UCLA | MDSH

2025 MDSH Summit

2025-04-24T00:00:00+00:00

Friday, June 6, 2025
8:45am-5:30pm, UCLA Kerckhoff Hall

Morning

Time	Session	Speaker(s)	Judges	Location
8:45 AM–9:00 AM	Registration & Breakfast			Grand Salon
9:00 AM–9:20 AM	Program Welcome	Hua Zhou (MDSH Director) & Mia Giordano (MDSH Project Coordinator)		Grand Salon
9:20 AM–9:30 AM	School Welcome	Ron Brookmeyer (FSPH Dean)		Grand Salon
9:30 AM–10:15 AM	Plenary Talk 1	Stella Grosser (U.S. Food and Drug Administration, Division Director)		Grand Salon
10:15 AM–10:30 AM	Break
10:30 AM–11:00 AM	Capstone Session 1	Team 4 – U.S. Food and Drug Administration Center for Devices and Radiological Health	Yu Wu (Galderma) Damla Şentürk (UCLA)	State Room
		Team 7 – Boston Children’s Hospital	Linxia Ren (Microsoft) Yuhua Zhu (UCLA)	Art Gallery
		Team 6 – Santa Clara County Social Services Agency	Greg Watson (Prenosis) Kate Crespi (UCLA)	Grand Salon
11:00 AM–11:15 AM	Break
11:15 AM–11:45 AM	Capstone Session 2	Team 1 – Audible Amazon	Yu Wu (Galderma) Grace Hyun Kim (UCLA)	State Room
		Team 11 – Microsoft	Derek Lee (Santa Clara County) Jin Zhou (UCLA)	Art Gallery
		Team 9 – ByteDance	Louay Constant (Santa Clara County) Xiaowu Dai (UCLA)	Grand Salon

Lunch
12pm-1pm, Kerckhoff Hall Coffee Patio

Afternoon

Time	Session	Speaker(s)	Judges	Location
1:15 PM–2:00 PM	Plenary Talk 2	Bonnie Zhang (Edwards Lifesciences, VP of Biometrics)		Grand Salon
2:00 PM–2:15 PM	Break
2:15 PM–2:45 PM	Capstone Session 3	Team 8 – UCLA Biostatistics	Yu Wu (Galderma) Marc Suchard (UCLA)	State Room
		Team 10 – Amgen	Stella Grosser (FDA) Fei Yu (UCLA)	Art Gallery
		Team 12 – Los Angeles Dodgers	Jing Zhai (FDA) Donatello Telesca (UCLA)	Grand Salon
2:45 PM–3:00 PM	Break
3:00 PM–3:30 PM	Capstone Session 4	Team 5 – City of Hope	Leiwen Gao (Amgen) Fei Yu (UCLA)	State Room
		Team 3 – Amazon Web Services	Bonnie Zhang (Edwards Lifesciences) Kate Crespi (UCLA)	Art Gallery
		Team 2 – Prenosis	Justin Williams (LA Dodgers) Marc Suchard (UCLA)	Grand Salon
3:30 PM–3:45 PM	Break

Closing

Time	Session	Speaker(s)	Location
3:45 PM–4:30 PM	Plenary Talk 3	Joseph Zoller (UCLA)	Grand Salon
4:30 PM–6:30 PM	Awards & Reception	Hua Zhou (MDSH Director) & Mia Giordano (MDSH Project Coordinator)	Grand Salon & Side Patio

GLA Health Data Science Career Day

Registration

Saturday, June 7, 2025
8:30am-12:30pm, UCLA Kerckhoff Hall

MDSH SUMMIT attendees are invited to the Greater Los Angeles Health Data Science Career Day, co-sponsored by International Chinese Statistical Association (ICSA) and UCLA MDSH. This half-day event features exhibits by pharmaceutical, biotechnology, and technology companies, mock interviews, and a panel discussion by leading statisticians and data scientists in industry.

