جستجوی استاد راهنمای دانشگاهی

Richard Traunmüllerمشاهده پروفایل

استاد

• Political Science
• Empirical Democracy Research
• Social Cohesion
• +۶ مورد دیگر

Prof. Dr. Richard Traunmüller is a Professor of Political Science and Empirical Democracy Research at the University of Mannheim. He serves as Scientific Director of the German Internet Panel (GIP) and is affiliated with the Research Institute Social Cohesion (RISC) at Goethe University Frankfurt. His research spans multidimensional social change, immigration policy, wartime sexual violence, and quantitative methodology. School of Social Sciences, University of Mannheim Goethe University Frankfurt University of Essex University of Bern University of Konstanz His research focuses on: Democratic challenges from social structural reconfiguration Religious diversity and social cohesion Free speech regulation in digital democracies Long-term effects of wartime sexual violence Recent work analyzes: Causal impacts of immigration policies Contextual speech norms Gendered consequences of conflict trauma Bayesian approaches to sensitive topics Scientific awards include: BEST PAPER AWARD (CES Immigration Research Network, 2017) BEST ARTICLE AWARD (APSA Migration & Citizenship, 2017) He teaches courses on: Bayesian Statistics Data Visualization Free Speech & Censorship Political Methodology Conflict Studies

Lorenzo Farinaمشاهده پروفایل

استاد

• Network Medicine
• Bioinformatics
• Systems Biology
• +۶ مورد دیگر

Lorenzo Farina is a Full Professor at Sapienza University of Rome's Faculty of Information Engineering, Computer Science and Statistics, specializing in Electronic and Computer Bioengineering (ING-INF/06). With over 25 years of academic leadership, he co-founded Italy's first Bioinformatics degree program and established key oncology precision medicine initiatives, maintaining active collaborations with Harvard Medical School's network medicine division. His educational background includes a cum laude Electronic Engineering degree and PhD in Systems Engineering, both from Sapienza University. These foundational studies evolved into pioneering work in positive linear systems theory, evidenced by his highly-cited Wiley textbook Positive Linear Systems: Theory and Applications (2000). Farina's research centers on network medicine – applying complex network science to molecular medicine since his 2004 breakthrough. His work spans cancer mechanisms (breast, glioblastoma, lung), drug repositioning (including COVID-19 applications), and liquid biopsy biomarker development. Current projects focus on miRNA-based network biomarkers for cancer diagnostics and immunotherapy response prediction, integrating multi-omics data through advanced computational frameworks. Analysis of his 15 most recent publications (2024-2025) reveals dominant themes: sexual dimorphism in cancer networks (MIRROR platform), immunotherapy response signatures, and critical examinations of AI's role in precision medicine. His work consistently bridges computational innovation with clinical applications, particularly in oncology diagnostics and therapeutic optimization. His scientific recognition includes: 2001 Guillemin-Cauer Award for best IEEE Transactions on Circuits and Systems article 2014 SysBio Award for annual best publication Farina actively mentors through interdisciplinary programs he established, including the Network Oncology doctoral program. His laboratory collaborations span Sapienza's Oncogenomics and Immunology Laboratories, Harvard's Channing Division of Network Medicine, and clinical departments in oncology and radiology, driving translational research from computational models to patient applications. He leads multiple research teams focused on network-based diagnostics, including the MIRROR platform for cancer disparity analysis and liquid biopsy development teams investigating circulating miRNA networks for early cancer detection across multiple malignancies.

Ben Jannمشاهده پروفایل

استاد

• Statistical Methods
• Data Visualization
• Social Inequality
• +۲ مورد دیگر

Ben Jann is a Professor and current Department Head at the University of Bern in the Department of Social Sciences . His methodological expertise spans statistical software development, decomposition analysis, and data visualization. Role: Department Head Institution: University of Bern Department: Department of Social Sciences Research Interests : Jann specializes in creating Stata modules for advanced statistical analysis, including geospatial mapping (geoplot), robust regression (robreg10), and inequality decomposition (oaxaca-blinder methods). His substantive work examines social inequality through economic and sociological lenses, analyzing how living costs and taxation systems impact income distribution in Switzerland. He also investigates educational transitions and gender disparities in STEM occupational choices through longitudinal studies like TREE2. Recent Publications Trends : Jann’s 15 most recent articles (2025-2023) demonstrate his focus on statistical software development for social science applications. Key contributions include methods for marginal odds ratios (2023), two-level model variance decomposition (2025), and list experiment analysis (2025). His empirical work connects statistical methodology to pressing social issues like gender wage gaps (2021) and teacher content knowledge in developing countries (2021).

