جست‌وجوی استاد و پژوهشگر

• Entomology
• Molecular Biology
• Genetics
• +۳ مورد دیگر

Frank W. Avila is a Researcher at the University of Antioquia (Medellín, Colombia) since July 15, 2016, focusing on mosquito reproductive biology and vector control. His research integrates molecular genetics, microbiology, and entomology to study Aedes and Anopheles mosquitoes. His work examines: seminal fluid proteins and their physiological impacts Wolbachia symbiont effects on vector behavior microbiota dynamics in reproductive tracts age-related fertility changes acoustic communication in mating transcriptomic responses to mating and blood-feeding Recent publications (2025-2020) reveal trends in: mosquito reproductive physiology microbiome-vector interactions Wolbachia-based control strategies post-mating behavior genetics non-invasive age-grading technologies sperm storage/degradation mechanisms Peer review activities include journals like Communications Biology , Journal of Insect Physiology , and PLOS Genetics .

• Semiconductors
• Optoelectronics
• Photonics
• +۳ مورد دیگر

Jean-Pierre Landesman serves as an Adjunct Professor in the Department of Engineering Physics at McMaster University, with scholarly activity spanning over 30 years and recent publications extending to 2025. His work centers on semiconductor device physics, specifically III-V materials systems including InP and GaAs, with emphasis on experimental characterization of fabrication-induced mechanical effects. Landesman's research interests focus on semiconductor stress phenomena, optoelectronic device reliability, and photonic materials engineering. He specializes in spatially-resolved luminescence techniques (micro-photoluminescence, cathodoluminescence) to quantify mechanical strain in laser diodes and quantum well structures. Key areas include plasma etching damage analysis, silicon nitride film property optimization for photonics, and automotive-grade component qualification under high-temperature stress. Analysis of his 2021-2025 publications reveals consistent expertise in correlating mechanical stress with optical properties in III-V devices. He frequently employs finite element simulations (FEM) to model strain distributions from dielectric films and etching processes, publishing in journals like Journal of Vacuum Science and Technology, Applied Optics, and ECS Meeting Abstracts. His work bridges semiconductor processing, materials characterization, and device performance validation. No scientific awards or honors were documented in the provided text. Landesman instructs the graduate course ENGPHYS 723 (Semiconductor Diode Laser Physics) in 2025, 2024, 2022, and 2019. While his publication record indicates active research collaboration, the text lacks specifics about PhD/Master's students, grant funding, or project leadership. Automotive reliability studies suggest industry partnerships, but no funding sources are named. The provided information does not reference any dedicated laboratory, research team, or institutional facilities under his direct leadership.

Johan Lindمشاهده پروفایل

دانشیار

• Behavioral Ecology
• Cognitive Science
• Evolutionary Biology
• +۴ مورد دیگر

Johan Lind is a senior associate professor in ethology at Linköping University and deputy director of the Centre for Cultural Evolution at Stockholm University. His research focuses on the evolutionary mechanisms underlying animal and human cognitive capacities, particularly in memory, associative learning, and cultural development. He has held postdoctoral and visiting fellowships at St Andrews University and Cambridge University, respectively. Key Research Areas: Cognitive evolution, associative learning, human cultural uniqueness, and behavioral ecology Notable Contributions: Critique of Dunbar's number, development of A-learning theory, analysis of sequence representation in cognition Scientific Awards: No explicit awards mentioned in the provided texts. Collaborations: Regular collaborator with Stefano Ghirlanda and Magnus Enquist on associative learning models and cognitive evolution.

Jon Michael Granمشاهده پروفایل

استاد

• Biostatistics
• Causal Inference
• Lifetime Analysis
• +۴ مورد دیگر

Jon Michael Gran is a Professor at the Department of Biostatistics , Institute of Basic Medical Sciences (IMB), University of Oslo, since 2022. He also holds a 20% senior researcher position at the Norwegian Institute of Public Health since 2024. PhD in Biostatistics (University of Oslo, 2011) MSc in Statistics (NTNU, 2005) His research focuses on causal inference , lifetime analysis , multistate models , and epidemiological methods , with applications in infectious disease modeling, clinical data analysis, and public health policy evaluation. Recent work examines opioid use in trauma patients, prenatal drug exposure effects, and interventions for inclusive working life. Publications (2025-2023) span journals like Acta Anaesthesiologica Scandinavica , Biometrika , and JAMA Network Open , emphasizing translational biostatistical methods applied to clinical registries and public health datasets. Notable collaborations include the Causal Inference Research Group and IPOT project on trauma outcomes. He serves as Associate Editor for Biometrika (since 2018) and Statistics in Medicine (since 2025), with teaching roles in medical statistics and machine learning at the University of Oslo.

