• Welcome!
    This is Jùnchéng (Billy) Lì

    Quantitative Researcher at TwoSigma

    Download CV

  • I am a
    Researcher

    I have worked on Machine Learning in Audio and Multimodal dataset

    Google Sholar

About Me

What is my Story?

Hi my name is Jùnchéng (Billy) Lì. 励骏成 I am currently a quantitative researcher at Two Sigma. I obtained my PhD in 2023 from CMU LTI. Before that, I spent four wonderful years at Bosch Center for Artificial Intelligence. In total, I have spent nearly ten years working on deep learning and its applications in audio, speech, and multimodal data, with a recurring focus on robustness and failure modes.
I have always been fascinated by the power of machine learning, and at the same time haunted by how much of it can remain opaque even when it works. In the era of LLMs and modern AI systems, I choose to embrace this shift and fully take advantage of what these models can do. To me, the right response is neither blind worship nor reflexive skepticism, but learning quickly, adapting continuously, and staying open-minded as the frontier moves.
Over time, I have also come to believe that research greatly resembles value investing. We need to keep learning new things, diversify enough to stay resilient, and yet concentrate when we see a direction with real long-term potential. We do not have unlimited time or attention, so where we place our effort matters. This process requires patience, conviction, and the ability to revise our views when the world changes.
At the end of the day, I believe the most important things are intuition and taste: taste in choosing problems, taste in knowing what matters, and intuition for when a new idea, tool, or direction is worth taking seriously. Those qualities are hard to fake, and they become more valuable as the field moves faster.

LLM Post-Training

Robust Deep Learning

Multimodal Machine Learning

Audio/Speech Processing

My Work

Recent Work

Towards Robust Large-scale audio/visual learning

Committee Members: Florian Metze (CMU, Meta), Shinji Watanabe (CMU), Emma Strubell (CMU), Daniel P Ellis (Google)

Towards Robust Large-scale audio/visual learning

Committee Members: Florian Metze (CMU, Meta), Shinji Watanabe (CMU), Emma Strubell (CMU), Daniel P Ellis (Google)

Audio Tagging Done Right

See the state-of-the-art of Audio Event Detection

100

On Adversarial Robustness of Large-scale Audio Visual Learning

Click the link below to check out the paper

Adversarial Music

Click the link below to check out the paper

100

Adversarial Camera Sticker

Click the links below to check out the related resources

A Comparison of Five Multiple Instance Learning Pooling Functions for Sound Event Detection with Weak Labeling

This work was collaboration with Yun Wang (Maigo), and it later became part of his thesis work. Check out the resources below:

Revisiting Disentanglement in VAE

Click to see our paper discussion.

times cited
publications
best paper award
press coverage
Education

Education

Carnegie Mellon University
School of Computer Science
Language Technology Institute

2019-2023

Carnegie Mellon University
School of Computer Science
Language Technology Institute

2017-2019

Carnegie Mellon University College of Engineering

2012-2014

Carnegie Mellon University College of Engineering

2012-2014

Tongji University Image

2008-2012

Experience

Work Experience

Quantitative Researcher 2023-

Two Sigma Investments Image

Quantitative Research leveraging machine learning.
- Post-training of LLMs to predict market behavior and extract useful trading signals.
- Deep learning applications for market prediction across financial data and related forecasting problems.

Deep Learning Research Engineer 2018-2019

Bosch Center for Artificial Intelligence Image

Built up my theoretical background, trying to look at ML from a different angle.
- Applied robust machine learning algorithms to Bosch Autonomous driving project, improved system robustness by 50% in bad weather condition.
- Explored mulimodality embeddings to make use of multi-sensor input, trans- ferred the technology to Bosch business team.
- Developed occupancy detection solution using RGB-D sensor, and facilitated the transfer of technology to business unit.
- Applied representation learning to Bosch drier, improved energy efficiency by 5%.
- Generated 2 patents and top-tier AI conference publications.
- Mentored 2 interns and hired 5 members for the new team.

Research Intern 2014-2014

Pittsburgh Port Authority

Build website and manage database to visualize transportation data of Pittsburgh city( Recent 2 years), and analyze the data to provide optimization solutions to improve the current resource allocation.

My Specialty

My Skills

I have been coding ML and general software projects in the past 6 years.

Python

95%

Java

50%

HTML5/CSS

85%

C/C++

45%

MatLab

70%

Go

50%
Read

Recent Blog

HTML5 Bootstrap Template by colorlib.com
Mar 25, 2026 | AI |

LLM Notes

How I think about LLMs, systems, and judgment in the current AI era.

HTML5 Bootstrap Template by colorlib.com
Feb 18, 2022 | ML Blog |

Machine Learning Pointers

Everything I learned about Machine Learning (Updating)

HTML5 Bootstrap Template by colorlib.com
April 30, 2021 | Algorithm | 4

Coding Interviews

Going back to the basics (Updating)

HTML5 Bootstrap Template by colorlib.com
Aug 31, 2021 | Statistics | 4

Theory NoteBook

To Strenghthen my Theoretical Foundation (Updating)

HTML5 Bootstrap Template by colorlib.com
Feb 21, 2022 | LinearAlgebra | 4

Linear Algebra

Interesting things I learned about Linear Algebra (Updating)

What's New?

Here are some of my recent updates

ICLR 2025

Will be presenting SMT joint work with Hector He.

ICML 2023 ES-FoMo,
ICASSP 2024

Will be presenting AudioJourney joint work with Jackson Michaels.

NeurIPS 2022

Will be presenting AudioMAE joint work with Bernie Huang at Meta.

ICASSP 2022

Our paper won the Best Student Paper Award ! Here's the video of our presentation.

Academic Paper Review

Reviewer for NeurIPS, ICML, ICLR, AAAI, EMNLP, CVPR, IEEE TNNLS, TALLIP,

NeurIPS 2019 (Vancouver, BC)

This piece of music could stop Amazon Alexa from working --NewScientist

ISCSLP 2021 Tutorial

Tutorial on Robust Audio

ICML 2019 (Long Beach, CA)

Video Presented at ICML 2019 about the adversarial camera sticker

ICASSP 2019 (Brighton, UK)

Slides Presented "A Comparison of Five Multiple Instance Learning Pooling Functions for Sound Event Detection with Weak Labeling"

ICMR 2018 (Yokohama, Japan) Best Paper Award

Our paper won the Best Paper Award

ICASSP 2017 (New Orleans)

Presented two pieces of work: Environment Sound Classification and VGG for Sound

Get in Touch

Contact

100 6th Ave 11th floor, New York