Paul W Burridgeمشاهده پروفایل

دانشیار

• Pharmacogenomics
• Cardio-Oncology
• Induced Pluripotent Stem Cell Modeling
• +۵ مورد دیگر

Paul W Burridge, PhD is an Associate Professor in the Department of Pharmacology at Northwestern University's Feinberg School of Medicine and a founding faculty member of the Center for Pharmacogenomics. His laboratory specializes in human induced pluripotent stem cell (hiPSC) modeling for pharmacogenomics and cardio-oncology research. Dr. Burridge's research focuses on understanding how genomic variation influences drug efficacy and toxicity, particularly in cancer therapy-induced cardiovascular complications. His lab pioneered several key methodologies including the first directed cardiac differentiation protocol, non-integrating blood-to-iPSC reprogramming, and chemically defined differentiation protocols. Current projects span cardio-oncology, arrhythmia mechanisms, regenerative medicine, hiPSC models of breast cancer, and cultivated meat applications. Analysis of his 15 most recent publications reveals a strong emphasis on pharmacogenomics of anthracycline cardiotoxicity, with significant focus on genomic risk prediction in childhood cancer survivors, molecular mechanisms of cardiotoxicity, and development of cardioprotective strategies. His work increasingly integrates large-scale genomic analysis with hiPSC modeling to establish causal relationships between genetic variants and clinical outcomes. Fellow of American Heart Association (2016) Recipient of NCI R01 grant for Nilotinib Induced Artery Disease research NIH NHLBI Pathway to Independence Award recipient Editorial Board Member, Journal of Molecular and Cellular Cardiology (2020-present) Associate Editor, JACC CardioOncology (2018-present) Dr. Burridge advises multiple postdoctoral fellows including Ning Ge (cardiac arrhythmia modeling), Praeploy Pongpamorn (chemically defined differentiation), Nnamdi Uche (population-specific doxorubicin susceptibility), and George Gibbons. His lab has secured substantial grant funding for projects including large-scale hiPSC production, cardiotoxicity screening platforms, and novel drug discovery initiatives. The Burridge lab maintains extensive resources including high-throughput screening systems, CRISPR editing platforms, and bioreactor-based differentiation systems, all developed with a focus on eliminating animal-derived products from research.

• Philosophy of Physics
• Quantum Mechanics
• Relativity Theory
• +۳ مورد دیگر

Tomasz Placek is a Professor at the Jagiellonian University within the Institute of Philosophy , specifically the Department of Epistemology . His work bridges philosophy of physics , ontology , and theories of agency , with a focus on quantum mechanics, relativity, and epistemological frameworks. Research Interests : Philosophy of physics (quantum theory, relativity), causal set theory, determinism vs. indeterminism, and modal interpretations of spacetime. Key Contributions : Analysis of Wigner’s Friend paradoxes, causal structures in quantum correlations, and topological issues in indeterministic models. Email : tomasz.placek@uj.edu.pl

Sumon Biswasمشاهده پروفایل

استادیار

• Software Engineering
• Artificial Intelligence
• Programming Languages
• +۵ مورد دیگر

Sumon Biswas is a tenure-track Assistant Professor in the Department of Computer and Data Sciences at Case School of Engineering, Case Western Reserve University. Previously, he was a Postdoctoral Researcher at the Institute for Software Research (ISR) at Carnegie Mellon University, working with Dr. Eunsuk Kang. He received his Ph.D. in Computer Science from Iowa State University under the supervision of Dr. Hridesh Rajan. His research focuses on the intersection of Software Engineering and Artificial Intelligence with particular emphasis on responsible AI engineering. His work spans several key areas: Formal verification and reasoning of fairness in AI systems Designing fair and safe AI systems AI engineering and analysis of machine learning software Long-term risks in machine learning systems Analysis of technical debt in AI/ML systems Dr. Biswas has made significant contributions to understanding and addressing fairness in machine learning pipelines, verification of neural networks, causal reasoning in ML pipelines, and safety assurance of predictive systems. His recent work increasingly focuses on foundation models and large language models (LLMs), with an emphasis on safety and responsible deployment of AI agents. His lab operates the state-of-the-art AISC2 cluster with five HGX H200 servers featuring 40 NVIDIA H200 GPUs. His publications show a consistent trend toward addressing both theoretical and practical challenges in responsible AI, with increasing focus on long-term system behavior, LLMs, and practical deployment challenges. The research spans formal methods, empirical studies, and practical tool development. Dr. Biswas has received several awards including the Research Excellence Award from Iowa State University and has been invited to serve on the Board of Distinguished Reviewers for ACM Transactions on Software Engineering and Methodology (TOSEM). He serves on the program committees of major software engineering conferences including ICSE, ASE, and ESEC/FSE, and has reviewed for prestigious journals such as IEEE Transactions on Software Engineering. As an educator, he teaches courses on Responsible AI Engineering and Software Engineering, focusing on building high-quality software systems that meet responsible AI principles including fairness, robustness, explainability, and safety.

