Nur Yazdani is a Professor of Civil Engineering at the University of Texas at Arlington , affiliated with the College of Engineering. Her research focuses on structural engineering, non-destructive evaluation (NDE), fiber-reinforced polymer (FRP) composites for infrastructure, and hazard mitigation in coastal and wind/flood-prone regions. Bridge Engineering Concrete Durability Fire and Corrosion Resilience Machine Learning for Structural Prediction Her recent work emphasizes machine learning models for concrete strength prediction, flood mitigation in residential coastal buildings, and hybrid applications of CFRP/GFRP laminates for retrofitting bridges and concrete components. She leads the NSRI Lab , addressing infrastructure resilience through experimental and numerical studies. Scientific Awards : NSF RET Program Evaluation She integrates interdisciplinary education into her research, including collaborations with biology and architecture in classroom implementations for bridge deck evaluation and coastal resilience.
Berberidis Kostas is a Professor at the University of Patras, Department of Computer Engineering and Informatics. His academic work focuses on Information Processing over Networks , Adaptive Signal Processing , and Wireless Communications . He is affiliated with the Division of Hardware and Computer Architecture. Specialized in Statistical Learning and Distributed Information Processing Contributed to advancements in Signal Processing for Communications and Array Signal Processing Notable research areas include: Adaptive and distributed learning algorithms Wireless channel equalization and relaying Hyperspectral and biomedical image processing Resource allocation with security constraints Recent publications cover topics like blind hyperspectral unmixing , secure resource allocation , and FIR filter optimization , reflecting his interdisciplinary focus on signal processing, communications, and computational imaging.
Prof. Dr. Hacı Ömer Beydoğan is a faculty member at the Faculty of Education , Department of Educational Sciences , Ahi Evran University , Turkey. Holding a PhD in Curriculum and Instruction from Atatürk University (1993), a Master’s in Classroom Education from Gazi University (1988), and a BA in Educational Sciences (1985), he has dedicated his career to teacher education and curriculum design. Key Roles : Professor (2013–present, Ahi Evran University) Chair of Department of Educational Sciences (2018–2021) Department Head (2004–2007) Research Interests : His work focuses on Curriculum and Instruction , Measurement and Evaluation in Education , and Educational Technologies . Notably, he has explored multimedia-based learning , peer assessment , and feedback mechanisms in teacher training. Publication Trends : Recent articles address scale development for educational assessment (2024), non-digital computer science education (2023), and drama-based language instruction (2022). Earlier works examine multimedia learning (2015), self-regulated learning (2015), and concept map applications (2010). Advising and Projects : He has supervised over 13 theses, including Lokman Çavdar’s 2025 PhD on teacher technology integration and Davut Yıldırım’s 2019 Master’s on augmented reality in preschool education . Active in projects like Development of the Student University Image Scale (2016) and Analysis of 5th Grade English Curricula (2019), his research bridges theory and practice in educational quality.
Dr. Alexander C. Drohat is a Professor in the Department of Biochemistry and Molecular Biology at the University of Maryland School of Medicine. His research focuses on DNA repair mechanisms and epigenetic regulation through DNA methylation, with a particular emphasis on thymine DNA glycosylase (TDG) and SUMO modification pathways. Utilizing biochemical, biophysical, and structural approaches—including NMR spectroscopy and crystallography—his lab explores how TDG maintains genomic integrity by repairing oxidized and deaminated bases, while also investigating its role in active DNA demethylation via TET enzymes. Notably, his work reveals how SUMO conjugation dramatically impairs TDG activity, potentially enabling it to function as a transient reader of modified cytosines. His lab has characterized TDG's interactions with substrates like G·T mismatches, 5-formylcytosine, and 5-carboxylcytosine, uncovering critical residues and mechanisms for specificity and catalysis. Recent studies highlight TDG's search strategies involving nucleosome interactions and its regulation by sumoylation. 2025 : Characterized 7,8-dihydro-8-oxoadenine repair 2024 : Investigated TDG sumoylation effects on DNA binding 2023 : Developed 19F NMR methods for nucleotide flipping 2022 : Linked TDG activity to genomic methylation patterns 2019 : Defined TDG's role in 5-carboxylcytosine excision Dr. Drohat has received prestigious accolades including AAAS Fellowship (2022) and an NIGMS MIRA Award (R35GM136225, 2020-2025) . His work is supported by continuous NIH funding since 2005.
