جست‌وجوی استاد و پژوهشگر

Michael Charles Sachsمشاهده پروفایل

دانشیار

• Biostatistics
• Causal Inference
• Survival Analysis
• +۳ مورد دیگر

Michael Charles Sachs serves as Associate Professor in the Department of Public Health, Section of Biostatistics at the University of Copenhagen's Faculty of Health and Medical Sciences. He holds a Doctorate in Biostatistics from the University of Washington (awarded August 15, 2011) and maintains an active research program with publications spanning 2022-2025. His primary research focuses on biomarker signatures for treatment selection , computational methods for deriving symbolic bounds on causal effects , and regression modeling of cumulative estimands with censored event history data . His general areas of interest include reproducible research, computational statistics, R programming, Bayesian nonparametric models, and survival analysis. Professor Sachs teaches the advanced course "Programming and Statistical Modeling in R" for PhD students and health researchers, covering programming principles, loops, functions, and efficient data manipulation. His recent publications demonstrate expertise in causal inference methodology, survival analysis techniques, and statistical software implementation, with multiple articles accepted for publication in 2025. His work spans theoretical methodology development and practical applications in medical research, particularly in gastroenterology and celiac disease prediction. His scholarly output shows consistent productivity with multiple first-author publications in high-impact biostatistics journals including Journal of Statistical Software, Journal of Computational and Graphical Statistics, and Biostatistics. He actively organizes academic activities, including a May 2025 workshop on statistical modeling in R.

• Computational Chemistry
• Quantum Chemistry
• Theoretical Chemistry
• +۲ مورد دیگر

Theo Juncker von Buchwald serves as a Guest Researcher in the Department of Chemistry at the University of Copenhagen, located at Universitetsparken 5 in Copenhagen Ø. His research focuses on advanced computational methods in quantum chemistry, particularly developing and implementing cluster perturbation theories for molecular excitation energies and ground-state properties. His primary research interests center on Computational and Theoretical Chemistry, specializing in electronic structure theory. He develops high-accuracy quantum chemical methods including coupled cluster theory, variational excitation-energy functions, and core-valence separation techniques. His work bridges theoretical chemistry with high-performance computing, implementing parallel algorithms for large-scale molecular systems. Analysis of his four recent publications reveals a consistent research trajectory in Cluster Perturbation Theory (CPT), with increasing computational sophistication. His work demonstrates expertise in both theoretical development (variational formulations, Lagrangian approaches) and practical implementation (parallelization, GPU acceleration). Key trends include targeting CCSD/CCSDT accuracy with reduced computational cost, developing diagnostics for model reliability, and extending CPT to core-excited states for X-ray spectroscopy applications. Research Collaborations and Infrastructure: Collaborates extensively with Kurt V. Mikkelsen, Poul Jørgensen, and Jeppe Olsen Utilizes Frontier supercomputer at Oak Ridge National Laboratory Employs hybrid MPI/OpenMP parallelization with GPU acceleration Receives funding from Danish Council for Independent Research (Grants DFF-0136-00081B, DFF-10.46540/3103-00261B)