جست‌وجوی استاد و پژوهشگر

Eugenia Loمشاهده پروفایل

دانشیار

• Molecular Epidemiology
• Parasite Genomics
• Host-Parasite Interactions
• +۳ مورد دیگر

Eugenia Lo, PhD, is an Associate Professor in the Department of Microbiology & Immunology at Drexel University College of Medicine. She holds a PhD in Ecology and Evolutionary Biology from the University of Toronto and completed a postdoctoral fellowship at Yale University. Her research focuses on molecular epidemiology, parasite genomics, and host-parasite interactions, particularly in malaria (Plasmodium species). Her work addresses global health challenges, including malaria transmission dynamics in sub-Saharan Africa and mechanisms of parasite adaptation to Duffy-negative hosts. Educations: PhD - Department of Ecology and Evolutionary Biology, University of Toronto BS - Environmental Science, University of Hong Kong Postdoctoral Fellow, Yale University Research Interests: Dr. Lo’s lab investigates the genetic basis of malaria parasite invasion, particularly how Plasmodium vivax adapts to Duffy-negative populations in Africa. Key areas include molecular epidemiology, parasite genomics, and the development of genomic tools for malaria surveillance. Her work integrates field-based epidemiological data with molecular biology and 'omics approaches to study transmission patterns and control strategies. Scientific Awards: COLC Travel Award, University of California Irvine (2017) Travel Award, Symposium on Phylogenomics (2014) Evolution Conference Travel Award, Society of Systematic Biology (2014) Advising & Grants: Dr. Lo mentors postdoctoral fellows (Cheikh Cambel Dieng, Bernis Yengo), graduate students (Kareen Pestana, Beka Abagero, Tassew Shenkutie), and undergraduate researchers (Canelle Kipayko). Her grants support studies on malaria genomics, vaccine efficacy, and diagnostic tool development in high-burden regions. Labs/Teams: The Lo Lab at Drexel collaborates globally on malaria research, with fieldwork in Ethiopia, Kenya, and Myanmar. The lab’s interdisciplinary approach combines evolutionary biology, genomics, and public health to combat malaria transmission.

Antje Gumzمشاهده پروفایل

استاد

• Psychotherapy Research
• Psychodynamic Psychotherapy
• Therapeutic Relationship Skills
• +۹ مورد دیگر

Professor Antje Gumz holds a Professorship for Psychosomatics and Psychotherapy with a focus on Depth Psychology-Based Psychotherapy at the Psychologische Hochschule Berlin (PHB). She leads a dedicated working group focused on psychotherapy research and training, with particular emphasis on therapeutic relationship skills, alliance ruptures, and psychodynamic concepts. Her academic work bridges clinical practice and scientific research, contributing significantly to the field of psychotherapy. Dr. Gumz's research interests span multiple dimensions of psychotherapy, with particular focus on measuring and training therapeutic relationship skills, including alliance ruptures, facilitative interpersonal skills, dealing with transference/countertransference, and enactments. She investigates mediators of therapy success and the role of language and voice in psychotherapy, bringing a unique perspective that integrates psychodynamic and systems theory concepts. Her work emphasizes the importance of understanding the therapist's role in therapeutic tensions and crises, and how these can be transformed into opportunities for therapeutic advancement. Professor Gumz has published extensively on psychotherapy techniques and training, with numerous publications in leading journals. Her recent work focuses on the development of assessment tools like the Psychodynamic Intervention List (PIL) and the Mediators of Change in Psychotherapy Inventory (MoCPI). Her research demonstrates how specific verbal techniques relate to session quality and therapeutic outcomes, providing empirical support for clinical practice. Heigl Foundation Research Grant (2019-2025) for therapist interpersonal skills research German Psychoanalytic Society Research Grant (2017-2019) for therapeutic techniques studies Professor Gumz actively supervises numerous doctoral students and research assistants, fostering the next generation of psychotherapy researchers. Her work extends beyond academia through collaborations with multiple psychotherapy training institutes across Germany. She has developed innovative training approaches like the Modified Alliance-Focused Training with Doubling (MAFT-D) to improve therapists' competencies in handling therapeutic tensions. Her research group maintains strong national and international collaborations, contributing to evidence-based psychotherapy training and improved treatment outcomes.