Alexia Auffèvesمشاهده پروفایل

استاد پژوهش

• Quantum Energetics
• Quantum Optics
• Quantum Foundations
• +۱ مورد دیگر

Alexia Auffèves serves as a First Class Research Director (DR1) at the French National Centre for Scientific Research (CNRS) and holds a Visiting Research Professor position at the Centre for Quantum Technologies (CQT), National University of Singapore. She directs the CNRS International Research Lab MajuLab and co-founded the Quantum Energy Initiative (QEI), an interdisciplinary global consortium investigating the energy footprint of quantum technologies. She completed her experimental PhD under Nobel laureate Prof. Serge Haroche. From 2017-2022, she led the QuantAlps center for quantum science in Grenoble before launching the Quantum Energy Initiative in 2022. Dr. Auffèves pioneers research at the intersection of quantum energetics, quantum optics, and quantum foundations. Her work establishes fundamental principles for quantifying energy costs in quantum information processing, bridging theoretical physics with philosophical inquiry. Recent focus includes developing energy efficiency metrics for quantum processors and analyzing thermodynamic constraints in quantum measurements. Her 2023-2025 publications reveal a cohesive research trajectory centered on quantum thermodynamics. Key contributions include establishing energy cost frameworks for quantum measurements, demonstrating reservoir-free decoherence mechanisms, and linking quantum negativity to anomalous energy exchanges. These works consistently integrate theoretical modeling with experimental validation through collaborations with leading quantum hardware groups. She leads multiple high-impact projects including BACQ and HQI (French Quantum Strategy), NGap (NRF), and OECQ (French Public Bank of Investment), involving industry partners like Alice&Bob, Quandela, and EDF to optimize quantum processor energy efficiency. Dr. Auffèves mentors a multinational research team comprising Kiarn Laverick, Kian Hwee Lim, Samyak Prasad, Nathan Shetell, Harshit Verma, Hanlin Nie, and PhD student Tejas Acharya. Her group operates within MajuLab and the Quantum Energy Team, driving collaborative research across France, Singapore, and international institutions.

B. Douglas Bernheimمشاهده پروفایل

استاد

• Behavioral Economics
• Public Economics
• Game Theory
• +۷ مورد دیگر

B. Douglas Bernheim is the Edward Ames Edmonds Professor of Economics at Stanford University's Department of Economics. He serves as the Academic Council Faculty Director of Undergraduate Studies, overseeing academic programs and policies for undergraduate economics students. His research spans behavioral economics, public economics, game theory, and financial economics, with notable contributions to rationalizability in game theory, coalition-proofness, and behavioral welfare economics frameworks. Professor Bernheim has received prestigious recognitions including an honorary doctorate from the University of Zurich and the 2022 Exeter Prize for groundbreaking work in experimental economics. His work often bridges theoretical economics with practical policy implications, particularly in areas like financial education and addictive behaviors. Research Interests: - Behavioral Welfare Economics - Social Motives for Economic Choices - Financial Education Policies - Theories of Collusion and Market Structures His recent publications explore interventionist policies in welfare states, peer influence in financial decisions, and the empirical foundations of decision theories like cumulative prospect theory. Bernheim's work emphasizes rigorous experimental methods and real-world policy applications, reflecting his dual focus on academic theory and societal impact.