Time	Session	Location
8:30 AM–10 AM	Exhibits	State Rooms
10 AM–11 AM	Mock Interviews	State Rooms
11:15 AM–12 PM	Panel Discussion	State Rooms
12 PM–12:30 PM	Boxed Lunch and Networking	State Rooms

Admission Requirements

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Admission Requirements
How to Apply
Deadlines
Admissions Timeline
Admissions Appeals

The Master of Data Science in Health (MDSH) applicants are expected to fulfill the minimum requirements for admission to the Fielding School of Public Health. Prospective students are encouraged to attend an information session, or contact us for an admissions consultation.

Admission Requirements

Resume/CV: Full-time work experience is not required.
Official Transcripts: A bachelor’s degree with at least a 3.0 cumulative GPA, or the equivalent. You may apply to the program using Unofficial Transcripts. Official transcripts will be required before enrollment. They must be sent directly by your University’s Registrar Office or via Parchment to admissions@ph.ucla.edu.
Statement of Purpose. Applicants should use these statements to highlight their academic background, research, or work experience, and their qualifications to contribute to the MDSH and to the field. Include your career goals and how the MDSH might aid in your professional growth.
Three Letters of Recommendation: Uploaded to the UCLA application site directly by your recommenders. Letters should be from a professional and/or academic source.
TOEFL/IELTS Scores: Test of English as a Foreign Language (TOEFL) or the International English Language Testing System (IELTS) is required for applicants who completed their post-secondary education outside of an Anglophone country. See University Policies and Requirements for details. Be sure to use exactly the same personal information (name, date of birth, gender) in your UCLA Graduate Application as you did in your TOEFL/IELTS testing.
GRE Scores (optional). If you choose to submit GRE scores, make sure to use exactly the same personal information on the GRE application as on the UCLA graduate application.

How to Apply

All applicants must apply online and submit application materials via UCLA’s Application for Graduate Admission.

Program name: Data Science in Health MDSH (Major code 00J7).
The GRE Code for UCLA is 4837, if you choose to submit these scores.
Please be sure to fill in all required sections.
- The Personal Statement is optional.
- A SOPHAS application is not needed.

The application fee is $135 for U.S. Citizens or Permanent Residents, or $155 for other applicants. The application fee is devoted to the administrative cost of processing applications, and is non-refundable.

Deadlines

The following deadlines apply to applications for Fall 2026 enrollment:

Priority deadline: February 1, 2026
Regular deadline: April 1, 2026
Final deadline: June 15, 2026

Admissions Timeline

Applications are reviewed on a rolling basis; decisions will be released in the 4-6 weeks following each deadline (priority, regular, and final deadlines).

The length of time it will take to release the admissions decision will depend on several factors, including the completeness of the application (transcripts, TOEFL/IELTS scores, Letter of Recommendation, etc.). To ensure the fastest possible processing of your application, be sure to upload all required documents.

Admissions Appeals

We acknowledge the effort required to submit an application to our program and thank each applicant for their attention to creating a high-quality submission. Multiple reviewers thoroughly review all applications. The MDSH program does not consider appeals except in light of new information. New information is limited to academic qualification which may include higher GPA, grades, and certification not already included in the application. TOFEL/IELTS scores are not considered new information. Due to the volume of applications, we do not provide individual feedback on the quality of applicants nor provide suggestions on how to strengthen future applications. If you wish to submit an appeal: email mdsh@ucla.edu with subject line, “Admissions Appeal” with the following content:

A one sentence summary of the new information
Relevant supporting documentation

Information Session

2022-09-09T00:00:00+00:00

Our next information session will be held on Monday, January 5th, 2026 at 5:00 PM PST, where you will have the opportunity to meet with the Director, program staff, teaching faculty, and students.

Finance

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Tuition and Fees
Financial Aid
- Federal Student Loans
- Sallie Mae Graduate Loans for Health Professions
Scholarships
- MDSH Student Scholarships
- Sallie Mae Graduate School Scholarship Tool
Veterans and Military Service Members
Refunds

Tuition and Fees

Tuition per credit hour is assessed based on year of entry into the MDSH program. Tuition covers the cost of registration and enrollment, and can be paid in three payments during each academic year.