Satish Nagarajaiahمشاهده پروفایل

استاد

• Structural Dynamics
• Earthquake Engineering
• Seismic Isolation
• +۱۲ مورد دیگر

Satish Nagarajaiah is a tenured Professor at Rice University with joint appointments in the Civil & Environmental Engineering Department , Mechanical Engineering Department , and affiliation with Materials Science and Nano-Engineering . His research spans structural dynamics , earthquake engineering , seismic isolation , and adaptive stiffness systems , with significant contributions to negative stiffness , smart tuned mass dampers , and strain sensing using nanomaterials . Joint appointments across Civil, Mechanical, and Materials Science departments Developed 3D-BASIS software for nonlinear dynamic analysis of base-isolated structures Recipient of NSF CAREER Award , ASCE Moissieff Award , and multiple ASCE medals Research Interests include: Nonlinear dynamic analysis of seismic systems Adaptive passive stiffness and control mechanisms Machine learning and computer vision for sparse structural identification Nanocomposite-based strain sensing (contact/noncontact) Development of smart skins and optical sensors for structural health monitoring Scientific Awards include: NSF CAREER Award (1998-1999) ASCE Moissieff Award (2015) Raymond C. Reese Research Prize (2017) Nathan M. Newmark Medal (2020) George W. Housner Medal (2025) Fellow, U.S. National Academy of Inventors (2019) Distinguished Member, ASCE (2021) Editorial Leadership includes Senior Editor of Mechanical Systems and Signal Processing (Elsevier, 2017-2019, 2024-present), Editor of Structural Control and Health Monitoring (Wiley, 2008-2022, 2024-present), and Editor-in-Chief of Structural Monitoring and Maintenance (Techno-Press, 2014-2024).

• Time series analysis
• Changepoint analysis
• Signal processing
• +۶ مورد دیگر

Xueheng Shi is an Assistant Professor in the Department of Statistics at the University of Nebraska-Lincoln (UNL), with a joint appointment in Biological System Engineering . He joined UNL in August 2022 after postdoctoral positions at UC Santa Cruz (2020–2021) and UC Davis (2021–2022) under mentors Robert Lund, Alexander Aue, and Thomas Lee. Dr. Shi teaches graduate courses including mathematical statistics, asymptotic theory, probability, stochastic processes, and time series analysis. Research Interests: Dr. Shi's work focuses on developing statistical methodologies for time series analysis , changepoint detection , and high-dimensional data . Key applications include climate science, signal processing, and machine learning. His research emphasizes computational algorithm development and theoretical foundations across domains like climate modeling and stochastic optimization. Publications: Recent articles (2019–2024) concentrate on climate change detection , particularly global warming trends and temperature series analysis. Methodological innovations include autocovariance estimation around changepoints, comparative studies of detection algorithms, and reviews of best practices in climatological statistics. Dominant themes are changepoint techniques, environmental data diagnostics, and statistical computing. Advising: Dr. Shi actively mentors graduate students in statistics and invites prospective applicants interested in his research areas to contact him directly.

Len Gelmanمشاهده پروفایل

استاد

• Signal Processing
• Condition Monitoring
• Vibration Analysis
• +۴ مورد دیگر

Len Gelman is a Professor and Chair in Signal Processing and Condition Monitoring at the University of Huddersfield's Department of Engineering within the School of Computing and Engineering. He also serves as Director of the Centre for Efficiency and Performance Engineering. His research focuses on advanced signal processing techniques for fault diagnosis in electromechanical systems, vibration analysis, and predictive maintenance. He is actively involved in PhD supervision and has authored over 100 publications, achieving 1499 citations and an h-index of 21. Key research areas include digital twin technology, nonlinear spectral analysis, and machine learning for industrial diagnostics. His work addresses challenges in non-stationary signal processing, motor current signature analysis, and condition monitoring under varying operating conditions. Collaborations include interdisciplinary projects with the Centre for Efficiency and Performance Engineering. Recent studies highlight innovations in fault diagnosis frameworks for rotating machinery, conveyor belt systems, and wind turbines. His contributions bridge theoretical advancements with practical industrial applications, emphasizing explainable AI and adaptive diagnostics. Gelman's research has been presented at major conferences like the World Congress on Engineering and published in specialized journals. Education: Not explicitly stated in the provided text. Awards: High citation count and h-index reflect his significant academic impact. Grants/Advising: Supervised 2 PhD projects; accepting new students in diagnostic engineering and condition monitoring. Labs/Teams: Leads the Centre for Efficiency and Performance Engineering and collaborates with the Department of Engineering's research groups.

