Katelyn Arnemann

Katelyn Arnemann has a diverse work experience in the field of data science and research. Katelyn is currently working as a Senior Data Scientist at Unlearn.AI, where they utilize their scientific and data science skills to accelerate clinical trials and build data products for ML models. At Unlearn.AI, they are the product owner of DataMontage, a state-of-the-art internal data product, and collaborates on software development to improve the quality and efficiency of data processing tools.

Prior to their current role, Katelyn worked as a Research Scientist at Datacubed Health, where they applied their scientific and statistical/ML expertise to drive innovation in digital health. Katelyn collaborated with cross-functional teams to set scientific requirements and data specifications for products, conducted statistical validation of mobile app features, and prepared technical reports and white papers to demonstrate the platform's performance and value.

In addition, Katelyn has experience as a Postdoctoral Research Scientist at Rutgers University - Newark, where they focused on neuroimaging. Katelyn also worked as a Data Science Fellow at Insight Data Science, where they built a web-app recommendation system for travel destinations by scraping, cleaning, and feature-engineering text data. Katelyn also explored categorical features using dimensionality reduction and employed topic analysis to recommend travel destinations.

Furthermore, Katelyn has a strong research background from their time as a Graduate Student Researcher at UC Berkeley, where they studied the etiology of Alzheimer's disease using graph-based models. Katelyn collected and analyzed longitudinal times series and 3D imaging data from MRI and PET, built predictive models, and developed a novel graph-based model of the topological spread of Alzheimer's disease pathology. Katelyn also served as a Graduate Student Instructor during their time at UC Berkeley.

Prior to their graduate studies, Katelyn worked as a Data Analyst at the Department of Veterans Affairs, where they used machine learning techniques to predict rehabilitation in brain-injured patients. Katelyn collaborated on code development and utilized graph-based community detection and perceptron neural networks to identify functional brain networks and explore information encoding.

Katelyn's early research experience includes working as a Research Assistant in Cognitive Science at Case Western Reserve University. Katelyn contributed to experimental design and conducted pilot analyses for fMRI studies and large-scale studies on individual differences in cognition.

Overall, Katelyn Arnemann has a strong background in data science, statistical analysis, and research, with experience in both academic and industry settings.

Katelyn Arnemann pursued their education in a chronological manner. Between 2007 and 2010, they attended Case Western Reserve University, where they obtained a Bachelor of Arts (B.A.) degree in Cognitive Science & Philosophy. Subsequently, from 2012 to 2018, they enrolled in the University of California, Berkeley. Here, they pursued a Doctor of Philosophy (Ph.D.) degree specializing in Neuroscience.