Curriculum vitae

Education

• Ph.D. in Computer Science, Artificial Intelligence
  • Graduated June 2020
  • University of California San Diego
  • Advisor: Kamalika Chaudhuri
• M.S. in Computer Science
  • Received 2016
  • University of California San Diego
• B.S. Mathematics, B.S. Computer Science
  • Graduated 2014
  • University of California Irvine

Work experience

• 2021 - Present: Data Scientist
  • Kaiser Permanente, Medical Informatics
  • Designing, training, and maintaining models.
  • Technologies used include the usual suspects of Python-based ML workflows.
  • Large-scale experience using TensorFlow and Apache Spark.
  • Example of a task: predicting ICD10 codes (diagnoses) from encounter data, and using historical data with an LSTM.
• 2019 - 2020: Associate-In (teaching a course) / Lecturer
  • University of California San Diego
  • Instructor Of Record
  • Taught upperdivision undergraduate courses, ranging from 40 to 100 students per section
  • Managed teams of 4 or more teaching assistants and tutors
• Summer 2018: AI Research Intern
  • Amazon
  • Location: Cambridge, UK
  • Supervisors: Borja Balle, Tom Diethe
  • Worked on projects exploring strong data processing inequalities for divergences.
• 2014 - 2020: Graduate Student Researcher, Teaching Assistant
  • University of California San Diego
  • Advisor: Kamalika Chaudhuri
  • Worked on various projects related to differential privacy, as an individual and as part of a team.

Skills

• Applied and Theoretical Machine Learning
  • Differential Privacy
  • Privacy Preserving Bayesian Data Analysis
  • Renyi Differential Privacy
  • Alternative Privacy Definitions
• Mathematics
  • Linear Algebra
  • Abstract Algebra
  • Real Analysis
  • Measure Theory
• Programming
  • C++
  • Python
  • NumPy, Pandas, Scikit, TensorFlow
  • R, MATLAB
  • Apache Spark
  • Linux Input Event Handling, Userspace Device Drivers
• Teaching
  • Effective Online Course Design
    • Canvas LMS, Blackboard LMS
    • Lecture Video Production
    • Formative and Summative Feedback
  • Universal Design for Learning

Publications

Sampling from Distributions under Differential Privacy Notions

Geumlek, J. D. (2020). Sampling from Distributions under Differential Privacy Notions. UC San Diego. ProQuest ID: Geumlek_ucsd_0033D_19410. Merritt ID: ark:/13030/m5p03hfr. Retrieved from https://escholarship.org/uc/item/1dt1m5v1

Privacy Amplification by Mixing and Diffusion Mechanisms

Balle, Borja, Gilles Barthe, Marco Gaboardi, and Joseph Geumlek (2019). "Privacy amplification by mixing and diffusion mechanisms." Advances in Neural Information Processing Systems,

Profile-based Privacy for Locally Private Computations

Geumlek, Joseph, and Kamalika Chaudhuri (2019). "Profile-based privacy for locally private computations." IEEE International Symposium on Information Theory

Rényi Differential Privacy Mechanisms for Posterior Sampling

Geumlek, Joseph, Shuang Song, and Kamalika Chaudhuri (2017). "Rényi differential privacy mechanisms for posterior sampling." Advances in Neural Information Processing Systems.

On the Theory and Practice of Privacy-preserving Bayesian Data Analysis

Foulds, James, Joseph Geumlek, Max Welling, and Kamalika Chaudhuri (2016). "On the theory and practice of privacy-preserving Bayesian data analysis." Conference on Uncertainty in Artificial Intelligence.

Contextual Point Matching for Video Stabilization

Meng, Ling Han, Joseph Geumlek, Holly Chu, Justin Hoogenstyrd, and Ernie Esser (2013). "Contextual point matching for video stabilization." SIAM Undergraduate Research Online. Volume 6.

Teaching Experience

CSE 150A Intro to Artificial Intelligence: Probabilistic Reasoning (Remote)

CSE 150A Intro to Artificial Intelligence: Probabilistic Reasoning

CSE 151A Intro to Artificial Intelligence: Statistical Approaches

Summer Graduate Teaching Scholarship / Intro to College Teaching

Awards and Distinctions

• Doctoral Award for Excellence in Teaching (UCSD CSE Department)
• Outstanding Senior in Mathematics (UCI Math Department)
• Howard Tucker Award (UCI Math Department)
• Campuswide Honors Program (UCI, now known as the Campuswide Honors Collegium)
• Honors in Mathematics (UCI Math Program)
• Summa Cum Laude (2014 UCI B.S. Mathematics)
• Magna Cum Laude (2014 UCI B.S. Computer Science)
• Phi Beta Kappa (Honor Society)