جست‌وجوی استاد و پژوهشگر

Mark C. Kruseمشاهده پروفایل

استاد

• High-Energy Particle Physics
• Large Hadron Collider (LHC) experiments
• Higgs boson physics
• +۵ مورد دیگر

Mark C. Kruse is a Professor in the Department of Physics at Duke University, within Trinity College of Arts & Sciences. His research focuses on High-Energy Particle Physics, particularly the analysis of data collected by the ATLAS detector at the Large Hadron Collider (LHC). With the Higgs boson discovered by ATLAS and CMS collaborations in July 2012, his work now centers on discovering models beyond the Standard Model of particle physics. Dr. Kruse's educational background includes: Ph.D. in Physics from Purdue University (1996) M.S. in Physics from University of Auckland, New Zealand (1988) B.S. in Physics from University of Auckland, New Zealand (1986) Professor Kruse's research primarily investigates phenomena beyond the Standard Model of particle physics. His work with the ATLAS detector at the LHC focuses on Higgs boson properties, top quark physics, and searches for new particles and forces that could explain dark matter and other cosmic mysteries. He has been instrumental in analyzing data from proton-proton collisions at various energy levels to uncover potential deviations from established physics theories. His research group at Duke actively contributes to the international effort to understand fundamental particles and their interactions at the highest energy scales accessible to humanity. Analysis of Professor Kruse's recent publications reveals a strong focus on Higgs boson physics, top quark measurements, and searches for physics beyond the Standard Model. His work with the ATLAS collaboration spans multiple areas including precision measurements of known particles, searches for exotic decays, and investigations of quark-gluon plasma. The research demonstrates increasing sophistication in data analysis techniques as the LHC continues to deliver higher luminosity and energy collision data. Professor Kruse has received several notable awards and recognitions: Dean's Leadership Award from Duke University (April 2013) Sir Thomas Lyle Fellowship from University of Melbourne, Australia (2013) Bass Society of Fellows at Duke University (May 2012) Shared recognition for the Discovery of the Top Quark (July 2019) As a dedicated educator and mentor, Professor Kruse has advised numerous students through independent study courses (PHYSICS 493) and thesis projects (PHYSICS 495). He has secured substantial research funding including the REU Site for Undergraduate Research in Nuclear Particle Physics (2022-2027) and the Support and Maintenance for the ATLAS Transition Radiation Detector at CERN (2025-2027). His grants consistently support both graduate and undergraduate research opportunities, reflecting his commitment to training the next generation of physicists. Professor Kruse is a key member of the ATLAS collaboration at CERN, where he serves as the US ATLAS Transition Radiation Tracker Level 3 Manager. His research group at Duke University works closely with international collaborators on data analysis and detector operations. The team contributes significantly to the ongoing physics program at the LHC, particularly in areas related to Higgs boson characterization and searches for new physics phenomena.

Bo Liمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Computer Vision
• Computer Graphics
• +۲ مورد دیگر

Dr. Bo Li serves as an Associate Professor at the University of Southern Mississippi, where he teaches core computer science courses including Artificial Intelligence, Computer Graphics, and Database Management Systems. His academic foundation spans institutions across three countries, reflecting a globally oriented research perspective in visual computing and machine learning. His educational background includes: PhD in Computer Science from Nanyang Technological University (2012) MS in Computer Science from Texas State University (2015) MS in Computer Science from Xi'an Jiaotong University (2005) BS in Computer Science from Xi'an Jiaotong University (2005) Dr. Li's research centers on 3D shape retrieval systems, where he pioneers methods for sketch-based and image-based 3D model search. His work bridges computer vision, graphics, and machine learning through innovative approaches to 3D scene analysis, semantic modeling, and cross-modal translation. Recent investigations extend into social media analysis and speech emotion recognition, demonstrating methodological versatility within artificial intelligence. Analysis of his 15 most recent publications reveals a sustained focus on 3D shape retrieval benchmarking through SHREC competitions, evolving from traditional descriptor methods to deep learning frameworks. Key trends include multimodal query processing, large-scale dataset handling, and applications in real-world image denoising. His research consistently addresses challenges in partial/non-rigid model matching and semantic scene understanding. Dr. Li has not been documented with scientific awards in the provided information. Regarding academic mentorship and funding, no details about student supervision, research grants, or sponsored projects are available in the source material. Similarly, information about laboratory facilities, research teams, or collaborative groups is not provided in the current documentation.