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +۳ مورد دیگر

Ioanna Ntinou is a Visiting Professor at Queen Mary University of London's School of Electronic Engineering and Computer Science. She teaches the Artificial Intelligence undergraduate module, focusing on core AI techniques like search algorithms, logic, and decision theory. Her research emphasizes computer vision, deep learning, and action recognition in videos, with contributions to spatio-temporal modeling, generative adversarial networks, and human pose estimation. Her work bridges theory and application, addressing challenges in video analysis, emotion understanding, and biomedical signal processing. Research interests include advanced computer vision techniques, machine learning frameworks for temporal data, and AI-driven solutions for real-world problems. Recent work explores multiscale vision transformers for action localization and transfer learning in facial expression analysis. Teaching focuses on foundational AI concepts, preparing students to design intelligent agents and apply AI tools. No grants or awards are explicitly listed in the provided materials.

• Nephrology
• Transplantation Medicine
• Immunology
• +۳ مورد دیگر

Thin Thin Maw, MD, MS, FASN is a Clinical Associate Professor of Medicine (Clinician Educator) at the Keck School of Medicine of USC. They hold additional roles as Medical Director of Live Donor Kidney Transplant, Medical Director of Kidney and Pancreas Transplantation, and Program Director for Transplant Nephrology Fellowship. Their primary affiliation is with the Department of Medicine at the University of Southern California. Education and Training: Completed a Transplant Nephrology Fellowship at UCSF Medical Center (2014), Nephrology Fellowship at University of Pittsburgh Medical Center (2013), Internal Medicine Residency at University Hospital of Brooklyn (2011), and earned an M.S. in Medical Microbiology from Long Island University (2008). They also hold an M.B.B.S. in Medicine and Surgery from University of Medicine 1 in Yangon, Myanmar (2004). Research focuses on immune monitoring in kidney transplant recipients, post-transplant complications (e.g., hyperparathyroidism, skin cancer), and improving donor wellness programs. They served as a Co-Investigator in a UCSF study (2013-2014) exploring NFAT-dependent cytokine gene expression for immune monitoring. Awards include the 2009 Honorable Mention for Intern of the Year from University Hospital of Brooklyn and the 2007 Award of Excellence in Education from Myanmar American Medical Education Society. They have also received honors from Yangon University of Medicine in Medicine, Microbiology, Physiology, and Biochemistry. Publications span 20 years, emphasizing transplant immunology, dermatological complications in transplant recipients, and novel therapies for post-transplant infections. Their work addresses clinical challenges such as managing SARS-CoV-2 in transplant patients and optimizing immunosuppression regimens. Leadership roles include directing transplant programs and fostering clinician-educator excellence. They actively contribute to multidisciplinary teams addressing complex cases in kidney and pancreas transplantation.

Mark Lescroartمشاهده پروفایل

استادیار

• Neuroscience
• Cognitive Psychology
• Visual Perception
• +۳ مورد دیگر

Mark Lescroart is an Assistant Professor in the Department of Psychology at the University of Nevada, Reno, where he leads the Pieces of Mind Lab. He joined the Cognitive & Brain Sciences group in 2018 after completing a Ph.D. in Neuroscience at the University of Southern California (2011) under Irving Biederman and postdoctoral research with Jack Gallant at UC Berkeley. His research focuses on how the brain transforms visual stimuli into cognitive representations of objects, spatial relationships, and human actions. He teaches Measuring the Human Brain (PSY 413) . Education Ph.D. in Neuroscience, University of Southern California, 2011 B.S. in Psychobiology, University of Southern California, 2002 Research Interests Dr. Lescroart’s lab develops computational models of fMRI responses to decode brain activity during visual perception. Key areas include object identity/shape encoding, spatial structure interpretation, and action recognition. Techniques involve voxel-wise encoding models and decoding algorithms to predict neural responses to stimuli like movies and images. Awards & Grants Ruth L. Kirschstein National Research Service Award (2012–present) USC Travel Award (2010) Rockwell Dennis Hunt Scholastic Award (2006) Lab & Collaborations The Pieces of Mind Lab integrates neuroscience, computational modeling, and psychophysics to study high-level vision. Recent work includes the Visual Experience Dataset , a multimodal recording of naturalistic visual experiences.

