Research

Models, measurement,
and what follows.

I’m interested in reliable machine learning: how evaluation choices, incomplete data, and uncertainty affect what a result can support.

Reliable machine learning
Evaluation & uncertainty
Measurement & evidence

View CV ↗Publications ↓

01 / Publication

Collaborative work.

Conference paper · 2024 · Coauthor

Intelligent vehicle classification system based on deep learning and multisensor fusion

Xinjin Li, Yuanzhe Yang, Yixiao Yuan, Yu Ma, Yangchen Huang, Haowei Ni

Fifth International Conference on Computer Vision and Data Mining (ICCVDM 2024)

A collaborative study of vehicle classification using deep learning and multisensor fusion.

Published paper ↗Read preprint ↗

02 / Experience

Where the questions started.

Research project

2024–2025

Demand & energy forecasting

Forecasting and modeling explorations focused on what can be inferred from incomplete data and how uncertainty affects interpretation.

Forecasting
Model evaluation
Incomplete data

Research project

2023–2024

Measuring change with satellite observations

Work with nighttime lights and vegetation indices as evidence of change, examining the gap between a measured signal and the conditions it represents.

Remote sensing
VIIRS nighttime lights
Measurement

Read the research reflection ↗

03 / Related writing

Questions I’m working through.

Notes on reading and interpreting research.

What does a benchmark score support?

Thinking through populations, metrics, stability, and the cost of an improvement.

Read essay ↗

How I read a paper

Following the claim, the comparison, and the limits of the evidence.

Read essay ↗