MUIDSI Dissertation Defense: IDENTIFICATION OF IMMUNE-RELATED GENE SIGNATURES TO EVALUATE IMMUNOTHARAPEUTIC RESPONSE IN CANCER PATIENTS USING EXPLORATORY SUBGROUP DISCOVERY

Phenotypic and genotypic heterogeneity are characteristic features of cancer patients. To tackle patients’ heterogeneity, immune checkpoint inhibitors (ICIs) represent one of the most promising therapeutic approaches. However, approximately 50% of cancer patients that are eligible for treatment with ICIs will…

MUIDSI DISSERTATION DEFENSE: Explainable Artificial Intelligence To Stratify Pan-Cancer Patients For Immune Checkpoint Inhibitor Decision Making

Immune checkpoints are a normal part of the immune system. It engages when proteins on the surface of immune cells called T cells recognize and bind to partner proteins on other cells, such as some tumor cells. Immune based therapies…

MUIDSI Comprehensive Exam — Measuring Geodiversity in Remotely-Sensed Imagery: Deep Spatial Change Detection Methods for Dataset Bias Mitigation and Visual Landscape Characterization

Amid explosive growth in availability of multimodal remotely sensed imagery (RSI) data from a constellation of overhead sensors, a lack of understanding persists concerning the actual content of these data sources, in particular the nature of spatial variation in the…

GIScience as an Interdisciplinary Bridge in Indigenous Health Equity 

GIS and geographic theories can help bridge a crucial gap in interdisciplinary research projects. Geography is uniquely poised to offer critical and practical analytical support, wrangle spatial data and relate them to other datasets, and ground community-based science within the…

Dissertation Defense – UNDERSTANDING GENOME COMPOSITION OF EUSOCIAL HYMENOPTERAN INSECTS

Genome sequencing of the Western honey bee (Apis mellifera), a model for the biology and evolution of eusocial behavior, has revealed unusual genome compositional characteristics, including a low but heterogeneous GC content, bimodal GC content distribution, and a biased tendency…

Comprehensive Exam: Accelerating Data-Driven Discovery In Type 1 Diabetes:An Informatics-Based Approach

Type 1 diabetes (T1D) is an immune-associated or immune-mediated chronic disease characterized by the progressive failure or targeted destruction of insulin-producing beta (β) cells in the pancreas. Management of the disease is challenging, involving lifelong exogeneous insulin replacement and 24/7 blood…

Computational Subgroups Stratification and Precision Drug Repositioning Using Explainable Artificial Intelligence

Enabling precision medicine requires developing robust patient stratification methods and identifying drugs tailored to homogeneous subgroups of patients from a heterogeneous population. Once discovering these subgroups, we can align patients and medications more specifically to achieve precision-based therapy. Developing de novo drugs…

Virtual Campus Visit with NSF CISE AD Dr. Margaret Martonosi

The National Science Foundation (NSF) supports a majority of US academic research in the Computer and Information Science and Engineering (CISE) topic areas. Since February, 2020, Dr. Margaret Martonosi serves as NSF CISE AD, stewarding the CISE directorate’s $1B annual budget on behalf…

Dissertation Defense – Utilizing Blockchain Technology for Clinical Trial Optimization

Clinical trials are the cornerstone of treatment discovery because they provide comprehensive scientific evidence on the safety, efficacy, and optimal use of therapeutics. However, current clinical trials are facing multiple challenges such as patient recruitment, data capture, and overall management.