Jene’ Madison, PhD

Quantitative and Qualitative Data Analysis; Text Mining & Sentiment Analysis; Scaled, Ordinal & Survey Data;  Experimental Design & Hypothesis Articulation; Biostatistics; Genomics; Population Genetics & Evolution; Geospatial Analysis; Machine Learning; Data Mining; Data Visualization; 'Big Data'

Tools Used: Python, R, SPSS, Systat, Weka, Knime, RapidMiner, Tableau, Hadoop Ecosystem, & Spark

Platforms: Windows, Linux, AWS, Google Cloud, HPC Environments

Dr. Madison has experience in analyzing data of numerous sources, including genomics and genetic data; sentiment analysis of text; and analysis of time series data.  She has over 10 years of experience with teaching and mentoring students in all phases of the data life-cycle: from collecting data, selecting the appropriate methods of analysis, extracting meaningful insights from the results, to articulating application within a variety of contexts. 

As a SCIENTIST she observes information flows, and articulates testable hypotheses (when possible); otherwise, she creatively seeks hidden structure, patterns, and meaning from fuzzy data. As a RESEARCHER she stayed updated with advancements in technology and knowledge, and innovates novel solutions to complex problems. As an ANALYST she verifies and validates her findings; and an EDUCATOR- she shuns overtly technical jargon, so that her words resonate with diverse audiences.

For her Master's work, Dr. Madison focused on: (1) Geospatial and temporal segmentation; (2) Applying Frequentist and Bayesian models of evolution; and (3) Identify features corroborating network topology.

For her PhD & Postdoc work, Dr. Madison focused on: (1) Likelihood ratio test and clustering to identify statistical outliers; (2) Anomaly detection amongst billions unlabeled text instances; (3) Identify elements which support group membership; (4) Extract meaning from volumes of unlabeled data generated by an ambiguous process; (5) Combine disparate data for validation, identifying deviation from norms, providing contextual frameworks; (6) Conveying insights from data, and meaning, value, and application of findings.