic disease management.