Florida United States
Senior Data Scientist/Author
Technology / Software / Internet
I am a computational topologist/geometer interested in the use of theoretical topology and geometry to extend existing statistical frameworks (GLMs, survival analysis, factor analysis/structural equation models, hypothesis tests, Bayesian adaptive trial designs), machine learning methods, graph/network analytics, and partial differential equation models of biological/industrial systems. These more general models allow for more flexible modeling and can accommodate diverse data structures. If there's an obscure mathematical theory that can solve a pressing problem, I'll find it and figure out how to leverage it in an analytics problem.
machine learning data science analytics topological data analysis big data statistics topology quantum computing time series natural language processing social network writing generalized linear regression network analysis supervised learning data analysis geometry differential geometry cluster analysis substance abuse psychometrics clustering poetry ebola python psychology alcoholism graph theory higher education persistent homology deep learning factor analysis addiction genomics unsupervised learning generative ai agriculture text data publishing diversity sociology neuroscience business intelligence healthcare profound giftedness profoundly gifted giftedness marketing business data mining data visualization manifold learning neural networks medicine superlearning tda reeb graph morse functions morse-smale complex hierarchical clustering homotopy principle component analysis mental health random forest tree methods image analytics epidemics hiv covid pydata finance development conference malawi ethics apps linguistics africa translation nlp career literature literary devices prosody lay audiences scientific writing science journalism academic writing politics stock market community detection stem education technology university of chicago women in data science conference 2018 wids intelligence gifted education insurance actuarial science theology einstein quantum theory physics brain biology pharmaceutical neurobiology gender graduate school medical research medical school medical scientist training program mstp md/phd alcohol abuse ptsd trauma education talent gifted acceleration eminence genius k-nearest neighbor regression subpopulation rare disease clinical trial robust analysis small sample multidimensional scaling laplacian eigenmaps isomap dimensionality reduction signal processing latent factors singular value decomposition multilinear algebra medical tensor decompositions fourier analysis spectral methods markov chains operations forecast mapper algorithm multiscale methods cox regression ensemble learning model averaging boosted regression bayesian statistics survival analysis survey design identity predictie analytics logistic regression genetic algorithm evolutionary algorithms hausdorffMehr anzeigen
Forecasting time series for business and operations data: A tutorial
Colleen Farrelly • Vor 5 Jahren