Maliha Ashrafمشاهده پروفایل

پژوهشگر

• Human Visual Perception
• Color Science
• Image Processing
• +۴ مورد دیگر

Maliha Ashraf is a researcher at the University of Cambridge's Department of Computer Science and Technology, focusing on human visual perception, color science, and display technology. Her work bridges psychophysics and computational models to advance understanding of contrast sensitivity and perceptual quality metrics. She holds a PhD from the University of Liverpool (2024) and an Erasmus Mundus Master's in Color Science (2018). Current roles include Research Associate under Prof. Rafał Mantiuk and Postdoctoral research in visual modeling for graphics applications. Education: PhD, University of Liverpool (2024); MSc, Erasmus Mundus Color Science (2018); BEng, NED University (2016). Awards include the MDPI ECR Prize (2024), Best Paper Awards at CIC 2022/2020, and a Meta Travel Award (2022). Research Interests : Contrast sensitivity modeling, perceptual quality metrics, color calibration, crossmodal perception, and applications in AR/VR displays. Her work combines experimental studies with computational models to predict human visual performance across diverse conditions. Publications focus on contrast sensitivity functions (e.g., castleCSF), perceptual metrics (ColorVideoVDP), and display optimization. She co-authored over 30 peer-reviewed papers and contributed to datasets like XR-DAVID for AR/VR artifact evaluation. Awards and grants include travel support from Meta and the Erasmus Mundus Scholarship. Active in conference organizing (CIC, SAP) and teaching roles at the University of Liverpool.

David Jinkinsمشاهده پروفایل

دانشیار

• International Economics
• Household Finance
• Labor Economics
• +۲ مورد دیگر

David Jinkins is an Associate Professor in the Department of Economics at Copenhagen Business School. His research spans international economics, household finance, labor markets, and urban economics, with particular focus on migration, trade dynamics, and behavioral aspects of economic decision-making. Jinkins' work examines how individuals and firms navigate economic systems with imperfect information and institutional constraints. His publications investigate refugee placement effects on local economies, welfare program spillovers, search frictions in trade markets, and the dynamics of student debt crises. Methodologically, he combines structural modeling with empirical analysis of large-scale datasets. Recent research explores urban experience premiums for immigrants, path dependence in location choices, and wage inequality across city systems. His work on trade dynamics develops models of firm learning and export behavior under uncertainty. In household finance, he analyzes housing tenure decisions, job transitions, and policy interventions in credit markets. Jinkins maintains the 'An Occasion for Bloviation' Substack discussing economic philosophy and maintains open-source repositories for econometric analysis.

• Computer Science
• Electrical Engineering
• Machine Learning
• +۳ مورد دیگر

Xue Jiang is a faculty member at Shanghai Jiao Tong University's School of Electronic Information and Electrical Engineering, China. Their research focuses on interdisciplinary areas including machine learning, signal processing, biomedical engineering, and cybersecurity. With a prolific publication record, they specialize in neural networks, fault diagnosis systems, federated learning, and brain-computer interfaces. Key research interests include developing intelligent algorithms for fault detection in mechanical systems, advancing medical imaging techniques through deep learning, and enhancing privacy in distributed data frameworks. Their work spans applications in robotics, cybersecurity, and bioinformatics. Notable contributions include adversarial robustness studies for EEG-based systems and PML-based computational methods for wave propagation analysis. Publications highlight innovations across engineering and computer science, with a focus on practical implementations in real-world systems. Collaborations with institutions like the Hong Kong University of Science and Technology and Harbin Institute of Technology reflect their extensive academic network.

Joseph Eremondiمشاهده پروفایل

استادیار

• Dependent Types
• Programming Languages
• Formal Verification
• +۲ مورد دیگر

Joseph Eremondi is an Assistant Professor in the Department of Computer Science at the University of Regina, specializing in programming language theory and design. His research develops tools to enhance usability of dependently typed programming languages, which enable mathematical specification and verification of code behavior. Current projects include gradual dependent types, semantics for pattern matching, termination proof techniques, and compiler error diagnosis. Eremondi's publications advance formal foundations for programming language design while addressing practical usability concerns. Recent work establishes theoretical foundations for gradual dependent typing and develops ordinal notations for termination verification. He teaches courses in programming language concepts and formal verification, including courses on Agda-based program verification.

