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Qi Qi, Ph.D.

Statistical Scientist

Genentech, A Member of the Roche Group

Biography

Qi Qi is working as a Senior Statistical Scientist at Genentech. She received her PhD in Statistics from University of Connecticut. Her research interests include Survival Analysis, Bayesian Methods, Longitudinal Data Analysis, Joint Modeling, Stochastic Models, Data Visualization, Machine Learning, Data Mining, Statistical Computing. She has worked as a research fellow at Boehringer - Ingelheim and research assistant at Albert Einstein College of Medicine.

Qi enjoys swimming, playing badminton and painting. She works out regularly and sometimes goes hiking. Qi loves her cat a lot. Her cat, Hera, is a lovely and sweet tuxedo cat and was born on July 2, 2016. It is her happiest moment when the cat sleeps in her arms every night.

Interests

  • Survival Analysis
  • Bayesian Methods
  • Longitudinal Data Analysis
  • Joint Modeling
  • Stochastic Models
  • Multi-stage Analysis
  • Data Visualization
  • Machine Learning
  • Statistical Computing

Education

  • PhD in Statistics, 2020

    University of Connecticut

  • MS in Statistics, 2017

    University of Connecticut

  • BS in Statistics, 2015

    Renmin University of China

Experience

 
 
 
 
 

Statistical Scientist

Genentech

Aug 2020 – Present Califonia
Responsibilities include:

  • Being study lead statistician for multiple clinical trials.
  • Collaborate with different functions, including clinical science, operation, safety, pharmacokinetics, biomarker, imagining science, etc.
  • Author study documents (protocol, statistical analysis plan, clinical study report, conferences/publications, etc.), being responsible for study design & sample size calculation, conduct statistical analyses, QC statistical outputs.
  • Lead a successful study read-out (Press Release).
 
 
 
 
 

Research Fellow

Boehringer - Ingelheim

Dec 2019 – Jul 2020 Connecticut
Responsibilities include:

  • Conduct research for potential type I error inflation if using Chronic slope to assess treatment effect.
  • Conduct Segmented Emax model for exposure-response analysis for Phase II dose finding study.
 
 
 
 
 

Biostatistics & Data Sciences Intern

Boehringer - Ingelheim

May 2019 – Aug 2019 Connecticut
Proposed and validated random change point model of estimating two/three intersecting lines.
 
 
 
 
 

Research Assistant

Albert Einstein College of Medicine

Aug 2017 – Dec 2019 Connecticut
Responsibilities include:

  • Evaluate the prediction accuracy of a new classification system of memory impairment for Alzheimer’s disease.
  • Investigate significant features affecting the prediction for Alzheimer’s disease.
  • Estimate transitional probabilities among the stages of memory impairment and investigate significant features on transition.
  • Explore the relationship between memory impairment test and AD neuropathologic change.
 
 
 
 
 

Statistical Consultant

University of Connecticut

Aug 2017 – May 2019 Connecticut
Presented workshops ‘Variable Selection with Demos in R’ and ‘Survival Study Design and Analysis’. Provided full project service, online question service and walk-in service.

Skills

Statistical Software

R, SAS, BUGS, JAGS, SPSS, AMOS, Matlab, Stata

Interactive Visualization

demo: https://qiqi7777.shinyapps.io/registrar/ https://qiqi7777.shinyapps.io/nyc_housing/

Github

Latex

Swimming

Sketch and Painting

Projects

A Bayesian Joint Model of Longitudinal Ordinal Outcomes and Time-to-event Data

Construct joint models and ROC curves to evaluate predictive performance of a new classification for Alzheimer’s Disease and …

A Bayesian Multistage Model for Joint Transitional Data

Construct a Bayesian stochastic multi-stage model to estimate transitional probabilities and evaluate the correlation among different …

A Bayesian Transitional Model for High Dimensional Data with Application to Human Microbiome Project

Conduct a Bayesian transitional model to perform variable selection for high dimensional microbiome data.

Bayesian Mixture Model on Determination of Root Cause Frequency

Estimated the proportion of root cause using power prior method and compared with EM algorithm.

Change Point Detection and Slope Estimation for eGFR

Constructed two different random slope models based on Poisson process to detect one or two change points and estimate the chronic …

Change Point Detection of Reputation Damage

Constructed change point analysis to detect reputation damage of United Airline based on high dimensional data obtained by text mining …

Competing Risk Analysis Based on SEER Breast Cancer Data

Estimated CIF and test the equality between different cause of death. Constructed semiparametric proportional hazards model for the …

Cost-Benefit Study

Conducted cost-effectiveness analysis and subgroup analysis on the SEER data based.

Interactive Visualization of Changes in Housing Condition in NYC

Built R shiny apps (demo: https://qiqi7777.shinyapps.io/nyc_housing/) to describe the changes in housing conditions for the first …

Interactive Visualization of Difficulties of Scheduling Classes

Conducted R shiny apps (demo: https://qiqi7777.shinyapps.io/registrar/) to visualize the occupancy of classrooms of University of …

Manuscripts

Working Papers
Qi Qi, Ph.D.
Project Project Project Project Project
Work in Progress
Qi Qi, Ph.D.

Presentations

Interactive Visualization of Housing Condition Changes in NYC

The objective is to address the research question of NYCHVS in the ASA Data Challenge Expo, which is to describe changes in housing …
Aug 28, 2019 14:00 Colorado Civention Center
Project

Predicting Alzheimer's Disease Using a New Classification System Based on Objective Memory Impairment Assessment

Stages of Objective Memory Impairment (SOMI) has been recently proposed by Grober et al. (2018) as a new classification system that …
May 16, 2019 16:00 Hilton Hartford
Project

A Multi-Stage Stochastic Model in the Analysis of Longitudinal Data

Multi-stage transition model is playing an important role in dementia studies. Since death is a significant source of missing data in …
May 12, 2018 16:00 Oak Hall, University of Connecticut
Project

Service

Session Chair

Joint Statistical Meeting Jul 2019

Committee Member & Session Chair

Conference on Bayesian Modeling, Computation and Applications May 2018

Contact

  • 600 E Grand Ave., South San Francisco, CA, 94080, United States