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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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I am a third year PhD student studying applied mathematics at UCLA.
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Journal of Chemometrics, 2019
Recommended citation: Kazmierczak, N.P.; Chew, J.A.; Michmerhuizen, A.R.; Kim, S.E.; Drees, Z.D.; Rylaarsdam, A.; Thong, T.; Van Laar, L.; Vander Griend, D.A. Sensitivity Limits for Determining 1:1 Binding Constants from Spectrophotometric Titrations via Global Analysis. Journal of Chemometrics, 2019, 33:e3119. Online access
Algorithms, 2022
Recommended citation: Li, P.; Tseng, C.; Zheng, Y.; Chew, J.A.; Huang, L.; Jarman, B.; Needell, D. Guided Semi-Supervised Non-Negative Matrix Factorization. Algorithms 2022, 15:136 Online access
Journal of Chemometrics, 2022
Recommended citation: Kazmierczak, N.P.; Chew, J.A.; Vander Griend, D.A. A reliable algorithm for calculating stoichiometry parameters in the hard modeling of spectrophotometric titration data. Journal of Chemometrics, 2022, 36:e3409. Online access
ICML Workshop on Topology, Algebra, and Geometry in Machine Learning, 2022
Recommended citation: Chew, J.A.; Steach, H.R.; Viswanath, S.; Wu, H.-T.; Hirn, M.; Needell, D.; Krishnaswamy, S.; Perlmutter, M. The Manifold Scattering Transform for High-Dimensional Point Cloud Data. arXiv preprint, 2022. Online access
arXiv preprint, 2022
Recommended citation: Chew, J.A.; Hirn, M.; Krishnaswamy, S.; Needell, D.; Perlmutter, M.; Steach, H.R.; Viswanath, S.; Wu, H.-T. Geometric Scattering on Measure Spaces. Submitted for publication, 2022. Online access
Analytica Chimica Acta, 2022
Recommended citation: Kazmierczak, N.P.; Chew, J.A.; Vander Griend, D.A. Bootstrap methods for quantifying the uncertainty of binding constants in the hard modeling of spectrophotometric titration data. Analytica Chimica Acta, 2022, 1227:339834. Online access
arXiv preprint, 2022
Recommended citation: Cheng, K; Inzer, S.; Leung, A.; Shen, X.; Perlmutter, M.; Lindstrom, M.; Chew, J.A.; Presner, T.; Needell, D. Multi-scale Hybridized Topic Modeling: A Pipeline for Analyzing Unstructured Text Datasets using Topic Modeling. Submitted for publication, 2022. Online access
arXiv preprint, 2022
Recommended citation: Chew, J.A.; Perlmutter, M.; Needell, D. A Convergence Rate for Manifold Neural Networks. arXiv preprint, 2022. Online access
One of the most important parts of applying to graduate school is identifying why you want to apply. What areas of mathematics interest you? Why go on to grad school instead of applying for a job elsewhere?
Since I was applying for the NSF GRFP, which was due in mid-October, I prepared my GRFP application first, then modified it for my graduate school applications. This was extraordinarily helpful for me, since it meant that the bulk of my graduate school applications were essentially finished by mid-October.
I found forums such as GradCafe very unhelpful in many respects, including actually putting together my applications and my mental health.
In August before my senior year, I put together a spreadsheet with all the programs I was interested in, application fees, deadlines, links to the program website and application portal, whether or not the program required the GRE (general or subject), how many recommendation letters were required, and the names of 3-5 faculty I was interested in working for. Looking for faculty in this way helped narrow down my list.
For me, the most important part of preparing to write my application was carefully reading the entire solicitation for the NSF GRFP that year. In my drafts for my personal statement and research statement, I kept key phrases and directions from the solicitation to make sure I was on track.
When writing the personal statement, the key for me was identifying the story I wanted to tell about my career. How did all of my past experiences move me towards what I wanted to do in graduate school and beyond? This was the question I sought to answer in all sections of this statement.
When writing the research statement, I drew heavily upon the REU I participated in during the summer before my senior year. While I think it is true that the NSF “funds the person, not the project”, it’s important to propose a project that is:
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Undergraduate course, UCLA, Fall 2021, Winter 2022, Spring 2022
Undergraduate course, UCLA, Winter 2022
Undergraduate course, UCLA, Fall 2021, Spring 2022
Undergraduate course, UCLA, Fall 2021
Undergraduate course, UCLA, Fall 2021