• Human Resources Management
• Nonprofit Organizations
• Environmental Management
• +۳ مورد دیگر

Patrick VALEAU is a Full Professor specializing in Human Resources Management at the University of Rennes, affiliated with the CREM UMR CNRS 6211 research center. He serves as Director of Studies for the DU Recherche en Management program and contributes to the Formation continue initiatives. His research focuses on HR practices in nonprofit organizations (NPOs), environmental management within organizations, entrepreneurial persistence, and the intersection of organizational behavior and sustainability. Key research themes include mission-based HR strategies in NPOs, green HR practices for environmental performance, and the role of commitment in sustaining ventures during decline. He has also explored governance structures in religious associations and pandemic-era workplace safety behaviors. His work integrates qualitative and quantitative methods, including fuzzy-set qualitative comparative analysis (fsQCA) and longitudinal studies. Recent publications highlight innovations in HRM for environmental initiatives, the mediating effects of perceived organizational support, and the strategic orientations influencing high-commitment HR adoption. His research often bridges theory and practice, offering actionable insights for nonprofit governance, sustainable business practices, and entrepreneurial resilience. Patrick VALEAU collaborates with international scholars and contributes to journals such as Employee Relations , Journal of Environmental Planning and Management , and Nonprofit and Voluntary Sector Quarterly . His work addresses contemporary challenges in organizational management, emphasizing adaptability and ethical practices across diverse sectors.

• Epidemiology
• Neurosciences
• Psychiatric Disorders
• +۳ مورد دیگر

Christina Dalman is a Professor and Senior Physician at the Department of Global Public Health , Karolinska Institutet. She leads the Epidemiology of Psychiatric Conditions, Substance use and Social Environment (EPiCSS) research group, focusing on understanding risk and protective factors for mental ill-health to enable early intervention and prevention. Her work emphasizes socioenvironmental contexts, high-risk groups, and intervention evaluation. Education: Docent (Associate Professor), Karolinska Institutet (2010) Research Interests: Epidemiology of psychiatric disorders, substance use, and neurodevelopmental conditions Socioeconomic determinants of mental health Maternal health and neurodevelopmental outcomes Healthcare equity and access Recent Grants: Complications during pregnancy and birth and offspring risk for schizophrenia and other psychoses (Swedish Research Council, 2025–2027) Estimating the prevalence of emotional distress among teenagers in Sweden (Forte, 2022–2026) Publications: Over 200 peer-reviewed articles, focusing on mental health disparities, neurodevelopmental risks, and public health interventions. Key work includes studies on prenatal exposures, refugee mental health, and healthcare equity.

Jilles Vreekenمشاهده پروفایل

استاد

• Causal Inference
• Machine Learning
• Data Mining
• +۵ مورد دیگر

Prof. Dr. Jilles Vreeken is tenured faculty at the CISPA Helmholtz Center for Information Security , where he leads the Exploratory Data Analysis group. He also serves as an Honorary Professor at Saarland University . Research focuses on causal inference, machine learning, and data mining Develops unsupervised methods for robust, interpretable models PI on grants like HAICU's Neuro-Explicit Models and Crushing Antimicrobial Resistance His recent work spans causal discovery in non-stationary time series ( SPACETIME ), federated binary matrix factorization, interpretable neural search patterns, and data modification rule mining from event logs. He applies information-theoretic approaches to address hidden confounding, selection bias, and multi-environment causal modeling. Key trends in his publications include: Integrating causal inference with machine learning via algorithmic Markov conditions Advancing federated learning for privacy-preserving causal discovery Creating interpretable pattern mining frameworks for graphs, sequences, and high-dimensional data Developing MDL-based methods for reliable dependency and rule discovery Scientific Recognition: 2018 - IEEE ICDM Tao Li Award 2018 - IEEE ICDM Best Paper 2015 - UdS-CS Busy Beaver Teaching Award 2011 - ACM SIGKDD Best Student Paper 2010 - ACM SIGKDD Doctoral Dissertation Runner-Up 2009 - ECML PKDD Best Student Paper As an educator, he has supervised 15+ PhD/MSc students and taught courses like Topics in Algorithmic Data Analysis and Information-Theoretic Machine Learning . His research group pioneers methods for trustworthy information processing and causal anomaly detection , with applications in materials science, epidemiology, and cybersecurity.

