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Ellie Guan

Certified

Data Scientist

Swiss Re | Beijing

Technologies

My Portfolio Highlights

My New Course

Introduction to Python

My New Course

Introduction to Python

Quantitative guru, enlightening the world with data-driven wisdom.

My Work

Take a look at my latest work.

course

Understanding ChatGPT

course

Introduction to Python

course

Intermediate Python

course

Understanding ChatGPT

My Certifications

These are the industry credentials that I’ve earned.

AI Fundamentals

DataCamp Course Completion

Take a look at all the courses I’ve completed on DataCamp.

Courses

Introduction to Python

Introduction to Power BI

Intermediate Python

Data Manipulation with pandas

Courses

Introduction to Python

Introduction to Power BI

Intermediate Python

Data Manipulation with pandas

My Work Experience

Where I've interned and worked during my career.

Swiss Re | Aug 2022 - Present

Data Scientist / Scoring and Analytics Expert

Develop data-driven scoring and pricing models for automobile insurance

Beijing Institute for General Artificial Intelligence (BIGAI) | Jun 2022 - Aug 2022

Machine Learning Engineer

N/A

Siemens Digital Industries Software | Aug 2019 - Jun 2022

Research Scientist

N/A

CiBO Technologies | Jul 2018 - Feb 2019

Data Scientist

Develop, use, and refine statistical tools to improve and understand CiBOs computational agronomy models.

University of California San Diego | Jul 2017 - Jun 2018

Postdoctoral Researcher

Investigated social perception of human faces using statistical inference and computer vision techniques (Active Appearance Model) at the Computational & Cognitive Neuroscience Lab lead by Dr. Angela Yu (http:// www.cogsci.ucsd.edu/~ajyu/)

University of Arizona | Jul 2016 - Jun 2017

Postdoctoral Researcher

Developed a Bayesian predictive model that predicts health outcomes from emotional experiences. • Improved the Bayesian dynamical system to model different emotion regulation patterns. • Extended the model to predict health outcomes based on the different emotion regulation patterns.

University of Arizona | Dec 2012 - May 2016

Graduate Student Research Assistant

Project: Bayesian generative modeling for complex dynamic social systems We develop a Bayesian generative approach to infer the parameters of complex dynamical systems that are used to model emotion-interacting patterns from multivariate data collected in social psychology studies. We use the State Space Model (SSM) to model the dynamics of emotion interactions. The latent states of the SSM are composed of continuous real numbers that represent the level of the true emotional states of both partners and are evolved over time by the differential equation of a coupled oscillator physics model. The observed states include self-reported emotional experiences and physiological measurements of both partners during the interactions. We further use Gaussian process (GP) prior to model the changes/drifts of the coupled oscillator parameters in longer periods of social interactions where the interaction dynamics slowly and smoothly vary over time. To fit the parameters of the proposed Bayesian generative model from noisy experimental data, we develop Monte Carlo Markov chain (MCMC) inference procedures to learn the parameters of the priors from a set of training couples. Finally, we use cross- validation to evaluate the fitted model by learning the group-shared parameters and distributions from training couples and testing the learned models on some held-out testing couples.

University of Arizona | May 2011 - May 2016

Graduate Student Research Assistant

Project: Temporal scene understanding We develop a detection-based tracking system that infers people 3D locations, physical dimensions and head orientations from monocular camera videos using Bayesian statistical modeling and MCMC inference methods. We use a principled probabilistic approach within the tracking-from-detection paradigm, using people detection, facial landmark detection, and optical flow as evidence. We seek the MAP estimate of the data association as well as other scene parameters using MCMC sampling techniques. We are currently working on inferring interesting locations in the scene based on people visual attentions that inferred from their head orientations.

University of Wisconsin-Madison | Feb 2009 - Jun 2009

Java Programmer

I worked on a Web application for Finiancial aid and scholarships using Oracle JDeveloper.

My Education

Take a look at my formal education

Doctor's Degree, Computer ScienceUniversity of Arizona | 2016

Bachelor of Science (BS), Computer ScienceWinona State University | 2008

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