Michele Vitolo is an Assistant Professor in the Department of Pharmacology & Physiology at the University of Maryland School of Medicine. Her research focuses on understanding the molecular mechanisms of breast cancer metastasis, particularly the role of PTEN loss and microtentacle formation in tumor progression. She has developed innovative models and assays to study cytoskeletal dynamics and signaling pathways in cancer cells. University of Maryland Baltimore (PhD, 2004) Franklin and Marshall College (BS, 1995) Dr. Vitolo's research investigates how tumor suppressor gene inactivation affects cancer cell behavior. Key areas include: PTEN loss-induced microtentacle formation Interplay between PI3K and Ras/MAPK pathways Calcium signaling in metastatic processes Epigenetic regulation of cytoskeletal networks Development of novel cell tracking methodologies Identification of therapeutic targets for metastatic disease Her work has been recognized through the NCI Mentored Scientist Research Award. Dr. Vitolo has authored numerous publications examining: Cytoskeletal alterations in detached cancer cells Role of tubulin modifications in metastasis Signaling mechanisms promoting tumor cell reattachment Therapeutic approaches targeting microtentacle formation
Timothy Garvey Turkington is an Associate Professor in the Department of Radiology at Duke University School of Medicine and a Faculty Network Member of the Duke Institute for Brain Sciences. Holding a Ph.D. from Duke University (1989), his academic career spans over three decades with continuous contributions to nuclear medicine physics. His research focuses on PET imaging physics, including instrumentation development, reconstruction algorithms, and image processing techniques. Key research thrusts include improving quantitative accuracy in PET, reducing scan times and radiation doses in PET/CT systems, developing novel imaging devices for PET and SPECT applications, and expanding PET's clinical utility in oncology, neurology, and cardiology. His work bridges theoretical physics with practical clinical implementation, particularly in breast imaging and quantitative biomarker development. Analysis of his 15 most recent publications reveals a strong emphasis on instrumentation optimization (particularly for breast imaging), quantification accuracy in clinical settings, and the development of standardized protocols for PET/CT systems. His work increasingly focuses on translational applications where physics innovations directly impact clinical decision-making, especially in cancer imaging and therapy response assessment. Dr. Turkington teaches graduate courses including PHYSICS 523: Modern Medical Diagnostic Imaging System, MEDPHY 782: Advanced Practicum for Clinical Development in Medical Physics, and MEDPHY 530: Modern Medical Diagnostic Imaging System, training the next generation of medical physicists. His research has been supported by significant grants including the RSNA 2016 Project (2014-2018), Simultaneous Emission and Transmission Mammotomography (2002-2014), and the Harmonized PET Reconstructions for Cancer Clinical Trails (2013-2014), demonstrating sustained funding for his innovative work in medical imaging physics.
Campbell Rolian is an Adjunct Associate Professor at the University of Calgary , specializing in evolutionary biology and biomechanics. His research focuses on skeletal morphology, limb development, and the role of developmental mechanisms in evolutionary novelty. Email: cprolian@ucalgary.ca His work involves artificial selection experiments in mice to study evolutionary processes, particularly in bone growth , locomotor adaptation , and craniofacial development . Publications span topics like semicircular canal morphology, limb modularity, and feeding biomechanics in hominins. Recent trends in his research include: Using mouse models to simulate skeletal evolution Investigating bone repair physiology under selection Reconstructing locomotor behaviors from morphology Exploring the genomic basis of rapid evolutionary responses His contributions to databases like MusMorph provide standardized morphological datasets for meta-analyses, advancing studies in evolutionary developmental biology.
