Quantitative Researcher 2023-
Two Sigma InvestmentsQuantitative Research leveraging machine learning.
Hi my name is Jùnchéng (Billy) Lì. 励骏成 I
got my PhD in 2023 from CMU LTI after coming back to CMU at fall 2019. Before this, I spent 4
wonderful years at Bosch Center for Artificial Intelligence.
In total, I have
spent nearly 8 years on topics related to deep learning. I have worked on Deep
Learning's applications in audio and multi-modal data. Recently, I have
worked on
understanding deep learning's vulnerabilities and robustness.
I have always been fascinated by the magical effects of deep neural
networks, meanwhile, the unexplainable behaviors of the neural nets kept
haunting me.
In my research careers, I have been influenced by various beliefs:
"Deep learning is the dark side, and convex optimization is the true
justice."
"We have been wasting so much time building symbolic knowledge-based
systems, and history proved that Alpha-zero and BERT are the only real
things that worked."
"Human knowledge is the corner stone of AI, the only valid path to building
AI is by teaching machines to think like humans."
.......
It is very tempting for young research Jedis to fall believing in any of
these "dogmas" since they are all very seductive to a certain group of
people
with specific background.
However, I believe there's a fine balance, a bridge that goes between all
the communities: the ML community, the theory community, the NLP commmunity
and the speech community...
My goal is to build part of that bridge between the gap between theory and
application during my PhD.
I am convinced that good research is not necessarily impactful,
but impactful researches are usually dependent on excellent taste of
topic,
significant effort, bullet-proof writing, and necessary PR.
As I grow more experienced, I also think research itself greatly
resembles
value investing. Not only do we need to diversify our portfolio,
we also need to put enough concentration in topics with growth. We don't
have
unlimited time and resources to spend, but we need to be patient and
confident
about whatever we chose to invest in. This process requires tremendous
tenacity and a stable mindset to be able to stomach the up and downs.
Never be arrogant, or you will get taught a lesson very soon!
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
2008-2012
Quantitative Research leveraging machine learning.
Officially returned to CMU, joined LTI in SCS. Focus on research on deep learning on audio and multimedia data. TA for 11-751 Speech Recognition; TA for 15-640 Distributed Systems.
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.
Developed an audio analytic platform for infrastructure monitoring and machinery monitoring using machine learning /deep learning techniques.
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.
Assist with the management of over 120 projects, total value over 2.5 million dollars. Coordination, BIM and database programming skills intensively involved.
I have been coding ML and general software projects in the past 6 years.
Everything I learned about Machine Learning (Updating)
Interesting things I learned about Linear Algebra (Updating)
Will be presenting AudioJourney joint work with Jackson Michaels.
Will be presenting AudioMAE joint work with Bernie Huang at Meta.
Our paper won the Best Student Paper Award ! Here's the video of our presentation.
Tutorial on Robust Audio
Reviewer for NeurIPS, ICML, ICLR, AAAI, EMNLP, CVPR, IEEE TNNLS, TALLIP,
This piece of music could stop Amazon Alexa from working --NewScientist
Video Presented at ICML 2019 about the adversarial camera sticker
Presented two pieces of work: Environment Sound Classification and VGG for Sound