Ying Fanمشاهده پروفایل

استادیار

• Industrial Organization
• Applied Microeconomics
• Market Structure
• +۲ مورد دیگر

Ying Fan is an Assistant Professor of Economics at the University of Michigan , where she is affiliated with the Department of Economics . She is also associated with the National Bureau of Economic Research (NBER) and the Centre for Economic Policy Research (CEPR) . Her research focuses on Industrial Organization , applied microeconomics, and market structure. She examines how financial constraints , subsidies , and regulatory policies influence firm behavior and consumer welfare. Her work spans industries such as smartphones, e-commerce platforms, automotive, and telecommunications. Her recent publications and working papers highlight trends in market competition , reputation management , subsidy effects , and spillover dynamics . Collaborative studies with institutions like Shanghai University of Finance and Economics and Stony Brook University emphasize cross-market analysis and policy implications. She has not explicitly mentioned scientific awards, student advising, or lab/team affiliations in the provided text.

• Speech Recognition
• Speaker Verification
• Language Identification
• +۷ مورد دیگر

Professor Jan Černocký serves as Head of Department at the Department of Computer Graphics and Multimedia (DCGM) within the Faculty of Information Technology at Brno University of Technology (FIT VUT). With a professional email cernocky@fit.vut.cz and office L221.2, he maintains an active research profile with numerous publications spanning over 20 years in the field of speech processing and recognition. His work is well-documented through multiple research identifiers including ORCID iD 0000-0002-8800-0210, Scopus Author ID 6604040821, and Researcher ID M-7494-2019. Professor Černocký's research interests focus primarily on advanced speech processing technologies, with particular emphasis on speech recognition, speaker verification, language identification, and multimodal systems. His work demonstrates a strong trajectory from traditional speech processing techniques toward modern deep learning approaches, especially in self-supervised learning for speech applications. Recent publications show his leadership in developing benchmarks like TS-SUPERB for target speech processing and innovative methods for speaker verification using transformer models. His research group at BUT has made significant contributions to multi-channel speech processing, target speech extraction, and speaker diarization systems. The analysis of Professor Černocký's recent publications (2023-2025) reveals several key trends in his research direction. There's a clear shift toward self-supervised learning approaches for speech processing, with numerous papers exploring how pre-trained models can be adapted for speaker verification, target speech extraction, and multi-channel processing. His work increasingly incorporates transformer architectures and attention mechanisms, reflecting the broader trends in speech processing research. The 2024 publications particularly highlight work on multimodal analysis (BESST dataset for stress detection) and practical applications of speech technology for social inclusion. Throughout his career, Professor Černocký has maintained strong collaborative relationships with researchers across Europe and internationally, evidenced by his extensive publication record with co-authors from multiple institutions. His leadership role as Head of Department at DCGM places him at the center of speech processing research at Brno University of Technology, where his team continues to produce cutting-edge research in speech technology.

• Labour Market
• Economic Inequality
• Technological Change
• +۶ مورد دیگر

Dr. Emilie Rademakers serves as an Assistant Professor in the Department of Economics at Utrecht University's School of Economics within the Faculty of Law, Economics and Governance. Her research critically examines labor market transformations driven by technological advancements, with particular focus on economic inequality and structural shifts in employment systems. Her expertise spans labour market dynamics, economic inequality, technological change, and online search competition. She investigates how automation and robotization reshape job polarization through task overlap mechanisms, analyzing both historical patterns and future trajectories of work. Her IOS - Future of Work research within Utrecht's Institutions for Open Societies initiative connects theoretical models with empirical evidence on technological displacement and skill redistribution. Analysis of her 2019-2024 publications reveals consistent exploration of automation's labor market impacts, emphasizing resilience mechanisms through task similarity and structural transformation rather than simple job elimination. These works demonstrate methodological diversity across plant closure studies, job polarization frameworks, and macroeconomic analyses of technological diffusion. Scientific Awards: LEG Visiting Fellowship (2021) Dr. Rademakers has secured competitive funding including an H2020 Grant for studying technology's impact on labor market skills, and has supervised graduate research as evidenced by her 'Supervised Work' profile entry. Her grant activities focus on technological transformation in labor markets with policy-relevant implications. She actively contributes to Utrecht University's Institutions for Open Societies (IOS) initiative as a core member of the Future of Work research theme, collaborating on interdisciplinary projects examining robotization's societal impacts and participating in the UUSE Multidisciplinary Economics network.

