About

Professor Ju Li is the Carl Richard Soderberg Professor in Power Engineering and a Professor of Materials Science and Engineering at MIT. His research group investigates the mechanical, electrochemical, and transport behaviors of materials, focusing on novel means of energy storage and conversion. His work has led to advances in materials with applications in nuclear energy, batteries, and electrolyzers, contributing to the efforts to decarbonize the planet. Additionally, his group works on various aspects of computing, including the development of the first universal neural network interatomic potential, analog neuromorphic computing hardware, and quantum information processing. Professor Li earned a BS in physics from the University of Science and Technology of China in 1994 and a PhD in nuclear engineering from MIT in 2000. Before joining MIT's Department of Materials Science and Engineering as a faculty member in 2011, he spent nine years at Ohio State University and the University of Pennsylvania. He is the chief organizer of the MIT A+B Applied Energy Symposia, which aims to develop solutions to global climate change challenges. His contributions include developing programmable resistors for deep learning, creating rechargeable fiber batteries for wearable electronics, and advancing materials science with a focus on energy and sustainability.

Research topics

• Materials science
• Chemistry
• Computer Science
• Physics
• Nanotechnology
• Composite material
• Metallurgy
• Chemical engineering
• Chemical physics
• Electrical engineering
• Physical chemistry
• Artificial Intelligence
• Condensed matter physics
• Engineering
• Neuroscience
• Structural engineering
• Thermodynamics
• Crystallography
• Computational chemistry
• Computer architecture
• Optics
• Optoelectronics
• Organic chemistry
• Biology

Selected publications

• Nuclear Quantum Effects at Metal-Water Interfaces

  ChemRxiv · 2026-03-12

  articleOpen access
  PublisherDOI

• A Boolean algebra approach for the disturbance decoupling problem of large-scale Boolean control networks

  Science China Information Sciences · 2026-03-10

  articleCorresponding
  PublisherDOI

• Downregulated lysyl oxidase in plasma extracellular vesicles: a biomarker linked to brain metastasis risk in lung adenocarcinoma

  BMC Medicine · 2026-03-12

  articleOpen access1st author

  BACKGROUND: Brain metastasis (BrM) is a leading cause of mortality in patients with lung adenocarcinoma (LUAD). Extracellular vesicles (EVs), which carry bioactive molecules, play a critical role in tumor microenvironment remodeling and exhibit metastatic organotropism, holding promise as liquid biopsy biomarkers. This study aims to identify plasma EV-derived proteins associated with LUAD-BrM. METHODS: A multi-omics framework was applied. Plasma EVs from 59 stage IV LUAD patients (30 BrM vs 29 non-BrM) were profiled using data-independent acquisition mass spectrometry proteomics. Candidate proteins were screened via bioinformatics and machine learning (LASSO/RF/SVM). Initial validation included tissue proteomics (n = 13), single-cell transcriptomics (TISCH2), and Western blot analysis of a subset of the discovery samples. Functional experiments were conducted in vitro. The lead candidate was ultimately validated in an independent plasma cohort (n = 158) through ELISA. RESULTS: Proteomic analysis implicated collagen-containing extracellular matrix (ECM) pathways. Lysyl oxidase (LOX), a key ECM cross-linking enzyme, was identified as a lead candidate. LOX and its family member LOXL1 were consistently downregulated in BrM tissues and plasma EVs. Single-cell analysis revealed decreased LOX expression specifically in BrM-associated fibroblasts, which showed suppressed ECM-related pathways. In vitro experiments supported a PI3K/AKT-LOX-ECM regulatory axis. Plasma EV-derived LOX demonstrated strong diagnostic performance in the independent cohort, with an AUC of 0.786 (95% CI 0.713iated fi. CONCLUSIONS: Our study establishes plasma EV-derived LOX as a promising non-invasive biomarker for LUAD-BrM through a comprehensive multi-omics validation strategy. We propose a model wherein downregulation of LOX, potentially driven by PI3K/AKT signaling in tumor-associated fibroblasts, contributes to ECM degradation and may promote brain-tropic metastasis. This finding offers new insights for risk stratification and timely intervention in LUAD patients.

  PublisherDOI

• Improving TCM question answering through tree-organized self-reflective retrieval with LLMs

