Page Not Found
Page not found. Your pixels are in another canvas.
Sitemap
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
Page not in menu
This is a page not in th emain menu
Posts
Future Blog Post
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
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
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
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
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
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
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
“Does the cafe entrance look accessible? Where is the door?” Towards Geospatial AI Agents for Visual Inquiries
ICCV ’25 Workshop Extended Abstracts, 2025
Download here
RAMPNET: A Two-Stage Pipeline for Bootstrapping Curb Ramp Detection in Streetscape Images from Open Government Metadata
ICCV ’25 Workshop, 2025
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 on Liquid Argon Time Projection Chamber (LArTPC) images
Published:
Building tools with ML for analyzing neutrino detector images from a Liquid Argon Time Projection Chamber. Using a VQVAE to compress large image files, and performing instance segmentation on the LArTPC images to extract neutrino trails.
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
Machine Learning for the Digital Typhoon Dataset
Published:
Discussing approaches, tasks, and challenges to using machine learning with the Digital Typhoon Dataset. Flyer here.
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