Arnab Nandiمشاهده پروفایل

استاد

• Database Systems
• Human-in-the-Loop Data Analytics
• Next-Generation Query Interfaces
• +۱۰ مورد دیگر

Arnab Nandi is a Professor in the Department of Computer Science & Engineering at The Ohio State University. His work bridges human interaction with data infrastructure, focusing on database systems, LLM-augmented analytics, and immersive query interfaces. Education: PhD in Computer Science & Engineering from the University of Michigan Leadership: Co-founder of OHI/O Hackathon Program and STEAM Factory interdisciplinary network Research spans human-in-the-loop data analytics , vibe querying (natural language + gestural interfaces), LLM integration into education, and climate response systems . Key projects include Omni (multimodal exploration), GestureDB , and Icarus (clinical pipelines). Recent publications analyze LLM-driven query stacks (HILDA 2025), video analytics (SIGMOD 2022), and data sunglasses for cognitive limits (HILDA 2025). Awards include NSF CAREER Google Faculty Research Award IEEE TCDE Early Career Award ACM Distinguished Member Advises students in database innovation , with alumni at Amazon, AWS, Roblox, and Meta. Teaches CSE 3241 (Database Systems), CSE 5889 (Software Startups), and CSE 5242 (Advanced Databases).

• Organizational Behavior
• Innovation Management
• Strategic Management
• +۵ مورد دیگر

Prof. Dr. Torsten-Oliver Salge is a University Professor and Co-Director of the Institute for Technology and Innovation Management (TIM) at RWTH Aachen University, where he heads the Innovation, Strategy and Organisation (ISO) Group since April 2013. He also serves as a Fellow of Cambridge Digital Innovation at the University of Cambridge, maintaining strong international academic connections. His work bridges theoretical organizational research with practical applications across multiple sectors. Salge completed his business administration studies across multiple European countries including Germany, France, Italy, and England. He earned both his Ph.D. and M.Phil. degrees from the University of Cambridge. His academic journey includes positions as interim professor at the University of Duisburg-Essen (2012-2013), junior professor at the Ruhr-University Bochum (2009-2012), and post-doctoral research associate at Cambridge (2009). His research focuses on organizational behavior in innovation contexts , particularly examining collaboration across disciplinary, organizational, and institutional boundaries. He investigates how organizations learn from performance feedback, approach problem-solving, and implement strategic HRM practices that enhance employee well-being. A distinctive feature of his work is the examination of technology legitimation, adoption processes, and payoff realization in complex organizational settings. His research combines behavioral and institutional perspectives to understand innovation processes. Analysis of Salge's publication record reveals a strong emphasis on healthcare innovation management, with numerous studies examining hospital information systems, infection control, and healthcare service improvement. His work often applies dynamic capabilities theory to innovation processes and demonstrates methodological sophistication through both quantitative and qualitative approaches. The publications show consistent contributions to top-tier management journals including Academy of Management Review , MIS Quarterly , and Journal of Product Innovation Management . Scientific Recognition: Nominated for European Research Paper of the Year 2016 (CIONET) Multiple Best Paper awards at Academy of Management conferences across various divisions Shortlisted for Strategic Management Society (SMS) Best Conference Paper Awards Recipient of prestigious scholarships including ESRC, DAAD, and Cambridge European Trust funding Recognized with the Knut Holt Best Paper Award from ISPIM Throughout his career, Salge has maintained active collaborations with organizations across healthcare, central government, and financial services sectors. His international scholarly network is evidenced by visiting appointments at universities in Auckland, Buenos Aires, Cambridge, Oxford, and Philadelphia. At RWTH Aachen, he leads an interdisciplinary team within the TIME Research Area, which comprises over 100 senior and junior researchers working at the intersection of innovation, technology management, marketing, and entrepreneurship. As Co-Director of the RWTH TIM institute, Salge oversees a research unit with approximately 30 doctoral candidates, 5 postdocs, and more than 20 student researchers. The institute maintains strong industry connections and focuses on strategic technology management, open innovation, innovation culture, organizational change, business model development, and customer-oriented value creation.

