Nian X. Sun
VerifiedNortheastern University · Engineering Management and Systems Engineering
Active 1974–2026
About
Nian X. Sun is a College of Engineering Distinguished Professor in the Departments of Electrical and Computer Engineering and Physics at Northeastern University. He directs the W.M. Keck Laboratory for Integrated Ferroics and is the founder and Chief Technology Advisor of Winchester Technologies, LLC. His research focuses on magnetoelectric materials and devices for wireless power and biomedical sensing, as well as advanced materials and microsystems including gas sensors, magnetic sensors, neural magnetic sensing and stimulation, tunable RF/microwave components, and energy harvesting systems. Dr. Sun earned his Ph.D. from Stanford University in 2002 and has worked as a Scientist at IBM and Hitachi Global Storage Technologies. In 2025, he served as Head of the Corporate Research Center at Midea Group, overseeing the R&D of approximately 600 scientists. His achievements have been recognized with numerous honors, including the W.M. Keck Foundation Award, Humboldt Research Award, Søren Buus Outstanding Research Award, NSF CAREER Award, and ONR Young Investigator Award. He has authored over 400 peer-reviewed publications, holds 21 US patents, and has delivered more than 200 invited presentations at international conferences and seminars. Dr. Sun is an elected Fellow of the National Academy of Inventors, IEEE, and the American Physical Society.
Research topics
- Engineering
- Materials science
- Physics
- Optoelectronics
- Electrical engineering
- Nanotechnology
- Acoustics
- Computer Science
- Composite material
- Optics
- Telecommunications
- Condensed matter physics
- Nuclear magnetic resonance
- Engineering physics
- Electronic engineering
Selected publications
Cancer Research · 2026-04-03
articleAbstract Background Loss-of-function mutations in KEAP1 frequently occur in lung adenocarcinoma and are associated with poor prognosis and limited benefit from immunotherapy. However, the mechanisms linking KEAP1 deficiency to immune evasion remain elusive. Methods We combined patient data analysis, in vivo tumor models, and in vitro co-culture systems to investigate how KEAP1 deficiency shapes dendritic cell (DC) biology and response to PD-1 blockade. Ferroptosis induction assays, damage-associated molecular patterns (DAMPs) quantification, cytokine profiling, and mechanistic interrogation of the FSP1-CoQ10 axis were performed to delineate underlying pathways. Results Clinically, KEAP1 mutations correlated with poor response to PD-1 blockade and reduced DC infiltration. In murine models, KEAP1-deficient tumors exhibited marked resistance to anti-PD-1 therapy. Mechanistically, KEAP1 loss impaired DC function in vitro, as evidenced by reduced maturation, phagocytosis, and naïve CD8+ T-cell priming capacity. This defect was linked to two complementary mechanisms. First, KEAP1-deficient tumor cells resisted ferroptosis and failed to release immunogenic DAMPs, including extracellular ATP, HMGB1, and calreticulin. Second, KEAP1 deficiency reprogrammed the cytokine secretion profile, with downregulation of CCL2, IL-6, CXCL1, and CXCL2, thereby diminishing DC recruitment and inflammatory signaling. Notably, inhibition of the FSP1-CoQ10 antioxidant axis restored ferroptosis-associated immunogenic cell death. Conclusions Our study identifies KEAP1 deficiency as a driver of immune-cold tumor microenvironments and resistance to PD-1 blockade, acting through impaired ferroptosis-induced immunogenic cell death and disrupted DC function. Targeting the FSP1-CoQ10 pathway may restore DC function and sensitize KEAP1-mutant lung cancers to immunotherapy. Citation Format: Xinfeng Wang, Yuxin Yao, Tomi Jun, Kuan-lin Huang, Nan Sun, Jie He. KEAP1 loss-of-function suppresses immunogenic ferroptosis and limits PD-1 blockade efficacy through an NRF2-FSP1 pathway [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 171.
