Assistant Teaching Professor
School of Informatics, Computing, and Cyber Systems, Northern Arizona University
Researcher | Educator | Engineer | Founder
Jiaming Li, Ph.D.
Assistant Teaching ProfessorSchool of Informatics, Computing, and Cyber SystemsNorthern Arizona University
My work connects interpretable acoustic modeling with AI-enabled engineering and embodied intelligence, from understanding complex physical systems to building practical intelligent applications.
Profile
Research, teaching, and applied AI leadership
Physical insight becomes computational intelligence.
I am an Assistant Teaching Professor at Northern Arizona University. My research spans acoustic modeling, AI applications in engineering, including AI-enabled CAD and robotics, data analytics, and information systems.
I earned my Ph.D. in Mechanical and Aerospace Engineering from Rutgers University in 2022. Before joining NAU, I worked in seismic imaging at CGG and held teaching and academic administration roles in the Rutgers School of Engineering and Rutgers Business School.
Since joining NAU in April 2024, I have served on faculty comprehensive review and doctoral admissions committees and as Assistant Director of Graduate Programs. I am also leading the development of a doctoral program centered on engineering applications of AI and closer integration between research and industry.
Across more than eight years of teaching in mechanical engineering and information systems, I have taught over 2,000 students and guided hundreds of graduate capstone projects. My current collaborations include researchers at Harvard University, the University of Oxford, and other international institutions.
Experience & education
Academic and professional path
Appointments
Adjunct Professor, Business School & Assistant to the Dean, School of Engineering
Rutgers University
Seismic Imaging Analyst
North America Surface Imaging, CGG
Education
Ph.D. in Mechanical and Aerospace Engineering
Rutgers University
M.S. in Mechanical and Aerospace Engineering
Rutgers University
B.E. in Mechanical Design, Manufacturing & Automation
Hefei University of Technology
Established research
Analytical modeling and inverse design of complex acoustic structures
Classical Helmholtz models become less reliable as resonator geometries grow asymmetric, multi-necked, or otherwise complex. I developed geometry-aware analogy mass-spring models that translate standing-wave behavior into fast, interpretable prediction.
The resulting AMSS and ASPMSS frameworks connect target sound-reduction frequencies directly to feasible resonator geometry, replacing repeated trial-and-error simulation with an analytical design workflow.
View this work on Google Scholar
Active research
Physics-guided learning, multimodal AI, and engineering intelligence
Current projects extend interpretable physical models into data-efficient machine learning, domain-adapted language models, and embodied systems.
Active direction 01
Analytical-prior machine learning for data-efficient acoustic prediction
This framework combines inexpensive analytical models with scarce high-fidelity simulations. Residual learning and prior distillation improve resonator prediction while preserving either explicit physical interpretability or a self-contained inference model.
Read the preprintActive direction 02
Rule-aware, parameter-efficient financial language modeling
RA-FinBERT combines LoRA-adapted contextual representations with lightweight sentiment and source features. The model improves low-resource financial sentiment classification with only a small number of additional trainable weights.
Read the preprint
Active direction 03
Acoustic-aware embodied intelligence and engineering agents
This direction combines motion, audio, vibration, state, and action for safer robot learning and execution. Related work also explores natural-language-driven CAD, multimodal evaluation, and intelligent engineering workflows.
Read the research statementResearch output
Publications
2026
A Data-Efficient Analytical Prior Machine Learning Framework for Sound Reduction Frequency Prediction in Helmholtz Resonators
Jiaming Li
arXiv:2608.16873, under review at Journal of Sound and Vibration
RA-FinBERT: Rule-aware LoRA adaptation for low-resource financial sentiment classification
Fan Zhang and Jiaming Li, co-first authors
arXiv:2608.09834, under review at Journal of Intelligent Information Systems
Systematic Design of Side-Branch Resonators for Targeted Noise Reduction Using an ASPMSS Analytical Model
Jiaming Li, Xue An, and Hae Chang Gea
Acta Acustica 10, 64
Edge-Side Residual Timing and Frequency Control for Software-Defined Ground Stations in 5G NTN Uplinks
Longji He, Elena Emma Wang, Xichun Wang, Juntao Xu, and Jiaming Li
arXiv:2604.13984
Burn-After-Use for Preventing Data Leakage through a Secure Multi-Tenant Architecture in Enterprise LLM
Qiang Zhang, Elena Emma Wang, Jiaming Li, and Xichun Wang
arXiv:2601.06627
On the Evolution of CI/CD Smells in Open-Source Android Applications
Zhongyu Ou, Elena Emma Wang, Jiaming Li, and Xichun Wang
SSRN Electronic Journal
2025
An Enhanced Analogy Serial-Parallel Mass-Spring System Analytical Model for Sound Reduction Frequency of Resonators With Multiple Necks
Jiaming Li, Xue An, and Hae Chang Gea
Journal of Vibration and Acoustics 147(6), 061003
An Improved Chaos Control with Adaptive Active Set Approach Combined in Reliability-Based Design Optimization
Xue An, De Li, and Jiaming Li
Scientific Reports 15, 42790
An Innovative Analogy Serial-Parallel Mass-Spring System Model for Sound Reduction Frequency Prediction of Asymmetric Resonators
Jiaming Li and Hae Chang Gea
Journal of Vibration and Acoustics 147(2), 021001
2024
A General Analogy Mass-Spring System Analytical Model for Sound Reduction of Side-Branch Resonators
Jiaming Li, Bowen Huang, and Hae Chang Gea
The Journal of the Acoustical Society of America 156(6), 4153-4168
Sound Reduction of Side-Branch Resonators: An Energy-Based Theoretical Perspective
Jiaming Li and Hae Chang Gea
AIP Advances 14(3), 035248, Editor's Pick
Accelerated PMA and Its Application in Reliability-Based Design Optimization
Xue An, Shanhai Jin, Dejin Zhao, Lifu Wang, and Jiaming Li
Structures 66, 106878
2019
A Systematic Optimization Method for Plastic Injection Molding Operational Parameters
Jiaming Li, Hae Chang Gea, and Euihark Lee
21st IAPRI World Conference on Packaging: Driving a Sustainable Future
Technical expertise
Research and engineering toolkit
Methods and platforms used across applied AI, computational modeling, robotics, simulation, and information systems.
AI / Machine Learning
Generative & Agentic AILLMs & Foundation ModelsMultimodal AIReinforcement LearningLoRA / PEFTSelf-Supervised LearningFederated LearningPhysics-Guided MLTime-Series ModelingPyTorchTensorFlowPythonCUDA
Computer Vision / Physical AI
Computer VisionImage ProcessingCNNs / ViTsMasked AutoencodersDiffusion ModelsImage ReconstructionRobotics & Embodied AIVLM / VLAWorld ModelsRobot LearningSim-to-RealIsaac Sim / LabROS2
Engineering / Simulation
AcousticsMechanical DesignComputational ModelingDigital TwinsSmart ManufacturingCAD / CAEFEA / CFDDesign OptimizationCOMSOLANSYS FluentSolidWorksMATLAB / SimulinkAutoCADCATIA
Software / Systems
Web & Mobile DevelopmentInformation SystemsProject ManagementJavaScript / ReactC++SQLUnix / LinuxJupyterLaTeX
Ventures
Building beyond the laboratory.
Founder
Bloomi Robotics
An early-stage robotics venture developing evaluation and benchmarking infrastructure for humanoid intelligence in industrial, care, and human-centered environments.
Company profile
Founder
TastyBite Foods
A global food sourcing and importing venture combining supplier relationships, international B2B trade, and AI-enabled operating tools for smaller businesses.
Company profileContact