Christopher Heartyمشاهده پروفایل

استاد

• Experimental Particle Physics
• Physics beyond the Standard Model
• Dark sector
• +۵ مورد دیگر

Christopher Hearty is a Professor in the Department of Physics & Astronomy at the University of British Columbia (UBC), Faculty of Science, and serves as an IPP (Institute of Particle Physics) Principal Research Scientist. His office is located in Hennings 268 with laboratory space at TRIUMF/Hennings 222, where he conducts cutting-edge experimental particle physics research using major international facilities. Hearty earned his B.Sc. in Mathematics and Physics from Simon Fraser University (1982), followed by a Ph.D. in Physics from the University of Washington (1987). He completed postdoctoral research at Lawrence Berkeley National Laboratory from 1987 to 1994 before joining UBC. B.Sc., Mathematics and Physics, Simon Fraser University, 1982 Ph.D., Physics, University of Washington, 1987 Postdoctoral Researcher, Lawrence Berkeley National Laboratory, 1987-1994 His research program focuses on direct searches for physics beyond the Standard Model through e+e- collisions, with particular emphasis on dark sector phenomena including dark photons, axion-like particles, and strongly interacting dark matter. As a key contributor to the Belle II experiment, he develops advanced calorimeter calibration techniques, reconstruction algorithms, and trigger systems while mentoring students in machine learning applications for large-scale data analysis. His work bridges theoretical phenomenology with experimental verification in the search for new fundamental particles. Recent publications demonstrate a concentrated effort on dark sector exploration at Belle II, featuring innovative approaches like graph neural networks for photon reconstruction and sophisticated analysis of displaced vertices. The research spans both visible and invisible decay channels, significantly advancing constraints on dark matter models while establishing Belle II's sensitivity to elusive particles through precision measurements of e+e- collision data. Hearty's scientific recognition includes: APS Fellow (2015) Breakthrough Prize in Fundamental Physics (2016) as part of the T2K collaboration He actively supervises graduate students on thesis projects spanning dark photon searches, axion-like particle detection, and detector development, while serving on UBC's teaching peer review committee and as LHCb chief reviewer for CERN's LHCC committee. His mentorship provides students with hands-on experience in international collaborations, detector instrumentation, and advanced data analysis techniques. Based at TRIUMF Canada's particle accelerator centre and UBC's Department of Physics & Astronomy, Hearty leads a research group within the global Belle II collaboration. His team contributes to multiple detector subsystems including calorimetry and tracking systems, while developing novel analysis frameworks for new physics signatures in high-energy collision data.

Shabnam Sadeghi Esfahlaniمشاهده پروفایل

دانشیار

• Robotics
• Mechatronics
• Artificial Intelligence
• +۳ مورد دیگر

Dr. Shabnam Sadeghi Esfahlani is an Associate Professor in Robotics at the School of Engineering and the Built Environment, Anglia Ruskin University , where she serves as Deputy Leader of the BORI research group and leads the Automation & Robotics MSc program. Her interdisciplinary expertise spans mechatronics, artificial intelligence, virtual reality, and serious games , with a focus on applications for rehabilitation, medical training, and autonomous systems . As a Chartered Engineer and Senior Fellow of the Higher Education Academy , she has secured significant funding from Innovate UK, Horizon 2020, and GCRF , with grants exceeding £3 million. Education PhD in Mechanical Engineering, Anglia Ruskin University BSc (First Class) in Statistics & Mathematical Science, Shahid Beheshty University Her research integrates AI with robotics for societal impact, exemplified by the open-source SROBO ground robot and projects like Rehabgame and the Assistive Feeding Robot . She has published over 45 peer-reviewed articles and contributes to academic communities as a journal guest editor and conference organizer . Key collaborations include IET, IMechE, and the Nuffield Foundation as a mentor for young students. Scientific Awards & Recognitions: Chartered Engineer (CEng), Engineering Council UK Senior Fellow (SFHEA), Higher Education Academy Student-Voted 'Made a Difference Award' (2018) Post-Graduate Certificate in Higher Education

