Deanna Needell

Current Students and Alumni

♦ Request letter of recommendation

♦ Undergraduate Advising Open Office Hours

    Current graduate students & postdocs

       













  • Zehan Chao, UCLA, PhD student, numerical linear algebra, machine learning
  • Jocelyn Chi, UCLA, NSF Postdoc, numerical linear algebra, statistical learning
  • Longxiu Huang, UCLA, CAM Postdoc, numerical linear algebra, learning, approximation
  • Ben Jarman, UCLA, PhD student, numerical linear algebra, machine learning
  • Halyun Jeong, UCLA, CAM Postdoc, signal processing, machine learning, nonlinear signal recovery
  • Shuang Li, UCLA, CAM Postdoc, signal processing
  • Xia Li, UCLA, PhD student, Distributed optimization
  • Michael Murray, UCLA, PIC Postdoc, machine learning, mathematical inference
  • Michael Perlmutter, UCLA, Hedrick Postdoc, signal processing, dimension reduction
  • Chris Strohmeier, UCLA, PhD student, Data completion and learning
  • Will Swartworth, UCLA, PhD student, stochastic iterative methods

    Alumni

          







  • Jamie Haddock (2021), UCLA, CAM Postdoc, optimization and learning (now at Harvey Mudd College)
  • Hanbaek Lyu (2021), UCLA, Hedrick Postdoc, dynamical systems, distributed algorithms, network data analysis (now at Univ. Wisconsin)
  • Jacob Moorman (2021), UCLA, Stochastic optimization and Graphical systems
  • Liza Rebrova (2021), UCLA, Postdoc, non-asymptotic random matrix theory (now at Princeton Univ.)
  • Palina Salanevich (2020), UCLA, Postdoc, phase retrieval and learning (now at Utrecht University)
  • Denali Molitor (2020), UCLA, Data analysis and learning (now at Google)
  • Anna Ma (2018), Claremont Graduate University, Topic modeling & compressed sensing (now UC Chancellors postdoc fellow at UC Irvine)
  • Dr. Tina Woolf (2017), Claremont Graduate University, Practical Compressed Sensing (now at JPL)
  • Guangliang Chen (2015), postdoctoral researcher (now at San Jose State)
  • Ran Zhao (2015), Claremont Graduate University, Stochastic optimization (now at AIG)

Summer Research

  • 2021 Research Experience for Undergraduates (REU), Applied Mathematics, UCLA
    Data Science for Innocence









    Team (mentors: Joyce Chew, Longxiu Huang (lead), Ben Jarman)
    • Pengyu Li
    • Imani Maliti
    • Christine Tseng
    • Yaxuan Zheng

  • 2020 Research Experience for Undergraduates (REU), Applied Mathematics, UCLA
    Data Science for Innocence









    Team (mentors: Denali Molitor, Liza Rebrova)
    • Ryan Budahazy
    • Lu Cheng
    • Andrew Johnson
    • Josh Vendrow
    • Diana Wu

  • 2019 Research Experience for Undergraduates (REU), Applied Mathematics, UCLA
    Topic-aware Chatbot








    Team (mentor: Hanbaek Lyu)
    • Yuchen Guo
    • Nicholas Hanoian
    • Zhexiao Lin
    • Nicholas Liskij
    • Jiahao Qu
    • Henry Sojico
    • Yuliang Wang
    • Zhe Xiong
    • Zhenhong Zou

  • 2018 Research Experience for Undergraduates (REU), Applied Mathematics, UCLA
    Patterns of Lyme Disease










    Data Completion Team
    • Matthew Patterson, Pomona College
    • Sneha Sambandam, UCLA
    • Joy Song, Tsinghua Univ.
    • Yuanxun Sun, Peking Univ.


    Deep Models Team
    • Mengdi Gao, UC Irvine
    • Eli Sadovnik, UCLA
    • Tyler Will, Michigan State
    • Runyu Zhang, Peking Univ.


