Teaching

University of Washington, Seattle. Summer Institute in Statistics and Modeling of Infectious

Diseases (SISMID)

Courses:

Summer 2018: Statistics and Modeling with Novel Data Streams, with Alex Vespignani.

Syllabus and Slides: Syllabus, Slides_1, Slides_2, Slides_3, Slides_4

Materials:, Dengue problem, Dengue data, Pseudo-code, toy-code

Solutions to exercise (prepared by Gal Wachtel): Static approach, Dynamic approach, Dinamic multivariate and seasonal approach,

ARGO: (R package), Manual, Sample R code for Zika prediction (prepared by Sarah McGough).

Data to predict Dengue in 5 countries: Yang et al. 2017, PLoS Comp Bio

Estimating Zika cases in Colombia in 2016: Instructions, Raw news_reports, Cumulative HM cases,

. Google trends Zika, Cumulative PAHO cases,

Exploring flu-related tweets: Flu-related tweets

Summer 2017: Statistics and Modeling with Novel Data Streams, with Alex Vespignani.

Summer 2016: Statistics and Modeling with Novel Data Streams, with Alex Vespignani.

• Harvard University, School of Engineering and Applied Sciences.

I have received two Harvard University Teaching Excellence Bok awards (2012 and 2014).

Courses:

Fall 2014: Physical Mathematics I, AppMath 201 (Graduate),M W, 1pm-2:30pm (Syllabus about Fall 2014: Physical Mathematics I, AppMath 201)

Spring 2014: Introduction to Scientific Computing, AppMath 111,Tu Th, 10-11:30am (Syllabus about Spring 2014: Introduction to Scientific Computing, AppMath 111)

Spring 2013: Introduction to Applied Mathematics, AppMath 50, MW, 1-2:30pm (Syllabus)

Fall 2012: Applicable Linear Algebra, AppMath 120, Tu Th, 2:30pm-4pm (Syllabus about Fall 2012: Applicable Linear Algebra, AppMath 120)

Spring 2012: Introduction to Applied Mathematics, AppMath 50, MW, 1-2:30pm (Syllabus)

Fall 2011: Applicable Linear Algebra, AppMath 120, Tu Th, 2:30pm-4pm (Syllabus about Fall 2011: Applicable Linear Algebra, AppMath 120)

Fall 2010: Practical Scientific Computing, AppMath 205 (Graduate), MWF 10-11am (Syllabus about Fall 2010: Practical Scientific Computing, AppMath 205 (Graduate))

---

2017

• David Castineira*, Massachusetts Institute of Technology, Postdoctoral Fellow/ Research Scientist
  Data-driven approaches to predict length of stay in pediatric patients
• Gaston Fiore*, Boston Children’s Hospital, Data Scientist
  Data-driven approaches for event detection in pediatric patients
• Katherine Schlosser*, Harvard Medical School, Fellow 2018
  Using vital signs to assess the need of escalation of care in a pediatric intensive care unit
• Yuval B. Corren*, Harvard Medical School/ Boston Children’s Hospital, Fellow 2018
  Using vital signs to predict readines of extubation for patients in a pediatric intensive care unit
• Nicholas Generous*, Harvard University School of Public Health, M.S. 2017
  Role of human mobility in the spread of mosquito-borne diseases
• Leonardo Cesar Clemente*, Monterrey Institute of Technology, Master’s student
  Development of tools to track flu in Latin America.

2016

• Fred Lu*, Boston Children’s Hospital, Data Scientist
  Development of ensemble methods to forecast flu activity in multiple spatial resolutions
• Sarah McGough*, Harvard University School of Public Health, PhD student in Global Health
  Forecasting Zika Incidence in the 2016 Latin America Outbreak Combining Traditional Disease
  Surveillance with Search, Social Media, and News Report Data
• Samuel Tideman*, Harvard University School of Public Health, M.S. 2016
  Google search information improves prediction of daily emergency medicine vists
• Kristin Baltrusaitis*, Boston University School of Public Health, PhD student
  Using crowd sourced disease surveillance tools to monitor flu activity in multiple scales
• Suqin Hou*, Harvard University School of Public Health, M.S. 2016
  Using Twitter and Google searches to track flu activity in Boston
• Tamara Louie*, Harvard University School of Public Health, M.S. 2016
  Cloud-based Electronic Health Records for Real-time, Region-specific Influenza Surveillance

2015

• Andre Nguyen*, Harvard University, B.S. Applied Mathematics, 2015
  Machine learning ensemble approaches to predict influenza epidemics in real-time
• Wesley Chen*, Harvard University, B.S. Applied Mathematics & M.S. Computational Sciences, 2015
  Using Twitter microblogs to track Chikungunya in Puerto Rico

2014

• Aditi Hota*, Harvard University, B.S. Applied Mathematics, 2014
  Development and Validation of Statistical and Deterministic Models to Predict Dengue in Mexico

2013

• Clifton Dassuncao*, Harvard University, M.S. Public Health, 2013 (Co-advised with Elsie Sunderland)
  Modeling Cholera outbreaks in Mozambique via human mobility networks
• Wendong D Zhang*, Harvard University, B.S. & M.S. Applied Mathematics, 2013
  Real-Time Estimates of Flu Activity Using Google Search Queries. A Dynamic Approach
• Michaela Tracy, Harvard University, B.S. Applied Mathematics, 2013
  Bach in Beta: Modeling Bach Chorales with Markov Chains
  

2012

• Adam Arthurs, Harvard University, B.S. Applied Mathematics, 2012
  A Decision-Making Support Tool for Generating Profitable and Practical Investment Strategies
  2008 and earlier
• Fidel Serrano, CentroGeo, Masters in Geomatics, 2008
  Modeling and Simulation of the Dynamics of Land Use in Urban Environments
• Fidel Serrano*, Universidad Nacional Autónoma de México, B.S. Physics, 2006
  Simulation of an Urban System Using Cellular Automata.

---

Previous Teaching Experience:

• University of Texas at Austin, Substitute lecturer, 2004-2008
  Courses: Graduate courses in applied mathematics and Aerospace Engineering (with Clint Dawson)
• Centro de Investigación en Geografía y Geomática, Lecturer and thesis advisor, 2003-
  Seminars: Mathematical Modeling in GIS (graduate)
• University of Texas at Austin, Teaching Assistant, 2002
  Courses: Introduction to Calculus.
• Universidad Nacional Autónoma de México, Teaching Assistant, 1998 – 2000
  Courses: Calculus I and Calculus II, Multivariable Calculus I and Multivariable Calculus II, Ordinary Differential Equations I.