Kalina Bontchevaمشاهده پروفایل

پژوهشگر

• NLP for social media
• semantic search
• GATE infrastructure
• +۸ مورد دیگر

Kalina Bontcheva is a Senior Researcher in the Natural Language Processing Group within the Department of Computer Science at the University of Sheffield. She holds an EPSRC Career Acceleration Fellowship (working part-time since October 2015) focused on personalized summarization of social media content. Her research spans multiple EU-funded projects including PHEME (computing veracity of social media), TrendMiner, DecarboNet, and uComp, with significant contributions to the GATE (General Architecture for Text Engineering) open-source NLP infrastructure since 1999. Dr. Bontcheva's research interests focus on the intersection of natural language processing and social media analysis. Her work encompasses NLP for social media, semantic search, information extraction from social platforms, crowdsourcing of NLP corpora, collaborative text annotation, semantic technologies, and text mining and analytics. She has particular expertise in developing methods for personalized, abstractive multi-document summarization across different social media platforms, addressing the challenges of noisy, jargon-filled and dynamic content. Her interdisciplinary approach combines machine learning, semantic technologies, and social dimension analysis to create systems that adapt to individual users' information seeking goals. Analysis of her recent publications reveals a strong focus on social media processing challenges, with emphasis on Twitter analysis, temporal expression recognition, and handling noisy text. Her work consistently addresses the unique characteristics of social media content and develops specialized techniques for information extraction, sentiment analysis, and user geolocation within these platforms. The GATE framework serves as the foundation for much of her tool development, demonstrating her commitment to creating reusable, open-source NLP infrastructure. Her most significant award is the EPSRC Career Acceleration Fellowship, which supports her work on personalized social media summarization. This prestigious fellowship includes a substantial budget of £560k and involves collaborations with industry partners including The Press Association, British Telecom, and Fizzback. Dr. Bontcheva has led numerous major research projects throughout her career. She was Principal Investigator on three EU-funded projects (MUSING, TAO, and ServiceFinder) between 2006-2009, coordinating the TAO consortium with seven partner institutions. She currently leads the PHEME EU project and serves as PI for TrendMiner and DecarboNet European projects, while also contributing as Co-I on the uComp project. Her project portfolio demonstrates consistent success in securing competitive research funding across multiple domains within NLP and semantic technologies. She works within the Natural Language Processing Group at the University of Sheffield, which has been central to the development of the GATE infrastructure. Her work connects with various initiatives including the GATE Cloud platform and the TextVRE project for e-humanities textual studies. She has established collaborations with organizations including the Press Association, British Telecom, Oxford Internet Institute, and Sheffield's Department of Journalism to ensure her research addresses real-world needs across different user communities.

Dimitris Papanikolaouمشاهده پروفایل

استاد

• Asset Pricing
• Macroeconomics
• Innovation
• +۲ مورد دیگر

Dimitris Papanikolaou serves as the John L. & Helen Kellogg Professor of Finance at Northwestern University's Kellogg School of Management and is a Research Associate of the National Bureau of Economic Research (NBER). His research critically examines the nexus between technological innovation and financial markets, with recent contributions spanning intangible capital measurement, innovation's impact on labor dynamics, executive markets, and financial frictions. Education: PhD in Financial Economics, Massachusetts Institute of Technology (2007) MS in Finance and Economics, London School of Economics (2001) BA in Economics and Finance, University of Piraeus (2000) Papanikolaou's research program centers on Asset Pricing , Macroeconomics , Innovation , Economic Growth , and Intangible Capital . He pioneers methodologies for quantifying innovation through textual analysis of patents while investigating how technological advances reshape financial markets and labor outcomes. His work reveals critical insights into human capital displacement, the economic value of intangibles, and the causal mechanisms linking financial constraints to innovation efficiency, employing rigorous empirical designs including natural experiments and administrative datasets. Analysis of his recent publications shows a pronounced interdisciplinary trajectory, merging finance, labor economics, and innovation studies through cutting-edge techniques like NLP and big data analytics. Key thematic clusters include AI's labor market effects (examining task exposure and wage dynamics), creative destruction measurement (using text-based innovation displacement metrics), and intangible capital's macroeconomic role (exploring firm scope, concentration, and growth implications). These works consistently establish causal relationships through exogenous variation in innovation shocks and patent data. Scientific recognition includes: Kellogg Research Mentorship Award Best Paper Award, London Business School Finance Symposium (2018) Best Paper Award, Red Rock Finance Conference (2017) Crowell Memorial Prize (second place), Panagora Asset Management Amundi Smith Breeden Prize, American Finance Association (2014 and 2013) Roger F. Murray Prize (second place), The Q Group (2011) As Co-Editor of the Journal of Financial Economics and former editorial board member for Management Science, the Journal of Finance, and the Review of Financial Studies, Papanikolaou shapes scholarly discourse in finance. His mentorship excellence—recognized by the Kellogg Research Mentorship Award—demonstrates commitment to developing next-generation scholars, though specific grant details remain undisclosed in available materials. Collaborative research networks with leading economists like Kogan, Schmidt, and Eisfeldt drive his high-impact publications. Papanikolaou's research ecosystem involves extensive collaboration with interdisciplinary teams leveraging computational methods for innovation measurement. Current projects focus on AI-labor market interactions and intangible capital dynamics, often utilizing proprietary patent datasets and administrative worker records to generate policy-relevant insights about technological disruption and market efficiency.