Journal of Central South University · 2026-02-01
article1st authorCorrespondingScreening of Ruthenium Complexes as the Protein Light Switches for Protein Detection
Analytical Chemistry · 2026-04-13
articleRuthenium(II)–dipyrido[3,2-a:2′,3′-c] phenazine (dppz) complexes (Ru–dppz complexes) can function as the molecular light switches for DNA assay, but their applications to protein detection remain a challenge because proteins possess more structural complexity than nucleic acids. Herein, we develop for the first time a computational virtual screening strategy to screen light switches for protein detection. We find that the binding affinity between Ru–dppz complexes and proteins relies on the structure and ratio of auxiliary and dppz ligands, and it plays a key role in light-switching performance. We discover that [Ru(dppz)2dip]2+ (dip = 4,7-diphenyl-1,10-phenanthroline) can function as the human serum albumin (HSA) light switch, and it exhibits strong hydrophobic and π-cation interactions with HSA to achieve a 280.0-fold luminescence enhancement, which is 2 orders of magnitude higher than the parent complex [Ru(dip)3]2+. Moreover, [Ru(dppz)2dip]2+ displays a rapid response time (<1 s), a large Stokes shift, and high sensitivity for HSA assay with a limit of detection of 0.0093 mg/L. We further develop a smartphone-integrated point-of-care device based on [Ru(dppz)2dip]2+ for rapid detection of HSA. Notably, this strategy can be extended to screen the β-lactoglobulin light switch that exhibits a 346.1-fold luminescence enhancement. This research provides a universal approach for the discovery of high-performance protein light switches with promising applications in biomedical research and clinical diagnostics.
Cancer Research · 2026-04-03
articleAbstract Background: High mobility group box 1 protein (HMGB1) is known to be associated with progression and poor prognosis of several solid tumors. However, its role in small cell lung cancer (SCLC) remains unclear. Therefore, we intend to provide the first systematically analysis of HMGB1 as a prognostic and immunotherapy predictive biomarker in SCLC. Methods: Public datasets and self-tested transcriptomic/proteomic data from SCLC surgical samples were integrated to screen target molecules through differential analysis. HMGB1 expression was validated in multicenter cohorts using qPCR and tissue microarray immunohistochemistry (IHC). Public data and in-house data were utilized to investigate the association between HMGB1 and SCLC transcriptional subtypes as well as clinicopathological features. The impact of HMGB1 on the tumor immune microenvironment was evaluated through transcriptomic enrichment analysis, single-cell sequencing and IHC. In the NCC cohort of over 180 SCLC patients treated with immune checkpoint inhibitors (ICIs), the relationships between HMGB1 and ORR, PFS, and OS were analyzed, with a prediction model constructed. Finally, serum HMGB1 levels were measured by ELISA to assess its value as a secreted protein biomarker. Results: Multi-omics screening and clinical validation confirmed that HMGB1 was significantly overexpressed in SCLC tumor tissues, and high expression was associated with shorter OS and DFS. HMGB1 expression showed no significant association with the four SCLC subtypes but correlated with high-risk factors such as advanced tumor stage. Transcriptomic enrichment and single-cell analyses revealed that high HMGB1 expression correlated with an immunosuppressive "cold tumor" microenvironment. In the ICIs-treated cohort, patients with high HMGB1 expression exhibited significantly shortened PFS and OS. ROC analysis demonstrated that HMGB1 outperformed traditional markers in predicting treatment response. Multivariate Cox regression confirmed HMGB1 as an independent predictor of immunotherapy efficacy in SCLC. Serum HMGB1 levels were consistent with tumor tissue expression, validating its liquid biopsy potential. Conclusions: HMGB1 is an independent risk factor for SCLC prognosis. Its high expression shapes an immunosuppressive microenvironment and mediates resistance to immunotherapy. HMGB1 shows a good potential to serves as a novel biomarker for predicting immunotherapy efficacy in SCLC, with clinical applicability for both tissue-based and blood-based detection. Citation Format: Bohui Zhao, Chaoqi Zhang, Peng Wu, Dongyu Li, Xuanyu Gu, Hengjia Tu, Nan Sun, Jie He. A comprehensive analysis of HMGB1 as a biomarker for predicting immunotherapy efficacy in small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6553.
Multi-Probing Opportunistic Routing in Buffer-Constrained Wireless Sensor Networks
Sensors · 2026-04-08
articleOpen access1st authorCorrespondingWireless sensor networks (WSNs) are fundamental building blocks of modern ubiquitous sensing systems. In many practical WSN deployments, sensing devices are tightly constrained in buffer capacity, while device mobility leads to topology decentralization. These characteristics pose significant challenges for reliable and timely data delivery across WSNs. In this paper, we propose a general multi-probing opportunistic routing strategy tailored for buffer-constrained WSNs, aiming to enhance transmission opportunity utilization under realistic sensing device limitations. With the help of Queueing Theory and Markov Chain Theory, we capture the sophisticated queueing processes for the buffer space of sensors, which enables the limiting distribution of the buffer occupation state to be determined. On this basis, we develop a theoretical performance modeling framework to evaluate the fundamental performance metrics of the WSN with the multi-probing opportunistic routing, including the per-flow throughput and the expected end-to-end delay. The validity of the performance modeling framework is verified by network simulations. Moreover, extensive numerical results demonstrate the network performance behaviors comprehensively and reveal some insightful findings that can serve as important guidelines for the configuration and operation of WSNs.