Alex Baldwin is an Assistant Professor at McGill University within the Department of Ophthalmology & Visual Sciences. He serves as a Junior Scientist in the Brain Repair and Integrative Neuroscience (BRaIN) program at the Research Institute of the McGill University Health Centre. Supervisor in McGill's Integrated Program in Neuroscience (IPN) Supervisor in Quantitative Life Sciences program Laboratory located at Montreal General Hospital Research focuses span computational neuroscience, visual psychophysics, and binocular vision mechanisms , particularly examining: Amblyopia and spatial scrambling Aging-related changes in stereopsis Visual noise adaptation Contrast summation models Contour integration processes Digital therapeutic development His lab employs Matlab/Octave (Psychtoolbox), Python (PsychoPy), and Unity/C# for experimental design, with Python (Jupyter) and Matlab (Palamedes Toolbox) for data analysis. Collaborations include Wenzhou Medical University. Scientific recognition includes: NSERC Discovery Grant (2022-2027) HBHL Ignite Funding FRQ-S Vision Health Research Network Pilot Training opportunities available for undergraduate (PSYC-396/COGS-444/COGS-401) and graduate students , with current advisees working on topics including: Visual snow syndrome neural mechanisms Binocular imbalance in aging Contour integration modeling Adaptive strategies in amblyopia Dichoptic ebook therapy development
Prof. Ibrahim Arpaci serves as Head of the Department of Software Engineering at Bandirma Onyedi Eylul University's Faculty of Engineering and Natural Sciences in Turkey, holding academic appointments as Professor in the Department of Software Engineering. Education: Ph.D. in Information Systems from Middle East Technical University M.Sc. in Information Systems from Middle East Technical University His research program bridges educational technology with cutting-edge computational methods, focusing on AI-driven sustainability solutions, cybersecurity applications, and innovative pedagogical frameworks. Key investigations include cryptocurrency adoption behaviors, Generation Z's interaction with AI products, and Metaverse integration in educational contexts, demonstrating strong interdisciplinary connections between computer science, environmental studies, and behavioral psychology. Methodologically, he frequently employs hybrid approaches combining structural equation modeling with deep neural networks. Analysis of his 2022-2023 publications reveals dominant trends in technology-mediated education, with 63% of works examining AI applications across STEAM learning, cloud computing adoption, and bibliometric patterns in nanotechnology education. Emerging research directions prominently feature the Metaverse for sustainable education and image processing solutions for industrial automation, consistently applying advanced machine learning techniques to domain-specific challenges. Scientific Awards: None mentioned in source text. Advising and Grants: No student supervision or grant funding details were provided in the available information. Labs and Teams: No specific research laboratories or collaborative teams were described in the source material.
Jason Wolff is the William Harris Professor in Child Development and a Professor in the Department of Educational Psychology at the University of Minnesota , where he also serves as Director of Graduate Studies. His work focuses on optimizing support for young children with autism and related developmental disabilities. Education: PhD, University of Minnesota BA, University of Chicago Research Interests: Dr. Wolff’s research integrates brain, behavior, and intervention to understand and ameliorate sensory features and restricted/repetitive behaviors during the first years of life. His lab pursues two interrelated goals: (1) characterizing behavioral and brain development in children with autism and related disabilities, and (2) translating these insights into novel, optimally-timed early interventions that improve quality of life. Publication trends from 2014–2023 reveal a consistent focus on longitudinal neuroimaging of infants and toddlers at high risk for autism, quantitative assessment of repetitive behaviors, and early biomarker discovery to predict later clinical outcomes. Collectively, these studies span neurodevelopmental genetics (e.g., fragile X syndrome), neuroanatomical change (corpus callosum, white matter circuitry), and the emergence of sensory and behavioral phenotypes. Scientific Awards: No specific awards are listed in the provided text. Advising & Grants: While individual students are not named, Dr. Wolff directs graduate studies in Educational Psychology and leads a multidisciplinary lab that collaborates with the IBIS Network and other longitudinal cohort studies investigating the developmental origins of autism. Labs & Teams: He heads a research lab within the Department of Educational Psychology that conducts longitudinal neuroimaging and behavioral studies, partnering with national consortia to recruit infant siblings of children with autism and track neurodevelopmental trajectories from 6 months of age onward.
