Intekhab will present the dissertation entitled “Biologically motivated artificial intelligence for explainable gene regulatory dynamics”. The dissertation committee is chaired by Dr. John Quackenbush, and includes Dr. Rebekka Burkholz, Dr. Rong Ma, and Dr. Kimberly Glass.
Eric will present the dissertation entitled “Statistical Methods for the Study of Effect Modification and Spatial Causal Inference: Theory and Applications”. The dissertation committee is chaired by Dr. José Zubizarreta, and includes Dr. Rajarshi Mukherjee and Dr. Andrea Rotnitzky.
Amy Zhou, PhD Student, Department of Biostatistics, Harvard University Comparison of Outcome-Dependent Sampling for Semi-Competing Risks Abstract: Outcome-dependent sampling is a commonly used design tool to collect otherwise unavailable information on a subset of participants rather than all participants. This is particularly useful in research settings where one or more covariates of interest may not … Continue reading "Quantitative Issues in Cancer Research Working Group Seminar"
Carmen B. Rodriguez, PhD Student, Department of Biostatistics, Harvard T.H. Chan School of Public Health A Bayesian Mixture Model Approach to Examining Socioeconomic Disparities in Endometrial Cancer Care in Massachusetts. Abstract: Endometrial cancer (EC) is the most common gynecologic cancer in the United States. On average, African American women have 55% higher 5-year mortality risk … Continue reading "Quantitative Issues in Cancer Research Working Group Seminar"
Seunggeun 'Shawn' Lee Adjunct Professor, Biostatistics University of Michigan Rare variant association analysis Rare variants significantly impact complex diseases. This presentation will first introduce SAIGE-GENE and SAIGE-GENE+, methodologies extending SAIGE to gene/region-based rare variant tests. These methods efficiently utilize mixed effects models to adjust for sample relatedness and saddlepoint approximations to account for case-control imbalance. … Continue reading "PQG Seminar"
Paige Williams Senior Lecturer on Biostatistics, Harvard T.H. Chan School of Public Health, Department of Biostatistics The Pediatric HIV/AIDS Cohort Study (PHACS) Abstract: The Pediatric HIV/AIDS Cohort Study (PHACS) network conducts multiple longitudinal cohort studies investigating the long-term effects of HIV and antiretroviral (ARV) medications in children and young adults who were born with HIV … Continue reading "HIV Working Group Seminar"
Kimberly Greco, PhD Student, Department of Biostatistics, Harvard T.H. Chan School of Public Health Graph Attention Framework to Enhance Rare Disease Sub-Phenotyping from EHR Abstract: Accurately sub-phenotyping patients according to their risk for an adverse clinical outcome can significantly enhance clinical decision-making. Recent advances in patient representation learning have enabled the development of sophisticated clustering … Continue reading "Quantitative Issues in Cancer Research Working Group Seminar"
Elizabeth Graff, PhD Student, Department of Biostatistics, Harvard T.H. Chan School of Public Health Applications of Deep Learning for Graph-Structured Data: From Disease Spread to Social Networks Abstract: How can we apply deep learning to solve problems in modeling the spread of disease? In this talk, we will explore the components and applications of Graph … Continue reading "Quantitative Issues in Cancer Research Working Group Seminar"
Ruben Dries Assistant Professor, Medicine Boston University Towards Solutions for Large-Scale Multi-Modal Spatial Data Analysis In the burgeoning field of spatial biology, the integration of multi-modal spatial omics technologies presents both a formidable challenge and a tremendous opportunity for advancing clinical research and diagnostics. I will discuss the concerted efforts of our laboratory to address … Continue reading "PQG Seminar"
Christian Covington, PhD Student, Department of Biostatistics, Harvard T.H. Chan School of Public Health Statistical theory and the practice of data analysis: A brief and biased history Abstract: This talk gives an account of the replication crisis and how different disciplines– namely applied sciences, statistics, and theoretical computer science (TCS), have developed their own research … Continue reading "Quantitative Issues in Cancer Research Working Group Seminar"