  Frontiers in Medicine · 2026-03-12 · 1 citations

  articleOpen access

  Background: Large language models (LLMs) offer significant potential for intelligent question answering (Q&A) in healthcare, yet traditional knowledge representation methods fail to capture the complex, hierarchical nature of Traditional Chinese Medicine (TCM) knowledge systems. The lack of effective retrieval-augmented generation (RAG) frameworks specifically tailored for TCM's unique epistemology limits applications. Objectives: This study aims to evaluate the effectiveness of a novel Tree-Organized Self-Reflective Retrieval (TOSRR) framework in enhancing LLM performance on TCM Q&A tasks through innovative knowledge organization and dynamic self-correction mechanisms. Methods: We developed a hierarchical knowledge representation system that structures TCM knowledge as subject-predicate-object-text (SPO-T) units within a tree-like architecture, enabling multi-dimensional relationships while preserving semantic context. Our iterative self-reflection mechanism implements dynamic knowledge retrieval and validation across textbook chapters and disciplines. Performance was evaluated using randomly selected questions from the TCM Medical Licensing Examination (MLE) and college Classics Course Exam (CCE), representing both standardized clinical knowledge and classical theory assessment. Results: When integrated with GPT-4, the TOSRR framework demonstrated a 19.85% improvement in absolute accuracy on the TCM MLE benchmark and increased recall accuracy from 27 to 38% on CCE datasets. Expert manual evaluation revealed substantial enhancements across critical dimensions: safety, consistency, explainability, compliance, and coherence, with a comprehensive improvement of 18.64 points. Retrieval-Augmented Generation Assessment (RAGAs) metrics confirmed the framework's superior knowledge utilization, retrieval precision, and resistance to information noise compared to standard RAG approaches. Conclusion: The TOSRR framework enhances LLM performance in TCM knowledge tasks through its hierarchical knowledge representation and self-reflective retrieval approach. And the framework has potential for application in teaching.

  PublisherOA PDFDOI

• Supporting data for the study of the IA-MSA-DMA system

  Open MIND · 2026-03-12

  datasetOpen access1st authorCorresponding

  IA-MSA-DMA

  PublisherDOI

• The Artistic Characteristics of the Seated Buddha Statue on the Main Wall of the Sixth Grotto of Bingling Temple

  Lecture Notes in Education Arts Management and Social Science · 2026-01-26

  articleOpen access1st authorCorresponding

  This paper examines the artistic characteristics of the seated Buddha statue on the main wall of the sixth grotto of the Bingling Temple Grottoes in Yongjing County, Gansu Province, which was created during the Northern Zhou period (557–581). As a significant Buddhist site located along the Silk Road, the sculptures and murals of the Bingling Temple Grottoes illustrate the stylistic evolution of Buddhist art across different historical periods. This paper presents a detailed analysis of the artistic style and carving techniques employed in the creation of the seated Buddha statue in Cave 6. The facial features, hairstyle, robe folds, gestural handprints, and backlight decoration of the statue are meticulously examined in order to gain insights into the artistic techniques used during the Northern Zhou period (557–581). The analysis of these artistic features posits the significant role of this seated Buddha in the Buddhist art of the Northern Zhou Dynasty and elucidates its function in the cultural exchange of the Silk Road. It offers a crucial lens through which to comprehend the artistic style of the Northern Zhou period. This research aspires to contribute to the understanding of Northern Zhou Buddhist art and its place in Chinese art history.

  PublisherDOI

• Seismic Response and Predictive Modeling of Large-Diameter Shield Tunnels with Voids Behind Lining

  Buildings · 2026-03-11

  articleOpen access

  Voids behind the lining that develop during long-term operation can seriously compromise the seismic safety performance of metro shield tunnels. To investigate the influence of such void defects on large-diameter shield tunnels, this study systematically analyzed the causes and distribution patterns of voids. A three-dimensional discontinuous finite element model was developed to simulate the interaction among lining segments, connecting bolts, and surrounding rock. The seismic responses, including circumferential stress, interface slip, interface opening, and bolt tensile stress, were analyzed considering coupled factors such as the void circumferential angle, radial depth, distribution location, and geological conditions. Single-factor and multi-factor sensitivity analyses were conducted to evaluate the significance of the above coupled factors on the overall seismic response. The results show that lining circumferential stress, displacement, interface opening, and bolt stress increase with void enlargement, a shift in void location from the crown to the haunch, and deterioration of geological conditions. A void located at the right haunch leads to a peak circumferential stress of 3.27 MPa, causing local segment damage. Sensitivity analysis reveals that void location is the most influential factor affecting the seismic response, while geological conditions exhibit lower sensitivity. A predictive model for the peak circumferential stress around the void was established using multiple linear regression, incorporating void position, circumferential angle, and radial depth. Within the parameter range considered in this study, this model provides a theoretical basis and practical reference for rapid seismic risk assessment and safety management of shield tunnels with void defects.

  PublisherOA PDFDOI

• Neurology and inflammatory‐associated plasma protein biomarkers linked to dementia progression, brain aging pathology

  Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · 2026-01-01

  articleOpen access

  Abstract INTRODUCTION Establishing links between circulating plasma proteins and neuroimaging measures of pathology is essential for advancing biomarker discovery in age‐related cognitive decline. METHODS Blood plasma proteins were measured using Olink's targeted panels in predominantly mild cognitive impairment participants from cross‐sectional ( N = 287) and longitudinal ( N = 125) cohorts. We assessed associations between 88 neurology‐related and 40 inflammatory‐related proteins with dementia severity and neuroimaging measures from 3T magnetic resonance imaging and global amyloid beta (Aβ) positron emission tomography. RESULTS Several proteins were cross‐sectionally associated with dementia severity, most mediated by white matter integrity. Decreased brevican (BCAN) expression was associated with dementia severity, partially mediated by white matter integrity and Aβ deposition. Lower baseline BCAN levels were longitudinally associated with worse dementia outcomes over 2 years. DISCUSSION These findings highlight the potential of plasma proteins, particularly BCAN, as biomarkers of cognitive decline and neuroimaging pathology, warranting replication and mechanistic follow‐up studies. CLINICAL TRIAL REGISTRATION The BICWALZS is registered in the Korean National Clinical Trial Registry (Clinical Research Information Service; identifier, KCT0003391, Registration date 11/11/2016). Highlights We linked plasma protein levels to dementia severity and neuroimaging measures. White matter integrity and amyloid beta deposition mediated several of these associations. Brevican levels were linked to worse dementia outcomes over 2 years. Findings highlight potential plasma biomarkers for clinical dementia progression.

  PublisherDOI

• CEACAM6 Expression is Associated with Immune Infiltration and Poor Prognosis in Esophageal Squamous Cell Carcinoma

  DOAJ (DOAJ: Directory of Open Access Journals) · 2026-03-01

  article1st authorCorresponding

  ObjectiveTo investigate the expression of carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6) in esophageal squamous cell carcinoma (ESCC) and analyze its correlation with immune cell infiltration and patient prognosis. MethodsThree ESCC datasets (GSE161533, GSE26886, and GSE23400) from the GEO database were analyzed to identify differentially expressed genes. CEACAM6 was identified as a key gene through survival analysis. Its expression, prognostic value, and relationship with immune cell infiltration were further explored using databases, such as TIMER. Tissue samples were collected from 162 patients with ESCC. Immunohistochemistry was performed to detect the expression of CEACAM6, immune cell markers (CD4, CD8, CD20, and CD56), and immune checkpoint molecules (HHLA2 and CD40LG). Correlations between CEACAM6 expression and clinicopathological features, immune cell infiltration, and immune checkpoints were analyzed. ResultsBioinformatic analysis and clinical sample validation confirmed that CEACAM6 expression was significantly upregulated in ESCC tissues compared with adjacent nontumor tissues (P<0.05). High CEACAM6 expression was closely associated with advanced clinical stage (AJCC Ⅲ-Ⅳ), high T stage (T3-T4), lymph node metastasis, nonulcerative type, and poor prognosis. Furthermore, CEACAM6 expression levels were positively correlated with the infiltration density of CD8+ T cells, CD4+ T cells, and CD20+ B cells within the tumor microenvironment and with the expression of the immune checkpoint molecules HHLA2 and CD40LG (all P<0.05). ConclusionCEACAM6 serves as an independent poor prognostic factor for ESCC. Its high expression is implicated in the modulation of the tumor immune microenvironment by correlating with specific immune cell infiltration and immune checkpoint molecules, suggesting its potential as a novel prognostic biomarker and immunotherapeutic target for ESCC.

  PublisherDOI

• A Monolithically 3-D Printed Quasi-Elliptic-Type Hemispherical-Resonator-Based Waveguide Filter Using Degenerate TM ₂₁₁ Modes

  2026-02-07

  article
  PublisherDOI

Recent grants

• Collaborative Research: Traversals in Transformation Strain Space and Microstructure Design for High Performance Ferroelastic Materials

  NSF · $303k · 2020–2024

• Collaborative Research: Electrochemically driven Mechanical Energy Harvesting

  NSF · $270k · 2016–2020

• EAGER: SUPER: Electrochemical Protonation to Achieve Superconducting Matter

  NSF · $300k · 2021–2024

• Collaborative Research: Design of Low-Hysteresis High-Susceptibility Materials by Nanodomain Engineering

  NSF · $300k · 2014–2017

• AHSS: Multi-scale Modeling of Deformation Mechanism for Design of New Generation of Steels

  NSF · $611k · 2008–2013

Frequent coauthors

• Sidney Yip

  Massachusetts Institute of Technology

  135 shared

• E. Ma

  Xi'an Jiaotong University

  116 shared

• Zhiwei Shan

  University of Liverpool

  85 shared

• Akihiro Kushima

  Materials Processing (United States)

  85 shared

• Jianyu Huang

  Yanshan University

  67 shared

• Shigenobu Ogata

  Kyoto University

  61 shared

• Haowei Xu

  IIT@MIT

  61 shared

• Jeng‐Kuei Chang

  National Yang Ming Chiao Tung University

  56 shared

Labs

• Ju Li GroupPI

Education

• PhD

  Massachusetts Institute of Technology

  2000

• BS

  University of Science and Technology of China

  1994

Awards & honors

• 2022 Fellow, The Minerals, Metals & Materials Society
• 2019 Fellow, American Association for the Advancement of Sci…
• 2017 Fellow, Materials Research Society
• 2014 Fellow, American Physical Society
• 2005 Presidential Career Award for Scientists & Engineers