Targeted intervention method for unsafe behavior based on pan-scene data of subway construction
International Journal of Occupational Safety and Ergonomics · 2026-03-31
article. The results showed that a targeted intervention method can provide new ideas for unsafe behavior modification, and realize accurate identification, intervention and management of unsafe behavior.
Solvent Polarity Modulated Excited-State Dynamics within a Pyrene-Based Covalent Organic Cage
The Journal of Physical Chemistry A · 2026-04-07
articleCorrespondingIt is still a great challenge to establish the relationship between intermolecular packing and photophysical properties in the solid state of photofunctional materials. Covalent linked multichromophoric architecture is a versatile platform to mimic the surrounding environment in the solid state. Here, a [3 + 6]-type covalent organic cage incorporating three 1,6-disubstituted pyrene units (denoted as PyTC1) was synthesized and its excited-state dynamics was systematically investigated using a transient spectroscopy technique. An H-type aggregate was formed in this cage, showing a strong intramolecular electronic coupling. As revealed by transient absorption spectroscopy, the excited-state dynamics of PyTC1 are strongly dependent on solvent polarities. In low-polarity solvents, PyTC1 undergoes intersystem crossing (ISC) to form the triplet state with a rate (3.11 ns in toluene) approximately twice that of the monomer (7.32 ns in toluene), while in high-polarity solvents, a rapid symmetry breaking charge separation (SB-CS) process (τ = 143.2 ps) occurs to generate a charge transfer state that forms an equilibrium with the singlet state, leading to the formation of delayed fluorescence (τ = 18.6 ns) from the reverse process of SB-CS. Then, the triplet state was formed from the charge transfer state via a spin–orbit charge-transfer intersystem crossing mechanism. These findings not only emphasize the importance of the solvent polarity on excited-state dynamics of organic cages but also provide molecular-level insights for the establishment of the structure–property relationship in the solid state.
Frontiers in Neurology · 2026-04-09
articleOpen access1st authorCorrespondingBackground: Post-stroke cognitive impairment (PSCI) is a common stroke complication, significantly reducing patients' quality of life and increasing caregiving burden. Repetitive transcranial magnetic stimulation (rTMS) of the left dorsolateral prefrontal cortex (L-DLPFC) improves cognition but with limited efficacy. Stimulation of Neiguan (PC6), a key acupoint in traditional Chinese medicine, modulates cognition-related brain networks. Objective: To compare cognitive improvement and brain network remodeling in PSCI patients who receive rTMS over the L-DLPFC combined with (1) PC6 magnetic stimulation (MAG), (2) PC6 acupuncture (ACU), or (3) PC6 sham magnetic stimulation (SHM). Methods: = 35) groups. Interventions will be administered 5 times/week for 3 weeks. All groups will receive high-frequency rTMS over the L-DLPFC (10 Hz, 80% rest motor threshold). The primary outcome is the Montreal Cognitive Assessment (MoCA) change from baseline to week 3. Secondary outcomes include the Mini-Mental State Examination (MMSE), Modified Barthel Index (MBI), Hamilton Anxiety Rating Scale (HAMA), Hamilton Depression Rating Scale (HAMD), Pittsburgh Sleep Quality Index (PSQI), and adverse events. Functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS) data will be acquired at baseline and post 3-week treatment. Clinical data will be analyzed via SPSS 26.0 using repeated measures analysis of variance (ANOVA) to compare intergroup changes in outcomes across time points. Neuroimaging data will be processed in MATLAB R2018a. Correlation analyses will assess associations between clinical scores and neuroimaging parameters. Conclusion: This study will provide the first randomized controlled evidence for acupoint magnetic stimulation in PSCI, demonstrating that adding MAG to L-DLPFC rTMS confers additional cognitive benefits. Its mechanism in reshaping brain networks will be elucidated via fNIRS-fMRI, which is expected to accelerate clinical translation of non-pharmacological interventions. Clinical trial registration: https://www.chictr.org.cn/, identifier ChiCTR2400090768.
