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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.

Pages

About me

Posts

Future Blog Post

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

blog

Why Urban Planning is Important to Me

Published:

This is an essay I wrote as part of my graduate applications on how I came to the realization that urban planning is one of the most impactful factors affecting our lives, and how it slips under our radars.

portfolio

publications

Digital Typhoon: Long-term Satellite Image Dataset for the Spatio-Temporal Modeling of Tropical Cyclones Permalink

NeuRIPS ’23 Dataset and Benchmarks Track, 2023

This paper presents the official release of the Digital Typhoon dataset, the longest typhoon satellite image dataset for 40+ years aimed at benchmarking machine learning models for long-term spatio-temporal data. To build the dataset, we developed a workflow to create an infrared typhoon-centered image for cropping using Lambert azimuthal equal-area projection referring to the best track data. We also address data quality issues such as inter-satellite calibration to create a homogeneous dataset. To take advantage of the dataset, we organized machine learning tasks by the types and targets of inference, with other tasks for meteorological analysis, societal impact, and climate change. The benchmarking results on the analysis, forecasting, and reanalysis for the intensity suggest that the dataset is challenging for recent deep learning models, due to many choices that affect the performance of various models. This dataset reduces the barrier for machine learning researchers to meet large-scale real-world events called tropical cyclones and develop machine learning models that may contribute to advancing scientific knowledge on tropical cyclones as well as solving societal and sustainability issues such as disaster reduction and climate change. The dataset is publicly available at this http URL and this https URL.

Download here

“Where Can I Park?” Understanding Human Perspectives and Scalably Detecting Disability Parking from Aerial Imagery

ASSETS ’25, 2025

Accessible parking is critical for people with disabilities (PwDs), allowing equitable access to destinations, independent mobility, and community participation. Despite mandates, there has been no large-scale investigation of the quality or allocation of disability parking in the US nor significant research on PwD perspectives and uses of disability parking. In this paper, we first present a semi-structured interview study with 11 PwDs to advance understanding of disability parking uses, concerns, and relevant technology tools. We find that PwDs often adapt to disability parking challenges according to their personal mobility needs and value reliable, real-time accessibility information. Informed by these findings, we then introduce a new deep learning pipeline, called AccessParkCV, and parking dataset for automatically detecting disability parking and inferring quality characteristics (e.g., width) from orthorectified aerial imagery. We achieve a micro-F1=0.89 and demonstrate how our pipeline can support new urban analytics and end-user tools. Together, we contribute new qualitative understandings of disability parking, a novel detection pipeline and open dataset, and design guidelines for future tools.

Download here

research

Isotope Decay at Rest Experiment (IsoDAR)

Published:

Developing a simulation code from the ground up for Radio Frequency Quadrupoles (RFQs). Designed to support existing simulation infrastructure, accurately simulate space-charge (interaction between charged particles), and parallelization. Faster and more scientifically accurate than existing alternatives!

Machine Learning for the Digital Typhoon Dataset

Published:

Preparing, publishing, and using the Digital Typhoon Dataset for machine learning. The dataset is the longest typhoon satellite image dataset available. We developed ways to interact with the dataset for ML, and performed benchmarks in analysis, reanalysis, and forecasting.

AccessParkCV: Understanding and Detecting Disability Parking

Published:

Accessible parking is critical for people with disabilities (PwDs). This work aims to understand how PwDs use disability parking, and develop a way to scalably detect and characterize (e.g., the width) disability parking in the built environment.

talks

teaching

Machine Structure and Assembly Language Programming, COMP40, Undergraduate TA

Undergraduate core course, Tufts University

Fall 2018, Fall 2019

TA for ∼120 students. Held weekly office hours; graded exams and assignments. Syllabus here (link may not be active at time of access).

Programming Languages, COMP105, Undergraduate TA

Undergraduate core course, Tufts University

Spring 2020

TA for ∼100 students. Graded exams and assignments. Held weekly office hours. Syllabus here.

Multimedia Systems Design, CSCI576, Graduate TA

Graduate course, University of Southern California

Fall 2022

TA for ~200 students. Held weekly office hours, wrote homework and exam questions. Graded assignments and exams. Syllabus here.

CSE160: Data Programming TA

Undergraduate course, University of Washington

Winter 2025

CSE160: Data Programming TA

Undergraduate course, University of Washington

Fall 2025