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Alisa Liu

University of Washington

Hi! I am currently a research intern on the MOSAIC team at Allen Institute for AI. I graduated this Spring from Northwestern University with majors in computer science and math. There, I was super fortunate to work in the fields of natural language processing and computer audition with Professor Doug Downey, Professor Bryan Pardo, and Dr. Prem Seetharaman, who have been the kindest of mentors and deeply formative to my intellectual interests.

I am super excited to join the University of Washington in Fall 2020 as a PhD student in the CSE department.

Interests

  • Natural language processing
  • Machine learning
  • Machine processing of music and audio

Education

  • PhD candidate, 2020 - present

    University of Washington

  • BA in Computer Science, Mathematics, 2020

    Northwestern University

Publications

Incorporating Music Knowledge in Continual Dataset Augmentation for Music Generation

A generative data augmentation method for music generation systems on a resource-constrained domain
Alisa Liu, Alex Fang, Gaëtan Hadjeres, Prem Seetharaman, Bryan Pardo
PDF Code

Bach or Mock? A Grading Function for Chorales in the Style of J.S. Bach

An automatic, interpretable, and musically-motivated grading function for Bach chorales
Alex Fang, Alisa Liu, Prem Seetharaman, Bryan Pardo
PDF Code

Model Selection for Deep Audio Source Separation via Clustering Analysis

Ensemble model for audio source separation, using a confidence measure to mediate among domain-specific models
Alisa Liu, Prem Seetharaman, Bryan Pardo
PDF

Multi-sense Definition Modeling using Word Sense Decompositions

Definition generation for multiple senses of a word
Ruimin Zhu, Thanapon Noraset, Alisa Liu, Wenxin Jiang, Doug Downey
PDF

CODAH: An Adversarially Authored Question-Answer Dataset for Common Sense

An adversarially-constructed dataset for common sense QA, collected from Northwestern ML students!
Michael Chen, Mike D’arcy, Alisa Liu, Jared Fernandez, Doug Downey
PDF Code Poster
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Teaching

CS 336: Design & Analysis of Algorithms

peer mentor, with Professor Jason Hartline (Fall 2019)

EECS 349: Machine Learning

peer mentor, with Professor Bryan Pardo (Spring 2019)

EECS 396/496: Statistical Machine Learning

course developer, with Professor Han Liu (Winter 2019)

CPSC 121: Models of Computation

undergraduate TA, with Professors Alice Gao, Steve Wolfman, Ryan Vogt (Term 2 2018)

Posts

Some study guides I've made

I really enjoy making study guides! Here are a couple I'm especially proud of, and I hope they are useful resources for other students. …
Last updated on 12/26/19 1 min read