MDSH Cohort	Tuition per credit hour	Total tuition for 2-year, 48 unit program
Entered Fall 2023	$1,200	$57,600
Entered Fall 2024	$1,250	$60,000

Students enrolled in this program are also required to pay the student services fee, campus‐based fees and health insurance. For the most up to date fees and more information on fee breakdown, visit the registrar’s office.

Financial Aid

Federal Student Loans

Most fully employed students are eligible for federal student loans. Please visit the UCLA Financial Aid website for detailed information on how to submit your FREE Application for Federal Student Aid (FAFSA). If you miss the deadline, you can still submit an application.

Upon acceptance into the program, financial aid notices will be available to students mid July and will continue throughout the academic year. It is very important to complete the FAFSA application as soon as possible.

Sallie Mae Graduate Loans for Health Professions

Sallie Mae offers graduate loans for Health Professions. Pay for your expenses in allied health, nursing, pharmacy, and other graduate-level health degrees. You can visit the site here.

Scholarships

MDSH Student Scholarships

The MDSH Program offers limited scholarships to currently enrolled MDSH students based on merit, need, and community involvement.

Sallie Mae Graduate School Scholarship Tool

Sallie Mae has a tool to help find scholarships for graduate school. You can visit the search tool here.

Veterans and Military Service Members

The MDSH program is approved by the U.S. Department of Veterans Affairs for the use of federal VA education benefits (Chapter benefits), such as the Post-9/11 GI Bill® (Chapter 33) and Dependents’ Educational Assistance (Chapter 35). For more information about using federal benefits at UCLA, please visit the UCLA Veteran Resource Center’s Benefits Overview page.

If you are exploring Department of Defense (DoD) Tuition Assistance or other military branch–specific education benefits, please consult your Education Services Officer (ESO) or your Military Service counselor, as these benefits are administered separately from the VA. You can also review how DoD Tuition Assistance is processed at UCLA here.

Please note: As a self-supporting degree program, the MDSH program is not eligible for the Cal Vet College Tuition Fee Waiver.

Refunds

Students can receive a 100% refund of tuition for all units dropped before the end of the 3rd week of the quarter. After that, they may receive a 50% refund until the end of the 4th week. Tuition for courses dropped after the 4th week is not eligible for refunds.

Class Schedules

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2025 - 2026 Class Schedules

Class Schedule for 2025-2026 - Class of 2027
Class Schedule for 2025-2026 - Class of 2026

Past Class Schedules

Class Schedule for 2024-2025 - Class of 2026
Class Schedule for 2024-2025 - Class of 2025
Class Schedule for 2023-2024 - Class of 2025

Academic Calendars

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Academic Calendar of 2025-2026

Academic Calendar of 2024-2025

Academic Calendar of 2023-2024

Admitted Students

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Official Transcripts
UCLA Logon ID
Student Handbook
Student ID (BruinCard)
Title IX Training
Vaccinations
Bruin Learn
Parking
Housing

Official Transcripts

After you have been admitted to the program, official transcripts with degree conferral and date of conferral must be provided. Official transcripts must be sent directly by your institution’s Registrar in one of the following ways:

Electronic Delivery Address: admissions@ph.ucla.edu

Physical Mailing Address:

UCLA Fielding School of Public Health
c/o Michelle Garcia
650 Charles E. Young Drive S., Room 16-068
Los Angeles, CA 90095

UCLA Logon ID

To create your UCLA Logon ID go to https://accounts.iam.ucla.edu/#/.

Student Handbook

For a checklist of important steps for newly admitted students, as well as other important information about the program, please see the Student Handbook.

Student ID (BruinCard)

To access the building on Saturday and Sunday you will need a BruinCard. It is best to apply online and submit your photo no later than August 31st, 2024 to ensure it is ready by orientation. Once you submit your photo, you will receive two emails, one indicating that your picture was received, and another email indicating whether your photo was approved or not. Please disregard the second email’s message about coming to the office to pick up your card. The MDSH program will pick up your BruinCard and have it available for you at the program orientation.

Title IX Training

Every UC graduate and professional student is required to complete sexual assault prevention training(s) each academic year as follows:

Each first-year graduate and professional student will be required to complete a 1-hour online training, from Vector LMS.
Each continuing graduate and professional student will only be required to complete a 1-hour online refresher training, from Vector LMS.