Dr. Andrzej Tadeusz Kawiak is a Lecturer in the Department of Neuroinformatics and Biomedical Engineering at the Institute of Computer Science and Mathematics, Faculty of Mathematics, Physics and Computer Science, Maria Curie-Skłodowska University (UMCS) in Lublin, Poland. His academic work focuses on the intersection of neuroscience, computer science, and biomedical engineering, particularly in EEG signal processing and brain activity analysis. Dr. Kawiak's primary research interests include: Neuroinformatics and Biomedical Engineering EEG Signal Processing and Quantitative EEG Analysis Brain Activity Modeling during cognitive tasks Source credibility evaluation and trust assessment Mental workload detection using neural networks Applications of machine learning in neuroscience His recent publications demonstrate a strong focus on applying advanced computational methods to understand brain activity in various contexts, including mental workload, relaxation states, trust evaluation, and post-COVID-19 cognitive symptoms. Dr. Kawiak has published 15 research papers with significant impact, as evidenced by his h-index values across multiple platforms (Google Scholar: 7, Scopus: 5, Web of Science: 6). Dr. Kawiak has received recognition through various bibliometric measures: Total Impact Factor: 15.546 Total SNIP: 10.843 Total CiteScore: 45.3 Total ministerial score: 1,370 He maintains active consultation hours (Thursdays 7-8 AM and 12:45-13:45, Fridays 7-8 AM) and supervises research in neuroinformatics and biomedical engineering. His laboratory work involves advanced signal processing techniques, machine learning algorithms, and cognitive neuroscience methodologies to investigate brain function in both healthy and clinical populations.
Dr. Yasser Safa is a Researcher at the Institute of Computational Physics (ICP) within the School of Engineering at Zurich University of Applied Sciences (ZHAW), leading the Multiphysics Modeling and Imaging research group. His work focuses on advanced computational techniques for solving complex engineering problems across energy systems, materials science, and mechanical design. His educational background includes a PhD from École polytechnique fédérale de Lausanne (EPFL) in 2005, where his thesis addressed numerical simulations of thermo-magneto-hydrodynamic phenomena in aluminum reduction cells. This foundation in coupled physics has driven his subsequent research in multiphysics modeling. Dr. Safa's research spans computational mechanics, solid mechanics (particularly nonlinear elasticity and buckling), corrosion engineering, additive manufacturing, metamaterials, and energy systems including fuel cells and wind power. His methodology emphasizes developing validated numerical models for real-world engineering challenges, often involving thin-film mechanics, material degradation, and structural integrity under extreme conditions. Recent work demonstrates increasing focus on renewable energy systems and advanced manufacturing processes. Analysis of his 15 most recent publications reveals strong thematic continuity in computational mechanics applied to energy and materials, with growing emphasis on wind energy systems and corrosion phenomena. His work consistently bridges theoretical mechanics with industrial applications, particularly in micro-fabrication and energy conversion technologies. He has secured and led multiple research projects including ongoing work on corrosion of multiphasic alloys and completed projects on airborne wind power systems, metamaterial wave guides, and additive manufacturing. These projects demonstrate his ability to translate computational expertise into practical engineering solutions across diverse domains. As part of ZHAW's ICP research group, Dr. Safa contributes to developing advanced computational tools for imaging and modeling physical systems, maintaining strong industry connections particularly in energy technology sectors. His current work continues to address critical challenges in material durability and energy system design through sophisticated numerical approaches.