• Human-Machine Interaction
• Usability Testing
• User Experience (UX)
• +۵ مورد دیگر

Jürgen Sauer is a Full Professor at the University of Fribourg , affiliated with the Department of Psychology under the Faculty of Letters and Human Sciences . With over 120 publications, his research focuses on Human-Machine Interaction , Usability Testing , User Experience (UX) , and Automation Design , particularly in high-stakes environments like X-ray baggage screening and spaceflight simulations . Email: juergen.sauer@unifr.ch Phone: +41 26 300 7622 Address: RM 01 bu. C-1.117, Rue PA de Faucigny 2, 1700 Fribourg Orcid: 0000-0003-2105-1694 His research projects, funded by the Swiss National Science Foundation (FNS), include: Improving work design for airport security officers (2019-2024): Developed pictorial scales for measuring psychological constructs in security environments. Social stress and support in hybrid teams (2018-2023): Investigated machine-induced social stressors and mitigation through social support. Automation in visual inspection tasks (2014-2018): Examined adaptable automation for baggage screening and system reliability effects. Usability testing effectiveness (2012-2016): Analyzed cultural background impacts and non-usability product features influencing test outcomes. Key contributions include the Luggage Inspection Simulation (LIS) environment for modeling work environments and the development of pictorial usability scales for multilingual applicability. His work bridges ergonomics , human factors , and applied psychology , with notable collaborations with researchers like Adrian Schwaninger and Andreas Sonderegger . His recent publications (2025-2014) analyze: Human-machine performance under false alarms and miscues Social stressor dynamics in hybrid teams Usability scale animation effects Phubbing behavior in professional contexts Accessible website design for non-disabled users

• Disaster Management
• Risk Resilience
• Water Rescue Operations
• +۳ مورد دیگر

Naomi Morris serves as a Teaching Fellow at the University of Portsmouth within the Faculty of Science & Health, specifically affiliated with the School of the Environment and Life Sciences and the Centre of Excellence in Defence, Risk & Resilience. She actively contributes to academic research in disaster management while accepting PhD students for supervision. Her research focuses on critical areas including disaster management, risk resilience, water rescue operations, and pandemic response strategies. These interests align with multiple United Nations Sustainable Development Goals, particularly those addressing disaster risk reduction and community resilience. Her work bridges theoretical frameworks with practical emergency response applications across diverse contexts. Morris has contributed to significant research projects including the GCRF-funded study on 'Impact of Covid19 in developing countries' and the examination of UK Search and Rescue frameworks titled 'For those in peril on the sea.' Her collaborative approach is evident through numerous co-authored publications spanning emergency medicine, geography, and public policy domains. Her research demonstrates an evolving trajectory from technical geospatial applications toward more community-centered emergency response frameworks, with particular emphasis on water rescue operations and pandemic prevention. This progression reflects growing focus on practical, community-based solutions to complex disaster scenarios. Morris actively collaborates across disciplines as a Co-Investigator on major projects. Her work has attracted substantial attention with significant readership on academic platforms like Mendeley, indicating relevance and impact within her research communities.