Water · 2026-04-11
articleOpen accessHydrodynamically triggered landslides remain a major concern in reservoir regions, where the mechanisms controlling displacement evolution are still not fully understood and the multi-scale deformation responses induced by individual hydrodynamic factors remain difficult to quantify. To address these issues, this study establishes a TSD-TET composite framework by integrating time-series signal decomposition with deep learning for multi-scale displacement prediction and the mechanism-oriented interpretation of hydrodynamically triggered landslides. The monitored displacement sequence is first decomposed into physically interpretable components, including trend, periodic, and random terms. Each component is subsequently predicted using deep temporal learning models to capture different deformation characteristics at multiple temporal scales. Meanwhile, key hydrodynamic driving factors, including rainfall, reservoir water level, and groundwater level, are decomposed within the same framework to examine their statistical associations with different displacement components. The proposed approach is applied to the Donglingxin landslide located in the Sanbanxi Hydropower Station reservoir area. Results show that the model achieves high prediction accuracy under both long-term forecasting horizons and limited-sample conditions, with a cumulative displacement coefficient of determination reaching R2 = 0.945. Mechanism analysis further indicates that trend deformation is mainly controlled by geological structure and gravitational loading, periodic deformation is strongly modulated by hydrological cycles associated with reservoir water level fluctuations, and random deformation is more likely to reflect short-term disturbances and transient hydrodynamic forcing. These findings provide new insights into the deformation mechanisms of hydrodynamically triggered landslides and offer a promising technical pathway for improving displacement prediction, monitoring, and early warning of reservoir-induced landslide hazards.
ACS Applied Polymer Materials · 2026-04-03 · 2 citations
article1st authorTo overcome the performance barriers of rigid polyurethane foam (RPUF), a boron-containing chitosan derivative, CBPM, was synthesized. Boron phosphate (BP, acid source) and melamine (nitrogen source) synergistically promote the conversion of chitosan to carbon. The combustion tests demonstrate that the RPUF/20CBPM composite exhibits excellent flame retardancy, with a limiting oxygen index of 27.5% and a UL-94 flammability rating of V-0. Compared to pure RPUF, the heat release rate, total heat release, combustible gases, and hazardous gas release of RPUF/20CBPM are significantly reduced, while the residual carbon yield increases dramatically from 0.5% to 12.2% at 800 °C, indicating CBPM’s excellent smoke-suppression and char-forming capabilities. Furthermore, RPUF/20CBPM exhibits satisfactory mechanical properties and thermal insulation, with a compressive strength of 0.23 MPa and a thermal conductivity of 0.0347 W/(m·K). Actually, the CBPM significantly improves the flame retardancy of RPUF and synergistically enhances its mechanical properties and thermal insulation. This advancement provides a promising approach to develop safer, more durable, and higher-performance RPUF materials, potentially expanding their applications in building insulation, aerospace, and transportation materials.
Recent grants
NSF · $406k · 2008–2013
NIH · $1.8M · 2018–2022
NCS-FO: Nanomagnetic Stimulation Capability for Neural Investigation and Control
NSF · $364k · 2015–2019
NSF · $287k · 2008–2011
Materials World Network: Self-Assembled Nanocomposite Magnetoelectric Thin Films
NSF · $188k · 2006–2009
Frequent coauthors
- 310 shared
Atsufumi Hirohata
Conference Board
- 244 shared
Mingzhong Wu
Conference Board
- 242 shared
L. H. Lewis
Northeastern University
- 242 shared
Ron Goldfarb
Conference Board
- 242 shared
Anjan Soumyanarayanan
Institute of Materials Research and Engineering
- 242 shared
Barry Zink
Conference Board
- 242 shared
Sachiko Yamaguchi‐Sekino
Antea Group (France)
- 242 shared
Lucian Prejbeanu
Institute of Electrical and Electronics Engineers
Education
- 2001
PhD in Materials Science & Engineering and MS in Electrical Engineering, Materials Science & Engineering; Electrical Engineering
Stanford University School of Engineering
- 1996
MS in Materials Science & Engineering, Institute of Metal Research
Chinese Academy of Sciences
- 1993
BS, Materials Science & Engineering
Huazhong University of Science and Technology
Awards & honors
- W.M. Keck Foundation Award
- Humboldt Research Award
- Søren Buus Outstanding Research Award
- Outstanding Translational Research Award
- NSF CAREER Award
- Resume-aware match score
- Save to shortlist
- AI-drafted outreach
See your match with Nian X. Sun
PhdFit ranks faculty by your research interests, methods, and publications — grounded in their actual work, not templates.
- Free to start
- No credit card
- 30-second signup