Jiawen Liu

Work Experience

Role: Lead Engineer / Architect (Level 18)
Duration: June 2023 – present (3 years)
Project 1 – DataAgent (Trustworthy AI Data Analysis Platform)
- Responsibilities: Overall system design, key technical breakthrough (POC) verification, project management, and team leadership.
- Key contributions: Built a code-based modeling platform that mitigates LLM hallucinations via formalizable data pipelines; enabled reliable AI‑driven data analytics for enterprise scenarios.
- Outcomes: 18 filed/granted patents (2023–2026) covering hallucination suppression, adaptive noise calibration, and verifiable data analysis.
Project 2 – OpenFuyao (Ascend NPU Ecosystem)
- Role: Co-lead of inference acceleration toolkit for LLMs on NPU.
- Contributions: Designed and optimized NPU‑aware operator libraries and memory scheduling; integrated the toolkit with mainstream LLM frameworks; achieved significant latency reduction for large‑scale deployment.
- Impact: Core contributor to Huawei’s Ascend computing ecosystem, enabling efficient LLM inference on domestic AI accelerators.

Program Analysis for Adaptive Data Analysis with Marco Gaboardi.
in Proceedings of the 44th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2023), Orlando, FL, USA. [PDF] [Github]

18 filed/published patents (as of 2026) in intelligent data analysis, LLM hallucination mitigation, code-based modeling, and NPU acceleration.

Short talk -- Type System in Adaptive Data Analysis -- EGLPLS 2019 (in Cornell University in Ithaca, NY, USA)[PDF]
Poster session -- Tailoring Differentially Private Bayesian Inference to Distance Between Distributions -- TPDP of CCS 2018 (in Toronto, Canada)[PDF]

POPL Jan. 15-21, 2023 (in Boston, Massachusetts, United States)
New England Programming Languages and Systems Symposium (NEPLS) Sep. 29, 2022 (in Harvard, Boston, Massachusetts, United States)
POPL Jan. 17-23, 2022 (in Philadelphia, Pennsylvania, United States)
PLWM@POPL Jan.18, 2021 (in Philadelphia, Pennsylvania, United States)
POPL Jan. 16-21, 2021 (online)
New England Systems Verification Day Oct.18, 2019 (in MIT, MA, USA)
POPL Jan. 13-19, 2019 (in Cascais, Portugal)
PLWM@POPL Jan.14, 2019 (in Cascais, Portugal)
OPLSS-- Foundations of Probabilistic Programming and Security -- Jun 17 - 29, 2019 (in University of Oregon, OR, USA)

Teaching Assistant for CS 320, Concepts of Programming Languages, 2019 Fall - Boston Univeristy course page
Teaching Assistant for CSE 305, Introduction to Programming Languages, 2019 Spring - Univeristy at Buffalo course page
Teaching Assistant for CSE 305, Introduction to Programming Languages, 2018 Fall - Univeristy at Buffalo course page
Teaching Assistant for CSE 305, Introduction to Programming Languages, 2018 Spring - Univeristy at Buffalo course page
Teaching Assistant for CSE 542, Software Engineer Concept, 2017 Fall - Univeristy at Buffalo course page

June 2023 – present, Huawei Technologies Co., Ltd. (Level 18) – Lead Engineer/Architect (DataAgent & OpenFuyao).
September 2019 – May 2023, Ph.D. in Computer Science, Boston University. Advisor: Marco Gaboardi. Thesis on program analysis for adaptive data analysis (PLDI 2023).
September 2017 – May 2019, Ph.D. student in Computer Science and Engineering, University at Buffalo, SUNY. Advisor: Marco Gaboardi.
September 2016 – June 2017, Intern, Institute of Information Engineering, Chinese Academy of Sciences.
September 2013 – June 2017, B.A. in Information Science, Central University of Finance and Economics, Beijing.
Born September 7, 1997 in China.

A programming language for adaptive data analysis based on probabilistic programs, using type information to guarantee confidence intervals on outputs. Github
An automatic formal verification tool for differentially private algorithms implemented in floating point computation. Github

An improved mechanism for Bayesian inference, calibrating noise to the sensitivity of a metric over distributions.Github