Jiachen Lian (连甲琛)

I am a PhD candidate in Berkeley EECS, affiliated with Berkeley Artificial Intelligence Research (BAIR), where I am advised by Prof. Gopala Krishna Anumanchipalli. I also collaborate closely with Prof. Maria Luisa Gorno-Tempini on precision healthcare for speech and language, and with Prof. Shankar Sastry on control theory, dynamics, and internal-model representations in AI foundation models. My work is supported by the Meta AI Mentorship (AIM) Program over two years, through which I have worked with Wei-Ning Hsu and Abdelrahman Mohamed.

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Updates

• Twice a year, we host the Bay Area Speech AI for Health, Education, and HCI Workshop, convening leaders from academia, industry, venture capital, healthcare, and education. Our goal is to shape the future of human-centered speech intelligence — connecting fundamental research with real-world systems and societal impact. We welcome researchers, practitioners, founders, and investors to join, present, or collaborate. Please feel free to contact me. https://sites.google.com/berkeley.edu/bair-speech-ai-workshop

Research

I'm interested in research questions that will still matter five years from now.

I build interpretable, human-centered foundation models — and the systems and robots that bring them into the real world.

(1) Interpretable-by-design, mechanistically grounded foundation models
I develop foundation models whose internal representations are structured and inspectable, and whose reasoning, planning, and dynamics can be examined and controlled.

(2) Human-centered speech AI systems
I build speech AI that is grounded in human cognition and physiology (perception, production, physics) and that keeps people in the loop through interactive labeling, feedback, and supervision.

(3) Controllable robots and inverse problems
I work toward robots whose actions we can steer, predict, and understand.

(4) Human-AI collaboration and deployment in high-stakes healthcare settings
I build collaborative, deployed systems for precision and public health — speech and language disorders such as dyslexia and primary progressive aphasia, and population-level language screening.

Essay

Why do so few scientists make significant contributions and so many are forgotten in the long run [1]?
[1] https://www.cs.virginia.edu/~robins/YouAndYourResearch.pdf

News

Starting from 2025, as approved by the California State Government, public schools will adopt our language screener, where I developed the first and state-of-the-art speech dysfluency transcriber [UDM][SSDM], serving 1 million kids! See reports.


Selected Publications
Automated Lexical Dysfluency Analysis to Differentiate Primary Progressive Aphasia Variants
Jet M.J. Vonk* (co-first), Jiachen Lian* (co-first), Zoe Ezzes, Lisa Wauters, Cheol Jun Cho, Brittany T. Morin, Rian Bogley, Diana Rodriguez, Boon Lead Tee, Jessica DeLeon, Zachary Miller , Maria Luisa Mandelli, Gopala Krishna Anumanchipalli* (co-last), Maria Luisa Gorno-Tempini* (co-last)
AAIC (Alzheimer's Association International Conference) 2025 (Oral Presentation). AI models assist doctors in diagnosing speech language disorders with high clinical alignment
Automatic Detection of Articulatory-Based Disfluencies in Primary Progressive Aphasia
Jiachen Lian, Xuanru Zhou, Chenxu Guo, Zongli Ye, Zoe Ezzes, Jet Vonk, Brittany Morin, David Baquirin, Zachary Miller, Maria Luisa Gorno Tempini and Gopala Krishna Anumanchipalli,
2025 JSTSP An efficient AI Agent for Language Screening and Spoken Language Learning.
[Project Page]
SSDM: Scalable Speech Dysfluency Modeling
Jiachen Lian, Xuanru Zhou, Zoe Ezzes, Jet Vonk, Brittany Morin, David Baquirin, Zachary Miller, Maria Luisa Gorno Tempini and Gopala Krishna Anumanchipalli,
2024 NeurIPS. An AI Agent for Speech Therapy and Spoken Language Learning. A foundation model for scientific research, engineering deployment and business development .
[Project Page] ( NeurIPs Scholar Award )
Unconstrained Dysfluency Modeling for Dysfluent Speech Transcription and Detection
Jiachen Lian, Carly Feng, Naasir Farooqi, Steve Li, Anshul Kashyap, Cheol Jun Cho, Peter Wu, Robbie Netzorg, Tingle Li, and Gopala Krishna Anumanchipalli,
2023 ASRU (Best Paper Nomination ). First work to detect both type and time of dys(dis)fluencies.
2024 Sevin Rosen Funds Award


Industrial
Meta AI, CA, USA
Visiting Researcher • Sep 2024 to Now
With: Abdelrahman Mohamed
Meta AI, CA, USA
FAIR-BAIR Student Researcher • Oct 2023 to May 2024
With: Wei-Ning Hsu
Meta AI, CA, USA
Research Intern • May 2022 to Dec. 2022
With: Alexei Baevski, Wei-Ning Hsu, Michael Auli
Speech and NLP Group, Tencent AI Lab(American) , WA, USA
Research Intern • April 2021 to May 2022
With: Chunlei Zhang, Dong Yu
Teaching
Introduction to Robotics, Berkeley EECS , CA, USA
Reader • Fall 2024
Lab GSI.
Instructor: Prof. Roberto Horowitz
Audio Signal Processing in Humans and Machines, Berkeley EECS , CA, USA
Reader • Fall 2022
Instructor: Prof. Gopala Krishna Anumanchipalli
Introduction to Deep Learning, CMU LTI , PA, USA
Teaching Assistant • Fall 2020
Instructor: Prof. Bhiksha Raj
Education
UC Berkeley, U.S.
Ph.D. in EECS • Aug. 2021 to Present
Carnegie Mellon University, U.S.
M.S. in ECE • Sept.2019 to Dec. 2020
Zhejiang University, China
B.Eng. in EE • Aug. 2015 to June 2019

Awards
2025 Radical Ventures AI Founders Grant ($350K)
2025 ASRU AI4CSL Best Paper
2024 Meta AI Mentorship (AIM) Program — 2-Year PhD Funding
2024 NeurIPS Scholar Award
2024 Sevin Rosen Funds Award
2023 ASRU Best Paper Nomination
2021 Berkeley Golden Fellowship