Will Fleesonمشاهده پروفایل

استاد

• Personality Psychology
• Moral Behavior Dynamics
• Dynamic Personality Models
• +۴ مورد دیگر

Will Fleeson is a Professor of Psychology at Wake Forest University, specializing in personality dynamics, moral behavior, and the integration of trait theories with dynamic systems. His research focuses on understanding how personality traits manifest in real-world behaviors, particularly in contexts involving morality, psychopathology, and virtue ethics. He leads the Fleeson Lab, exploring topics such as honesty, virtue profiles, and the interplay between personality and psychological well-being. Central to his work is the Whole Trait Theory, which emphasizes the dynamic nature of personality as both structural and process-oriented. Fleeson employs methodologies like experience sampling and multilevel modeling to examine intra-individual variability and situation-based contingencies. His studies often bridge philosophical and psychological perspectives, particularly in defining moral exceptionalism and intellectual virtues. Key research themes include the dynamics of borderline personality disorder symptoms, the measurement of honesty and virtue, and the motivational underpinnings of moral behavior. Fleeson’s contributions challenge traditional static trait models, advocating for frameworks that account for temporal fluctuations and situational influences. Despite the absence of listed awards or grants in the provided text, his extensive publication record underscores his influence in advancing dynamic personality theory and moral psychology. His lab’s website (linked) highlights ongoing projects and collaborations, though specific advisees or teams are not detailed here. Fleeson’s work consistently emphasizes the practical implications of personality research for understanding mental health, ethical behavior, and individual flourishing.

IMRAN Bashirمشاهده پروفایل

مدرس ارشد

• Acoustic Metamaterials
• Aeroengine Acoustics
• Condition Monitoring
• +۳ مورد دیگر

Dr. IMRAN Bashir is a Senior Lecturer in Instrumentation & Control Engineering at Teesside University's SCEDT Engineering Centre for Sustainable Engineering. He holds a PhD in Acoustics Metamaterials from an EU-FP7 funded project and has extensive postdoctoral experience across the University of Bath, Southampton, and Exeter. His research focuses on acoustic metamaterials, aeroengine acoustics, and condition monitoring. Education: PhD in Acoustics Metamaterials (EU-FP7 HOSANNA Project) MSc in Data Communication (University of Sheffield) BEng in Electrical Engineering (COMSATS University, Pakistan) His research interests span acoustic metamaterials, aeroengine acoustics, vibration control, and signal processing. He leads projects like the EU Horizon 2020 AERIALIST initiative for noise reduction in aeronautics. Current work includes smart bearing systems for aeroengines and condition monitoring for wave energy devices. Collaborations include multi-university projects on hydrogen production and sustainable engineering. He has published extensively in peer-reviewed journals and conferences, with a focus on battery diagnostics, acoustic modeling, and smart systems. As a Co-Investigator in the Hydrogen Production Life-Cycle project (2024–2026), he contributes to knowledge transfer for emerging energy markets. His interdisciplinary approach bridges engineering disciplines, emphasizing practical applications in aerospace, energy, and environmental acoustics.

• Autonomous Systems
• Signal Processing
• Vehicle Health Management
• +۷ مورد دیگر

Dr Ivan Petrunin is a Research Professor in Signal Processing for Autonomous Systems and a DARTeC Fellow at Cranfield University's School of Aerospace, Transport and Manufacturing. His work focuses on advancing sensor technologies, data fusion, and decision-making systems for Cyber-Physical Systems, with applications in aerospace, ground-based autonomous systems, and urban air mobility. Key areas include Position, Navigation and Timing (PNT), vehicle health management, and AI-driven fault detection. He leads research at facilities like the Muti-User Environment for Autonomous Vehicle Innovation (MUEAVI) and collaborates with industry partners like Airbus, Rolls-Royce, and Thales. Education: BSc and MSc in Design of Electronic Equipment from National Technical University of Ukraine (1996–1998), followed by a PhD in Signal Processing for Condition Monitoring from Cranfield University (2013). Prior to Cranfield, he was a Lecturer in Digital Signal Processing at NTU Ukraine (2001–2005). Research Interests: Autonomous Systems & Sensor Fusion Machine Learning in Navigation and Safety GNSS Integrity & Urban Air Mobility Condition Monitoring & Structural Health Multi-Agent Reinforcement Learning Publications: Over 100 journal/conference articles and book chapters, with recent works emphasizing hybrid sensor fusion, resilient navigation architectures, and AI-driven solutions for GNSS-denied environments. Notable contributions include multi-sensor fusion frameworks for UAVs and Bayesian filter innovations. Awards: FRIN Fellowship, SMAIAA Membership, IEEE and ION Fellowships, and FHEA recognition. His work is supported by ESA, Innovate UK, and EPSRC. Advising & Labs: Supervises PhD students in UAV navigation and machine learning. Leads Cranfield's facilities for autonomous systems experimentation and advanced timing node infrastructure.