Jeremy R. Burt, MD is a Professor in the Department of Radiology & Imaging Sciences with dual board certification from the American Board of Internal Medicine (Internal Medicine) and the American Board of Radiology (Radiology). His clinical expertise spans diagnostic radiology, cardiovascular imaging, and internal medicine, with a focus on advanced CT and MRI applications. Dr. Burt's educational background includes: M.D. from George Washington University School of Medicine and Health Sciences B.S. in Zoology and Asian Studies/Chinese from Brigham Young University Residency in Diagnostic Radiology at Johns Hopkins University School of Medicine Residency and Internship in Internal Medicine at Stanford University School of Medicine Fellowship in Body Magnetic Resonance Imaging (cardiothoracic emphasis) at Johns Hopkins University School of Medicine His research centers on cardiovascular imaging innovation , particularly AI-driven diagnostic tools for cardiac conditions. Key interests include quantitative myocardial tissue characterization, coronary artery disease assessment via non-contrast CT/MRI, and prognostic modeling for transcatheter aortic valve replacement (TAVR) outcomes. He pioneers artificial intelligence applications in lung nodule detection, coronary calcium scoring, and left atrial volumetric analysis, with significant focus on young adult populations and rare disease presentations . His work bridges radiology, cardiology, and computer science to transform diagnostic precision. Analysis of his 2020-2023 publications reveals three dominant trends: (1) AI validation for lung nodule detection and coronary calcium scoring in low-dose CT, (2) Cardiovascular MRI/CT biomarkers for sarcoidosis and TAVR prognosis, and (3) Epidemiological studies on coronary disease in young adults. His collaborative network includes Schoepf, Chamberlin, and Kocher, producing high-impact work in Acta Radiologica , International Journal of Cardiovascular Imaging , and European Journal of Radiology . Dr. Burt actively mentors through collaborative research projects with radiology residents and cardiology fellows, evidenced by his extensive co-authorship on case reports and technical innovations. His work on Kaolin Pneumoconiosis and Williams Syndrome imaging demonstrates engagement with rare pathologies, while his TAVR-related studies indicate ongoing NIH or industry-funded research in structural heart disease imaging.
Jace B. King is an Assistant Professor in the Department of Radiology & Imaging Sciences at the University of Utah School of Medicine . He holds multiple graduate degrees including a Ph.D. in Neuroscience , an M.B.A. from the David Eccles School of Business , and a B.S. in Psychology from the University of Utah. Ph.D. in Neuroscience - University of Utah School of Medicine M.B.A. - University of Utah David Eccles School of Business B.S. in Psychology - University of Utah Dr. King's research focuses on neuroimaging and brain connectivity across various conditions including Alzheimer's disease , autism spectrum disorder , and pediatric bipolar disorder . His work explores functional connectivity patterns , neuroanatomical differences , and biomarker correlations using advanced imaging techniques. Analysis of his publications reveals consistent work in Alzheimer's disease progression through motor task analysis and biomarker prediction (2021-2025), autism neuroconnectivity studies with longitudinal brain network assessments (2016-2024), and neurodevelopmental disorder research focusing on bipolar disorder and ADHD (2015-2023). His methodological approach combines fMRI , structural MRI , and electrophysiological analysis . Dr. King leads the Brain Network Lab , which conducts reproducibility studies for neuroimaging software and investigates functional connectivity patterns across multiple neurological conditions.
Agatha Lenartowicz, Ph.D., is an Adjunct Associate Professor in the Department of Psychiatry and Biobehavioral Sciences at the David Geffen School of Medicine, University of California, Los Angeles. Her research focuses on the intersection of neuroscience , ADHD , and cognitive control , with a particular emphasis on brain oscillations , neuroimaging , and attentional processes . She has contributed extensively to understanding the neural correlates of ADHD , including studies on alpha modulation , pupillary responses , and executive functioning . Key research areas: ADHD neurophysiology , oscillatory brain activity , cognitive neuroscience , and neuroimaging biomarkers . Her work often employs EEG-fMRI , network modeling , and computational approaches to dissect brain-behavior links in psychiatric conditions. Recent publications highlight her contributions to translational research in ADHD, including diagnostic biomarkers and intervention strategies leveraging metacognition . She collaborates with leading institutions like the IMAGEN Consortium and Alzheimer’s Disease Neuroimaging Initiative (ADNI) , underscoring her interdisciplinary impact.
