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518 Northcreek Dr. Durham, NC 27707

[téléphone] | [e-mail] | [lien]

Education

PhD in Statistical Science · Expected May 2020

Duke University, Durham, NC

Advisor: Mike West

B.A. in Mathematics, B.S. in Chemical Engineering · May 2014

Lafayette College, Easton, PA

Professional Experience

Machine Learning and Relevance Intern · May 2018 – August 2018

LinkedIn | San Jose, CA

Supervisors: Shaunak Chatterjee, PhD and Kinjal Basu, PhD

• Contributed to the ranking algorithm for content in the LinkedIn Feed
• Learned Spark and Scala to fit predictive models for user clicks, responses, and impressions
• Created a multi-objective optimization strategy for distributing user attention, implemented in R

Data + Project Manager · May 2017 – August 2017

Duke Information Initiative | Durham, NC

Supervisor: Rachel Richesson, PhD, MPH

• Managed a team of masters and undergraduate students exploring disease classification systems to quantify and visualize the prevalence of rare diseases at Duke Hospital

Business Intelligence and Analytics Consultant · July 2014 – September 2015

Thorogood Associates | Philadelphia, PA

Supervisor: Corey Hulse

• Provided business insights for a global packaged goods company using technologies such as Tableau, R, and SQL Server
• Implemented dynamic linear models in R to model time series of sales
• Presented in marketing and training events for a variety of clients Research Experience Bayesian Forecasting and Decision Analysis · January 2019 – Present 84.51 Research Assistant Advisor: Mike West, PhD
• Forecast product demand with novel Bayesian models for count-valued time series
• Researched computationally efficient methods to share information across related time series
• Created an open-source Python package for Bayesian time series modeling

Robust Latent Factor Analysis · August 2018 – June 2019

NIH Research Assistant

Advisor: Amy Herring, PhD

• Developed robust dimension reduction strategies in Bayesian factor models

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• Designed models to identify consistent risk factors in studies of chemical exposures
• Explored broadly applicable techniques for robust estimation and prediction

Deep Learning · August 2017 – May 2018

Independent Study

Advisor: Joseph Lucas, PhD

• Built a convolutional neural net to predict mortality risk for patients with pulmonary hypertension at Duke Hospital
• Derived model features from diagnosis codes, patient medications, and previous hospital visits
• Presented relevant research papers on deep learning for 2 semesters of independent study

Dynamic Forecasting · August 2016 – May 2018

SAMSI Optimization Research Assistant

Advisor: Mike West, PhD

• Designed an adaptive variable selection strategy for sequential prediction in Bayesian dynamic models
• Proposed novel ideas from Bayesian decision theory to combine goal-focused metrics, such as multiple step-ahead forecasting, with scalable computational strategies
• Applied the strategy to long-term macroeconomic forecasting

Semiconductor Simulation · June 2012 – May 2014

EXCEL Research Scholar and Honors Thesis student

Advisor: Joshua Levinson, PhD

• Developed a predictive numerical simulation of passivation processes in optoelectronic semiconductor materials
• Implemented a custom finite difference scheme in MATLAB for numerically solving systems of partial differential equations to improve simulation accuracy and robustness Relevant Coursework Deep Learning – Deep Learning Independent Study (2 semesters), Deep Learning for Coders (online course), Neural Networks and Deep Learning (textbook) Statistical Forecasting – Time Series and Dynamic Models, Bayesian Forecasting Programming – Statistical Computing (Python), Numerical Optimization Leadership Graduate Consultative Committee: Elected leadership position within Duke Statistical Science - Represented PhD Students to the department, and organized social and academic events Teaching Assistant: Introduction to Bayesian Statistics (STA 601), Hierarchical Models (STA 610), Linear Models (STA 721), Probability and Statistical Models (STA 831) Toastmasters: A professional club to develop public speaking and leadership skills Software Skills Software: pybats, a Python package for Bayesian dynamic modeling Programming Languages: Python, R, MATLAB. Basic SQL, C++, and Scala. Bash shell scripting Software Experience: Spark, Tableau Desktop and Server, Qlikview and Qliksense

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Publications

[nom], I., Cron, A., and West, M. “Analytic Inference and Forecasting in Count Time Series.” 2019.

Technical Report, Department of Statistical Science, Duke University.

Roy, A., [nom], I., Herring, A., and Dunson D. “Perturbed Factor Analysis: Improving generalizability across studies.” 2019. Submitted for publication. arXiv:[téléphone].

[nom], I., Lindon, M., and West, M. 2019. “Adaptive Variable Selection for Sequential Prediction in Dynamic Models.” Submitted for publication. arXiv: [téléphone].

Klosterman, S.T., Hufkens, K., Grey, J.M., Melaas, E., Sonnentag, O., [nom], I., Mitchell, L., Norman, R., Friedl, M.A., and Richardson, A.D. “Evaluating remote sensing of deciduous forest phenology at multiple spatial scales using PhenoCam imagery.” 2014. Biogeosciences, 11, 4305-4320.

[nom], M., Brothers, R.J., Lohmann, K.J., and [nom], I. “Sea Turtles: A Case of Animal Magnetism.”

2016. CHANCE Magazine.

[nom], I. and Levinson, J.A. “Modeling and Simulation of Hydrogen Passivation in Semiconductor

Photonic Materials.” 2014. Undergraduate Honors Thesis, Lafayette College Department of Chemical

Engineering.

Conference Presentations

Joint Statistical Meetings (JSM) · July 2019

Adaptive Variable Selection for Sequential Prediction in Dynamic Models

SAMSI Graduate Fellows Poster Session · May 2017

Adaptive Variable Selection for Sequential Prediction in Dynamic Models

American Chemical Society (ACS) · March 2014

Modeling and simulation of hydrogen diffusion and reaction in semiconductor photonic materials

Academic Honors

BEST Award (2017): BEST Foundation award to support Bayesian research in financial time series

National Science Foundation: Honorable Mention for the Graduate Research Fellowship

Luther F. Witmer Prize (2014): Lafayette College Chemical Engineering senior award

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