• Computer Vision
• Metric Learning
• Image Generation
• +۳ مورد دیگر

Dr. Xinyu Zhang is a Research Fellow at the Australian Institute for Machine Learning (AIML), University of Adelaide's Faculty of Sciences, Engineering and Technology. Her research bridges computer vision and machine learning, focusing on image/video generation, self-supervised learning, and multimodal retrieval for human-centric AI applications. Zhang's current investigations include: Causal representation learning and multimodal integration Bayesian deep learning frameworks Video generation with temporal consistency Lightweight detection transformers Unsupervised person re-identification Analysis of recent publications reveals strong emphases on generative modeling innovations (especially video synthesis), efficient transformer architectures for real-time applications, and self-supervised representation learning. Her work frequently addresses the alignment between latent representations and human perception across vision-language tasks. Dr. Zhang co-supervises graduate students on projects involving multi-agent 3D scene generation and knowledge transfer in low-supervision learning. She serves as conference reviewer for premier venues including CVPR, ICCV, and NeurIPS, contributing to the advancement of computer vision research.

Lisa Leeمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Reinforcement Learning
• Continual Learning
• +۵ مورد دیگر

Lisa Lee is a Research Scientist at Google DeepMind, focusing on creating AI agents that emulate biological learning and adaptability. She previously taught at Princeton University and received TA awards for Deep Reinforcement Learning and Probabilistic Graphical Models. Education: PhD in Machine Learning from Carnegie Mellon University (advised by Ruslan Salakhutdinov and Eric Xing); A.B. in Mathematics from Princeton University (advised by Sanjeev Arora). Her research centers on AI embodiment, intrinsic motivation, and hierarchical planning. She explores how evolutionary-inspired inductive biases and memory mechanisms can enable agents to generalize across physical and conceptual domains, as demonstrated in her work on robotic agility benchmarks and multimodal transformers. Notable scientific contributions include the Barkour quadruped robot benchmark, Gemini multimodal models, and theoretical work on causal language models. She co-organized key AI workshops at NeurIPS and ICML, and her awards include Princeton's TA of the Year for technical courses. Leadership: ICML Workflow Chair (2019), NeurIPS workshop co-organizer (2019, 2021), peer reviewer for top AI conferences.

Philip Shawمشاهده پروفایل

دانشیار

• Macroeconomics
• Economic Growth
• Computational Economics
• +۳ مورد دیگر

Dr. Philip Shaw is an Associate Professor of Economics at Fordham University's Department of Economics. His research focuses on computational macroeconomics, nonparametric econometrics, and the economic impacts of corruption. He holds a Ph.D. from the University of Connecticut and specializes in macroeconomic theory, economic growth, and computational methods. Shaw teaches advanced courses such as Macroeconomic Theory II, Monetary Policy, and Nonparametric Econometrics. His work explores topics like educational corruption's effects on economic growth, nonparametric instrumental variable estimation, and stochastic general equilibrium models. He has published extensively in journals like the Journal of Econometric Methods, Contemporary Economic Policy, and Economics Letters. His teaching emphasizes computational tools like R and MATLAB for econometric analysis. Shaw's research bridges theoretical frameworks with practical computational solutions in macroeconomics and finance. Education: Ph.D., University of Connecticut Key Research Themes: Nonparametric econometric methods Computational solutions to DSGE models Educational corruption and its macroeconomic implications Instrumental variable estimation techniques Teaching Responsibilities: Graduate courses: Computational Economics, Econometrics I & II, Monetary Policy Undergraduate courses: Introductory Econometrics Recent Articles: Shaw's recent work includes analyzing corruption's role in educational choices (2023), nonparametric approaches to stochastic growth models (2014), and the determinants of educational corruption in Ukraine (2015). His methods often integrate advanced computational techniques to address econometric challenges.

Thomas Banitzمشاهده پروفایل

پژوهشگر

• Ecological Modelling
• Biodiversity Dynamics
• Microbial Ecology
• +۷ مورد دیگر

Thomas Banitz is a Researcher in the Department of Ecological Modelling at the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany. His work focuses on developing computational models to study ecological systems, population dynamics, and ecosystem functions. Key research areas include grassland biodiversity responses to environmental changes, microbial ecology, and causal reasoning in social-ecological systems. He leads projects like BioDT (biodiversity digital twin) and contributed to CauSES (causation in social-ecological systems). Education: PhD in Environmental Sciences from Universität Osnabrück (2011), Dissertation: 'Modelling bacterial growth, dispersal and biodegradation'. Research Highlights: Developed individual-based models for microbial systems (e.g., McComedy tool) Investigated microbial interactions and ecosystem processes in disturbed environments Advanced causal explanation frameworks for complex systems Explored spatiotemporal dynamics of biodiversity under environmental stressors Labs/Teams: Member of FORMIND vegetation model team and EcoEpi ecological epidemiology initiative. Collaborates with interdisciplinary groups on digital twins and sustainability science.