Vaccinations

Students are required to show proof of immunity against Measles, Mumps, Rubella, Varicella (Chicken Pox), Tdap (pertussis) and Meningitis ACYW (for those under the age of 21) and complete a screening questionnaire for Tuberculosis (TB).

The University of California allows for exemptions to these immunization requirements based only on a medical condition that is a contraindication to a vaccination. (See Medical Exception Request)
Covered individuals are required to submit documentation of either a COVID-19 vaccine or opt out by declining the vaccine on the Ashe Center Patient Portal

If you fail to complete these requirements by the first day of fall quarter, an enrollment hold will be placed and you will not be able to add/drop or register for classes.

Bruin Learn

FSPH uses the Canvas (Bruin Learn) educational platform. For Bruin Learn resources and a tutorial, visit here and scroll down to students.

Parking

The closest parking lot is parking structure 8. It is located at 555 Westwood Plaza Los Angeles, CA 90095. Discounted daily parking is available through the Bruin ePermit portal at a rate of $7/day (subject to availability). If unavailable, you can also purchase a daily permit at the parking pay station on the top floor or through the ParkMobile app at a rate of $16/day.

For more information, visit here under the tab “How to Pay”.

Housing

The department does not provide housing assistance. UCLA Housing has on campus living options and provides assistance in locating off campus housing. Please visit the website for more information about housing for graduate and professional students.

Course Description

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Public Health Foundation (4 units)
MDSH Core Courses (24 units)
MDSH Elective Courses (16 units)
MDSH Capstone (4 units)

The MDSH is a two-year, 48 unit program, consisting of public health foundation (4 units), MDSH core courses (24 units), MDSH electives (16 units), and a data science capstone course (4 units).

Public Health Foundation (4 units)

PUBHLT C201 Fundamentals of Public Health Exploration of foundations of public health by examining public health challenges at local, national, and global levels, and current strategies for advancing population health. Analysis of current public health issues and modern public health policies and practices.

MDSH Core Courses (24 units)

BIOSTAT 203A,B,C Introduction to Data Science The BIOSTAT 203 3-course sequence introduces practical data science (data ingestion, data cleaning, data wrangling, data visualization and reporting, databases) and big data computing (parallel, distributed, cluster and cloud computing) skills using computer languages R, Python, SAS, and SQL. Other topics include data ethics.
BIOSTAT 201A Introduction to Biostatistics Principles of biostatistics.
BIOSTAT 212A,B Statistical Learning The BIOSTAT 212 2-course sequence lays a rigorous foundation to commonly used data analytic tools for prediction, classification, and artificial intelligence (AI), with emphasis on applications to big and complex health data.

MDSH Elective Courses (16 units)

MDSH students take at least 4 elective courses from the following list.

BIOSTAT 218 Observational Health Data Science and Informatics An introduction to observational research in the health data sciences. Topics include disease cohort characterization, patient-level prediction and population-level estimation using administrative claims and electronic health records. Lectures will cover an introduction of observational health databases, a common data model for representing patient trajectories through healthcare systems, tools to manipulate data while preserving patient privacy theory of patient-level prediction and casual inference from observational data, and best practices for generating reproducible and reliable observational studies. Introductory theory will demonstrate how linear and generalized linear modeling is used in observational studies. Weekly practical laboratories will demonstrate the methods discussed in lecture. Laboratories will use SQL and R software, and regular homework assignments will re-enforce theoretical work with practical application using large-scale synthetic and real-world example databases. Students will design and complete a data analysis project that reflects the best practices covered in this course and translate their results into an oral presentation and written report.

