cv

Please see pdf for more details.

Basics

Name Prateek Anand
Role Computer Science Ph.D. Student
Email panand2@g.ucla.edu
Phone (408) 431-1325
Homepage https://prateekanand2.github.io/
Summary My research interests are in developing novel AI/ML computational methods. I am invested in deep learning, traditional machine learning, and statistical approaches that are scalable and interpretable. Recently, I have been focused on deep generative models for genetic variation data. I have also started exploring discrete diffusion and masked language modeling approaches for rare feature imputation.

Education

  • 2024 - 2029

    Los Angeles, CA

    Ph.D.
    UCLA
    Computer Science
    • Major Field: Artifial Intelligence
    • Minor Fields: Data Science Computing and Computational Systems Biology
  • 2020 - 2024

    Los Angeles, CA

    B.S.
    UCLA
    Computer Science

Experience

  • 06/2022 - Present
    Graduate Student Researcher
    UCLA Computer Science | Sriram Lab
    Currently building deep generative models for genetic variation data and imputation.
    • Developed scalable machine learning/statistical software for human genetics
    • Research Intern: Bruins in Genomics Research Program (06/2022 - 08/2022)
  • 06/2023 - 01/2024
    Research Intern
    Stanford University School of Medicine | Curtis Lab
    Early detection of blood cancer through computational modeling and inference.
    • Canary CREST Research Program for Early Cancer Detection (06/2023 - 09/2023)
  • 01/2021 - 04/2022
    Research Assistant
    UCLA Jonsson Comprehensive Cancer Center | Boutros Lab
    Pipeline development for quantifying/locating copy-number aberrations in human cancer samples.

Publications

Presentations

Teaching

Skills

Programming languages
Python
C++
Frameworks
Scikit-learn
PyTorch
Numpy
Pandas
Git
Courses
Machine Learning
Artificial Intelligence
Neural Networks and Deep Learning
Big Data Analytics
Software Engineering and Construction
Data Structures
Algorithms and Complexity
Linear Algebra
Statistics and Probability
Optimization
Machine Learning in Genetics
Algorithms in Bioinformatics
Other
Generative Models
Probabilistic Models
Hypothesis Testing
Cluster Computing

Awards