Keiichi Yoshimatsuمشاهده پروفایل

دانشیار

• Biochemistry
• Chemical Biology
• Biomaterials
• +۳ مورد دیگر

Keiichi Yoshimatsu is an Associate Professor at Missouri State University, affiliated with the Department of Chemistry and Biochemistry. His research spans biochemistry, chemical biology, and biomaterials, with a focus on synthetic polymer nanoparticles for biomedical applications. PhD, 2009, Lund University, Sweden BEng, 2004, Tokyo University of Agriculture and Technology, Japan Research Interests: Dr. Yoshimatsu specializes in developing synthetic polymers for drug delivery, sepsis therapy, and cancer treatment using infrared spectroscopy and machine learning. His work explores the intersection of biochemical systems, nanotechnology, and computational methods. Article Trends: His recent publications highlight advancements in using graph neural networks for spectral prediction, synthetic antibodies for ischemic injury, and polymer nanoparticles for targeted therapies. Earlier work delves into micelle dynamics, protein purification, and molecular imprinting techniques. Professional Experience: Following postdoctoral research at Japan's National Institute for Materials Science (2009–2010) and the University of California, Irvine (2010–2015), he has contributed to analytical chemistry laboratories and graduate programs at Missouri State University.

Hendrik Rochمشاهده پروفایل

پژوهشگر ارشد

• Phenomenology of heavy-ion collisions
• Nuclear Physics
• Particle Physics
• +۵ مورد دیگر

Dr. Hendrik Roch is a Research Fellow in the Department of Physics and Astronomy at Wayne State University's College of Liberal Arts and Sciences. His primary affiliation involves research in theoretical and computational nuclear physics, with office facilities provided in Room 314. No educational background or teaching roles are documented. Research Focus: Dr. Roch specializes in the phenomenology of heavy-ion collisions, employing advanced computational and statistical methods. Key areas include: Jet quenching dynamics and modification patterns in quark-gluon plasma Bayesian inference for nuclear matter properties and collision dynamics Relativistic kinematics frameworks like SPARKX software Hybrid hadronization models and multi-stage evolution systems Initial-state fluctuations and statistical analysis of hot-spot distributions Equation of state derivation using Gaussian-process generative models Publication Trends: The 15 most recent articles (2021-2025) demonstrate consistent focus on high-energy nuclear collision phenomena. Dominant themes include jet modification probes (photon-triggered jets, momentum broadening), Bayesian analysis of RHIC beam scan data, computational tool development (SPARKX, SMASH transport code), and hybrid hadronization models. Methodological emphasis is placed on statistical inference, multi-stage frameworks, and precision kinematics conservation. Awards & Recognition: No scientific awards, prizes, or fellowships are documented in the available information. Research Infrastructure: No dedicated laboratories, research groups, or external collaborations are explicitly mentioned beyond institutional affiliation. Software contributions include SPARKX kinematics analyzer and SMASH transport code updates.

Troy Messickمشاهده پروفایل

استادیار

• Syntax
• Morphology
• Linguistic Agreement
• +۲ مورد دیگر

Troy Messick serves as Assistant Professor and Undergraduate Program Director in the Department of Linguistics within Rutgers University's School of Arts and Sciences. His primary academic appointment focuses on theoretical syntax and morphological phenomena. Research interests center on syntactic theory with specialized expertise in syntax , morphology , pronouns , agreement phenomena , and ellipsis . His work demonstrates particular depth in Dravidian languages (especially Telugu), exploring case-copying reflexives, shifty agreement patterns, and cross-clausal dependencies. Recent publications reveal a trajectory examining morphosyntactic interfaces through both theoretical and experimental approaches. Analysis of his 15 most recent publications (2012-2025) shows consistent focus on agreement anomalies, ellipsis mechanisms, and syntactic locality. Key trends include: investigation of hybrid noun phenomena in English and Telugu, experimental validation of gender asymmetries in ellipsis, and theoretical reevaluations of E-raising and case-matching reciprocals. His work bridges formal theory with cross-linguistic data, particularly from South Asian languages. No scientific awards or fellowships are documented in available sources. As Undergraduate Program Director, Messick oversees linguistics curriculum and student advising. Office hours are held Thursdays 9:00-11:00am (in-person) and 2:00-4:00pm (via Zoom), with primary contact through departmental email channels. No specific research grants or laboratory affiliations are mentioned in current materials.

Gualberto Asencio Cortésمشاهده پروفایل

دانشیار

• Machine Learning
• Time Series Forecasting
• Data Mining
• +۲ مورد دیگر

Gualberto Asencio Cortés is Associate Professor in Computer Science at Universidad Pablo de Olavide. He holds Ph.D. in Computer Science from UPO (2013) and Executive Master in Innovation from EOI (2016). Research focuses on developing advanced algorithms for: Time series forecasting in energy, agriculture, and environmental domains Feature selection methods for deep learning Explainable AI for predictive modeling Big data stream processing Developed innovative tools like FS-Studio for feature selection experimentation. Recent publications demonstrate strong focus on agricultural applications (pest forecasting, phenology prediction) and energy consumption modeling using hybrid deep learning approaches.