BIOSTAT M215 Survival Analysis Data science methods for survival and life time data.
BIOSTAT 231 Statistical Power and Sample Size Methods for Health Research Sample size and power analysis methods for common study designs, including comparisons of means and proportions, ANOVA, time-to-event data, group sequential trials, linear regression, cluster randomized trials and multilevel data, with emphasis on designing randomized trials. Discussion also of multiple endpoints.
BIOSTAT M234 Applied Bayesian Inference Bayesian approach to statistical inference, with emphasis on biomedical applications and concepts rather than mathematical theory. Topics include large sample Bayes inference from likelihoods, noninformative and conjugate priors, empirical Bayes, Bayesian approaches to linear and nonlinear regression, model selection, Bayesian hypothesis testing, and numerical methods.
BIOSTAT M236 Longitudinal Data Analysis of continuous responses for which multivariate normal model may be assumed. Students learn how to think about longitudinal data, plot data, and how to specify mean and variance of longitudinal response. Advanced topics include introductions to clustered, multivariate, and discrete longitudinal data.

BIOSTAT 285 Advanced Topics. Machine Learning: Healthcare, Economics, and LLM This course provides an introduction to modern methods in health data science, focusing on the intersection of machine learning, game theory, and economic principles, particularly in the context of decision-making and interactions between multiple self-interested participants. Topics include advanced patient-level prediction, population-level estimation, and the application of large language models (LLMs) to healthcare data. Homework assignments will focus on applying theoretical concepts to practical scenarios. By the end of the course, students will design and complete a data analysis project that incorporates best practices in machine learning and healthcare, translating their results into both an oral presentation and a written report.
BIOSTAT 285 Advanced Topics. Deep learning: a statistical perspective The goal of this course is to study deep learning methodologies and identify related statistical issues. The content includes selected topics from the following: pre-deep-learning methods such as feature extraction and discrimination; components of well-established machine learning tools (support vector machines, reproducing kernel Hilbert spaces, model complexity, sparse models); history of neural networks; multi-layer-perceptron; backpropagation; convolutional neural networks; transformer networks; variational inference; generative adversarial networks; optimization and regularization; visualization; Python and deep learning frameworks.

MDSH Capstone (4 units)

BIOSTAT 401 Data Science Capstone A capstone project that consists of an original written analysis and an oral presentation that addresses an applied health-related data science topic and advances existing skills and techniques in healthcare or public health. Communication skills for professionals. Data ethics training.

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Cohort Learning
Class Schedule
- Two-Year Program Schedule
- Quarter Schedule

Cohort Learning

MDSH Students come with diverse academic and professional backgrounds, yet share a similar goal to gain data science skills and credentials that will enable them to expand their scope of professional expertise. This program’s executive-style schedule features the same curriculum that has made the UCLA Fielding School of Public Health an internationally recognized leader in public health, but in a format that recognizes the many priorities in a student’s life including family and career.

The program caters to working professionals by providing a convenient schedule of classes that introduces the principles, theories, and methods of health data science.

Through this highly cost-effective program, students are able to maintain their full-time working schedule and professional income. Combining in-class sessions and distance learning education, the 20-month program is intended to be fast-paced and demanding. The goal is to create a student-centered and supportive environment that produces unlimited opportunities for career success.

Students will start the program together and move through each quarter as a cohort. This gives students an opportunity to learn from each other and experience the various backgrounds and work experience that each student brings to the cohort.

Classes are held on campus only one weekend per month. The class schedule is given to all students in advance in order for them to plan around their career and family.

Class Schedule

The MDSH program caters to working professionals by providing a convenient schedule of classes. Through this highly cost-effective program, students are able to maintain their full-time working schedule and professional income. Combining in-class sessions and distance learning education, the 20-month program is intended to be fast-paced and demanding. The goal is to create a student-centered and supportive environment that produces unlimited opportunities for career success.

Two-Year Program Schedule

MDSH students typically take 2 courses per quarter and complete the program in 6 academic quarters (20 months).

Year	Fall Quarter	Winter Quarter	Spring Quarter
1	BIOSTAT 203A Data Management and Statistical Computing BIOSTAT 201A Introduction to Biostatistics	BIOSTAT 203B Data Science in R BIOSTAT 212A Statistical Learning	BIOSTAT 203C Data Science in Python BIOSTAT 212B Statistical Learning
2	PUBHLT C201 Public Health Elective 1	Elective 2 Elective 3	Elective 4 BIOSTAT 401 Capstone

Quarter Schedule

In each academic quarter with two courses, MDSH students take in-person classes on UCLA campus for three weekends and two online, synchronous sessions per week for seven weeks.