Assistant Teaching Professor
School of Informatics, Computing, and Cyber Systems · Northern Arizona University

Researcher · Educator · Engineer · Founder
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
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
School of Informatics, Computing, and Cyber Systems · Northern Arizona University
Rutgers University
North America Surface Imaging · CGG
Rutgers University
Rutgers University
Hefei University of Technology
Established research
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

Current research
My current work extends interpretable physical modeling into AI-enabled engineering: physics-informed inverse design, natural-language-driven CAD, multimodal robot evaluation, and practical decision systems.
A central direction is acoustic-aware world modeling for embodied AI. By combining motion, audio, vibration, state, and action, these models can help robots anticipate contact outcomes, recognize failure, learn from difficult experience, and assess risk before acting.
Read the research statementResearch output
Journal articles, preprints, and conference work in acoustics, engineering design, applied AI, and information systems.
Jiaming Li, Xue An, and Hae Chang Gea
Acta Acustica 10, 64
Longji He, Elena Emma Wang, Xichun Wang, Juntao Xu, and Jiaming Li
arXiv:2604.13984
Qiang Zhang, Elena Emma Wang, Jiaming Li, and Xichun Wang
arXiv:2601.06627
Zhongyu Ou, Elena Emma Wang, Jiaming Li, and Xichun Wang
SSRN Electronic Journal
Jiaming Li, Xue An, and Hae Chang Gea
Journal of Vibration and Acoustics 147(6), 061003
Xue An, De Li, and Jiaming Li
Scientific Reports 15, 42790
Jiaming Li and Hae Chang Gea
Journal of Vibration and Acoustics 147(2), 021001
Jiaming Li, Bowen Huang, and Hae Chang Gea
The Journal of the Acoustical Society of America 156(6), 4153–4168
Jiaming Li and Hae Chang Gea
AIP Advances 14(3), 035248 · Editor’s Pick
Xue An, Shanhai Jin, Dejin Zhao, Lifu Wang, and Jiaming Li
Structures 66, 106878
Jiaming Li, Hae Chang Gea, and Euihark Lee
21st IAPRI World Conference on Packaging: Driving a Sustainable Future
AI application projects
Five working prototypes that translate AI capabilities into focused systems for procurement, international trade, robotics evaluation, commodity operations, and travel planning.

Embodied AI evaluation and certification
A structured evaluation environment for humanoid robots across mobility, manipulation, perception, autonomy, safety, and task success, with repeatable test suites and comparative scoring.

AI decision support for commodity operations
A multi-agent operating console that connects market analysis, supplier comparison, procurement, sales, and executive summaries for mineral and commodity trading decisions.

Multi-agent international trade assistant
A coordinated AI team for international B2B trade. Specialized agents interpret incoming email, review customers, prepare quotations, coordinate logistics, and support after-sales work.

AI-assisted B2B food procurement
A mobile-first procurement experience for independent food businesses, combining product discovery, repeat ordering, price-aware offers, delivery scheduling, and bilingual operation.

AI itinerary generation
A guided travel planner that converts destination, schedule, preference, and budget inputs into a structured day-by-day itinerary that can be saved or exported.
Ventures

Founder
An early-stage robotics venture developing evaluation and benchmarking infrastructure for humanoid intelligence in industrial, care, and human-centered environments.
Company profileFounder
A global food sourcing and importing venture combining supplier relationships, international B2B trade, and AI-enabled operating tools for smaller businesses.
Company profileContact