    Classification Team
    • Eric Chen, UCLA
    • Rong Huang, UCLA
    • Diyi Liu, Shanhai Jiao Tong Univ.
    • Cathy Wahlenmayer, Gannon Univ.
    • Jiewen Wang, UCLA


    Co-mentors
    • Jamie Haddock, UCLA
    • Denali Molitor, UCLA
    • Anna Ma, UC San Diego

  • 2017 Research Experience for Undergraduates (REU), Applied Mathematics, UCLA
    Data Science meets Lyme Disease Data
    • Allyson Cruz, Claremont McKenna College
    • Anna Ma (co-mentor), Claremont Graduate University
    • Kevin Stangl, UCLA

  • 2015 Research Experience for Undergraduates (REU), Applied Mathematics, UCLA
    Practical Compressive Signal Processing









    • Mindy Case, UCLA
    • Xiaoyi Gu (NSF RA), UCLA
    • Hao-Jun Michael Shi, UCLA
    • Shenyingying Tu (NSF RA), UCLA

  • 2015 Research Experience for Undergraduates (REU), Applied Mathematics, UCLA
    Longitudonal MRI and compressed sensing









    • Samuel Birns, UCLA
    • Bohyun Kim, UC Irvine
    • Stephanie Ku, UCLA
    • Kevin Stangl, UCLA

  • 2014 Research Experience for Undergraduates (REU), Applied Mathematics, UCLA
    Practical Compressive Signal Processing










    • Christopher Garnatz, Pomona College
    • Xiaoyi Gu (NSF RA), UCLA
    • Alison Kingman, Harvey Mudd College
    • James LaManna, Pitzer College
    • Shenyingying Tu (NSF RA), UCLA

  • 2014 Research Experience for Undergraduates (REU), Applied Mathematics, UCLA
    Analysis of Neuroscience Data









    • Arpineh Asadoorian, UCLA
    • Christian Ayala, Claremont McKenna College
    • Jessica Nadalin, UC Berkeley
    • Ryan McCarthy (RA), UCLA
    • Susannah Shoemaker, Pomona College

  • 2014 Summer Graduate Research Program, Claremont McKenna College
    Practical Compressive Signal Processing
    • Flora Xu Shu Jing (NSF RA), Claremont Graduate University
    • Tina Woolf (NSF RA), Claremont Graduate University
    • Ran Zhao (NSF RA), Claremont Graduate University

  • 2012 Research in Industrial Projects for Students (RIPS), Institute of Pure and Applied Mathematics, UCLA
    Spectral Clustering and the Attrition Problem









    • Bianca Cung, UCLA
    • Tony Jin, Stanford
    • Juan Carlos Ramirez, Univ. of Mexico
    • Aubrey Thompson (project manager), Univ. of Nebraska

  • 2010 VIGRE VPUE Undergraduate Summer Workshop, Stanford
    Robust Principal Component Analysis
    • Michael Hornstein, Stanford

      Past thesis students

            







            







    • Matthew Aven, Claremont McKenna College (2017), Daily Traffic Flow Pattern Recognition by Spectral Clustering
    • Wei Wu, Scripps College (2017), Paving the Randomized Gauss-Seidel Method
    • Dejun Wan, Claremont McKenna College (2016), The Randomized Kaczmarz Method with Application on Making Macroeconomic Predictions
    • Phillip North, Claremont McKenna College (2015), One-bit compressed sensing with prior information [Best Thesis Award 2015]
    • Jonathon Briskman, Claremont McKenna College, Block Kaczmarz Method with Inequalities
    • Evan Casey, Claremont McKenna College, Scalable Collaborative Filtering Recommendation Algorithms on Apache Spark [Outstanding Thesis Award 2014]
    • Nathan Falk, Claremont McKenna College, Policy Uncertainty and Irreversible Investment in the United States
    • Aparna Sarkar, Pomona College, Compressed Sensing and Human Vision
    • Zachary Siegel, Pomona College, Generative Models and Sparse Coding
    • Nathan Lenssen, Claremont McKenna College (2013), Audio Signal Processing and Forecasting [Best Thesis Award 2013]
    • Morgan Mayer-Jochimsen, Scripps College (2013), Public Healthcare Evaluation Techniques
    • Jing Wen, Pomona College (2013), Spectral Clustering Methods in Finance
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