Christian Weinheimerمشاهده پروفایل

استاد

• Neutrino Physics
• Dark Matter Research
• Astroparticle Physics
• +۵ مورد دیگر

Professor Christian Weinheimer is a leading experimental physicist at the University of Münster's Institute of Nuclear Physics, where he holds a full professorship and serves as the Managing Director of the Institute. His research focuses on fundamental questions in particle and astroparticle physics, particularly neutrino mass measurements and the search for dark matter. He plays key roles in major international collaborations including KATRIN (neutrino mass experiment at Karlsruhe Institute of Technology) and XENONnT (dark matter search experiment at the Italian LNGS underground laboratory). Weinheimer's research interests span neutrino physics , dark matter detection , precision measurement techniques , and detector development . His group develops cutting-edge technologies for the KATRIN experiment's precision high-voltage system and electrode components, while also pioneering cryogenic distillation techniques for the XENON experiments to remove radioactive contaminants. His work extends to medical applications through the BOLD-PET project, developing novel detectors using trimethylbismuth for positron emission tomography. Analysis of his recent publications reveals a strong focus on pushing the boundaries of neutrino mass measurements, developing next-generation dark matter detectors capable of reaching the 'neutrino fog' sensitivity limit, and exploring innovative detector technologies. His work consistently combines theoretical insight with experimental ingenuity to address fundamental questions about the universe's composition and fundamental particles. Scientific awards: ERC Advanced Grant (2022) Helmholtz-Preis (2001) Dissertationspreis from Vereinigung der Freunde der Universität Mainz (1993) CERN Fellowship (1995-1996) Weinheimer actively mentors PhD students working on KATRIN background reduction, dark matter searches with XENON, precision energy measurements, and novel PET detector development. His research is supported by major grants including the ERC Advanced Grant LowRad project (2022-2027), multiple DFG-funded Collaborative Research Centers, and international collaborations with CERN, DESY, and research institutions worldwide. He also leads the development of technologies for the future DARWIN/XLZD observatory, which aims to be the most sensitive dark matter detector ever built. His laboratory operates specialized facilities including a large xenon purification system, detector development labs for the BOLD-PET project, and precision measurement equipment for high-voltage and low-background applications. Weinheimer's group collaborates extensively with other research teams at Münster University, particularly with the Cells in Motion initiative and the European Institute for Molecular Imaging.

Jared R. Bagleyمشاهده پروفایل

استادیار

• Behavioral Pharmacology
• Addiction Neurogenetics
• Genomics
• +۳ مورد دیگر

Jared R. Bagley is an Assistant Professor in the Department of Pharmaceutical Sciences at the School of Pharmacy and Pharmaceutical Sciences, Binghamton University, where he joined in 2024. His research focuses on the genetics and neurobiology of substance use disorders through integrated behavioral, neuroscience, genetic, and genomic approaches. His educational background includes the following degrees: Postdoctoral Fellowship at Binghamton University PhD in Neuroscience and Behavior from the University of California, Santa Barbara BA in Psychology from the University of California, Davis Bagley's research spans behavioral pharmacology, addiction neurogenetics, and genomics/transcriptomics. He employs behavioral pharmacology, advanced mouse genetics (Hybrid Mouse Diversity Panel, Collaborative Cross, Diversity Outbred), pharmacogenomics, and physiological neuroscience techniques to identify genetic factors driving addictive behaviors and their neural impacts, with specific focus on cocaine self-administration and nucleus accumbens dopamine transmission. His recent publications (2021-2025) reveal consistent emphasis on genetic architecture of substance use disorders using diverse mouse populations to study cocaine/alcohol addiction. Research integrates behavioral phenotyping with genetic mapping, highlighting polygenic influences and candidate genes (e.g., Neuron Navigator 1) in drug response, reward processing, and cognitive flexibility related to addiction vulnerability. His scientific awards include: NIH K99/R00 Pathway to Independence Career Development Award Carlisle Award, University of California, Santa Barbara (2016) Leading the Search, The Jackson Laboratory (2011) Bagley maintains extensive teaching and mentorship commitments with holistic student development philosophy emphasizing learning, curiosity, creativity, inclusion, and respect. His current NIH-NIDA K99/R00-funded research investigates how polygenic factors and candidate genes affecting cocaine self-administration alter dopamine transmission in the nucleus accumbens. The Bagley lab operates cutting-edge methodologies including fiber photometry, optogenetic fast-scan cyclic voltammetry, and advanced genetic mouse models to dissect neural mechanisms of addiction at molecular, cellular, and circuit levels.