Victor M. Brightمشاهده پروفایل

استاد

• Micro/Nanoelectromechanical Systems
• Optical Engineering
• MEMS Technology
• +۳ مورد دیگر

Victor M. Bright is a Professor and Assistant Vice Chancellor for Research Micro/Nanoscale at the University of Colorado. His research focuses on Micro/Nanoelectromechanical Systems (MEMS), electrowetting-based optical devices, and advanced imaging technologies. Key contributions include innovations in electrowetting lenses, microLED arrays for microscopy, and biomedical imaging systems. His work integrates MEMS fabrication, optical engineering, and material science to develop novel optical components and imaging solutions. His laboratory develops miniature, high-resolution imaging systems such as the Opto2P-FCM microscope and advanced tunable lenses for applications in neuroscience and optical coherence tomography. Recent efforts emphasize real-time monitoring of membrane fouling via Raman spectroscopy and high-speed calcium imaging in live tissues. Publications highlight advancements in adaptive optics, structured illumination microscopy, and MEMS-based devices. His research addresses challenges in precision manufacturing, optical system miniaturization, and biomedical diagnostics. The laboratory website and full CV provide further details on ongoing projects and collaborations.

• Industrial Livestock Production
• Digital Farming
• Antimicrobial Resistance
• +۷ مورد دیگر

Kin Wing (Ray) Chan is a Wellcome Research Fellow (2022-2025) at the Royal Agricultural University, specializing in industrial livestock production, digital farming, and antimicrobial resistance. His interdisciplinary research integrates Human Geography, Veterinary Science, and Science and Technology Studies to examine relationships between precision livestock technologies, biopolitics, and animal production. Education PhD Geography and Planning, Cardiff University, UK MA Human Geography, University of Calgary, Canada BA (First Class Honours) Geography, Hong Kong Baptist University, Hong Kong Research Focus Chan's work explores how farming technologies and governance structures impact animal health and antimicrobial resistance across UK and Chinese agricultural systems. His research spans: Digital livestock management systems One Health approaches to disease control Farmer decision-making processes Environmental governance in agriculture Research Leadership He leads significant projects including a £197k Wellcome Trust fellowship on digital animal health technologies in China and coordinates international networks on biosecurity and antimicrobial resistance. His publications demonstrate consistent focus on veterinary practices, agricultural governance, and farmer behaviors, with recent work emphasizing diagnostic technologies and regulatory frameworks. Awards and Grants Wellcome Research Fellowship (2022-2025) AWRN Kick-Start Award (2024-2025) Multiple collaborative grants from ESRC, COST-Action, and GW4 Teaching At RAU, Chan leads modules on: Advanced Dairy Chains Global Meat Chains Editorial Contributions Editorial Board: Springer Nature Humanities & Social Sciences (2023-present) Review Editor: Frontiers in Veterinary Science (2018-present) Regular peer reviewer for 15+ journals

Steven Abellمشاهده پروفایل

استاد

• Clinical Psychology
• Personality Theory
• Psychoeducational Assessment
• +۱ مورد دیگر

Dr. Steven Abell is a Professor of Psychology at the University of Detroit Mercy, board-certified in clinical psychology. With over 25 years at the university, he has served as department chair and directed clinical psychology programs. His work integrates psychoanalytic theory, personality assessment, and psychotherapy. Publications address gender bias in child diagnosis, body image, and adolescent development. Abell teaches courses on abnormal psychology, personality theory, and psychotherapy practicum.

Jane Wangمشاهده پروفایل

استاد

• Biological Physics
• Theoretical Condensed-Matter Physics
• Computational Fluid Dynamics
• +۴ مورد دیگر

Affiliations and Roles Professor Wang holds dual appointments as Professor of Physics and Mechanical and Aerospace Engineering at Cornell University. She is affiliated with the Sibley School of Mechanical and Aerospace Engineering and the College of Arts and Sciences. Education B.S. in Physics, Fudan University, Shanghai, China (1989) Ph.D. in Physics, University of Chicago (1996) NSF-NATO Postdoctoral Fellow, Theoretical Physics, Oxford University (1997) Visiting Member, Courant Institute of Mathematical Sciences, NYU (1997-1999) Research Her research focuses on the physics of living organisms, particularly insect flight dynamics , biophysics , and computational modeling . Key projects include: Dragonfly righting reflex mechanisms Neuro-mechanical control in fruit flies Unsteady aerodynamics and fluid-structure interactions Awards and Honors Simons Fellowship in Theoretical Physics (2020) Radcliffe Fellowship (2007) Cornell Provost's Award for Distinguished Scholarship (2005) David and Lucile Packard Fellowship (2002) Labs and Collaborations Her work integrates experimental and computational approaches, often conducted in collaboration with institutions like the Janelia Research Campus (HHMI) and the Joint Texas Experimental Tokamak (J-TEXT).

• Neuroscience
• Psychiatry
• Addiction Medicine
• +۵ مورد دیگر

Dr. Jean King is an Adjunct Professor at UMass Chan Medical School's Department of Psychiatry and Behavioral Sciences, affiliated with the T.H. Chan School of Medicine. She holds dual roles in the Radiology department as part of her other academic positions. Her educational background includes a BS in Biology from Saint Francis College, an MS in Cell Biology from City University of New York, and a PhD in Biology/Neurophysiology from New York University. Her research focuses on translational neuroimaging to study brain alterations linked to stress-related conditions such as addiction, ADHD, and traumatic brain injury (TBI). Recent work extends to co-morbid mental health disorders and stress mitigation strategies like mindfulness. Her lab employs both preclinical models and clinical populations to explore neural mechanisms of emotional/cognitive processing under stress. Key publications (2014–2020) investigate neural connectivity in ADHD, nicotine dependence pathways, concussion bioenergetics, and mindfulness-based interventions. Dr. King has received over 20 awards including the NIH-funded NCCIH grant (2017–2020), multiple mentorship accolades, and the University of Massachusetts President’s Public Service Award. Her work bridges neuroscience, psychiatry, and clinical applications, with a focus on translational research. Lab activities include multi-modal imaging studies (fMRI, MRS) and behavioral assessments in both human and animal models. Current projects explore the neurobiological basis of stress resilience and cognitive recovery post-TBI. Collaborations span addiction medicine, mental health, and neurodegenerative disease research.

Stefano Buosoمشاهده پروفایل

مدرس

• Biomedical Engineering
• Cardiovascular Modeling
• Computational Fluid Dynamics
• +۴ مورد دیگر

Dr. Stefano Buoso is a Lecturer at ETH Zürich's Department of Information Technology and Electrical Engineering, specializing in biomedical imaging and computational mechanics. His research focuses on cardiovascular modeling, fluid-structure interaction, and reduced-order modeling. He holds a position in the Professur für Biomedizinische Bildgebung (Biomedical Imaging Professorship). Key research areas include computational fluid dynamics applied to cardiovascular systems, development of machine learning tools for medical imaging (e.g., MRI and echocardiography), and creation of patient-specific numerical phantoms. His work bridges engineering and medicine, with applications in clinical diagnostics and personalized medicine. Recent articles emphasize innovations like automated 3D heart modeling from 2D echocardiography, synthetic MRI data generation, and turbulence analysis in aortic flow. He has developed open-source tools like CMRsim for cardiovascular simulations. Buoso collaborates on digital twin technologies for carotid artery disease assessment and fluid dynamics modeling of biological systems. His technical contributions include methods for rapid mesh generation, stabilized reduced-order models, and MRI-guided cardiac shape modeling. Research spans from microvascular neurovascular unit studies to bio-inspired membrane wing aerodynamics, reflecting interdisciplinary expertise.

• Genetic Disorders
• Human Infertility
• Embryonic Development
• +۳ مورد دیگر

Odelya Hartung Kaufman, MD, PhD, is a Clinical Geneticist and Associate Research Scientist in the Department of Genetics at Yale School of Medicine. She specializes in diagnosing and managing genetic conditions in children and adults, with expertise in developmental disabilities, inherited eye disorders, hearing loss, and congenital birth defects. Her research focuses on genetic mechanisms underlying early embryonic defects, human infertility (e.g., unexplained female infertility and recurrent pregnancy loss), and rare undiagnosed diseases via the Undiagnosed Disease Network. Education & Training: MD and PhD in Biomedical Sciences from Albert Einstein College of Medicine (2016) Pediatrics and Medical Genetics Residency at Mount Sinai Hospital (2020) Research Interests: Dr. Kaufman’s work combines clinical practice with research into genetic causes of rare diseases. Her studies utilize zebrafish models to investigate RNA binding proteins’ roles in ovary development and Balbiani body architecture. Recent publications highlight advancements in understanding nutrient sensing pathways and genetic mutations linked to syndromes like Shwachman–Diamond syndrome. Awards & Grants: No specific awards listed, though her work aligns with NIH-funded initiatives through the Undiagnosed Disease Network. Grants and funding sources are not detailed in the provided text. Labs & Teams: Member of the Jiang Lab at Yale School of Medicine, collaborating on interdisciplinary projects at the intersection of genetics and clinical care.