NanoTRIZ
Innovation Institute
Brisbane, Australia
CORE MISSION:
• A global research-enrichment institute focused on AI-assisted problem solving, innovation, and scientific communication
• Bridging guided research, translational thinking, and real-world applications
• Supporting the next generation of students, researchers, and innovation leaders
An independent Deep Tech Research Institute headquartered in Australia
(a private research initiative; not a university or RTO)
Call for Abstracts: International Conference
WELCOME TO THE NANOTRIZ INNOVATION INSTITUTE
As a pioneer in nanotechnology, I realized that creating yet another structure that merely "looks deep into the nanometers" is no longer sufficient. NanoTRIZ is a Meta-Institute for the Future. We are moving beyond traditional, fragmented research models to focus on the architecture of discovery itself. By combining structured problem-solving with advanced, ethical AI workflows, we are reviving the full-cycle "science-to-product" paradigm. We welcome collaboration across four pathways:
For Academics and Professors: Affiliate PIs, Research Leads, and expert mentors may support thematic research tracks, project groups, review sessions, or student cohorts within the NanoTRIZ framework.
For Students and Early Researchers: Participants may join selective research-enrichment and portfolio-development tracks designed to strengthen research literacy, responsible AI skills, academic writing, scientific communication, and documented project outputs.
For Technical Builders: Selected builders, engineers, and AI developers may collaborate on scientific software, research automation, SciOS tools, simulation workflows, and venture-oriented prototypes under project-specific agreements.
For Industry and Institutional Partners: NanoTRIZ can support innovation sprints, problem-framing workshops, technical roadmaps, research translation, and early-stage concept development for complex scientific or technological challenges.
I invite you to explore the NanoTRIZ ecosystem and identify the pathway most relevant to your goals.
Professor Alexander Solovev
Founding Director, NanoTRIZ Innovation Institute (Australia | Global Operations)
Previous affiliations: Harvard University • Columbia University in NYC • Max Planck Institute • TU Munich • Fudan University • University of Toronto
Phase I: 3-Month Research Sprint
Phase II: 12-Month Research Residency (Online)
The NanoTRIZ Research, AI and Academic Portfolio Program is a selective, output-oriented non-accredited enrichment program designed to help motivated participants move from academic learning to guided research development. Participants receive structured support in research topic selection, literature review, responsible AI use, academic writing, scientific communication, and portfolio development. The program combines AI-enabled research workflows with TRIZ-based problem-solving to help participants produce documented academic outputs such as a research proposal, short report, presentation, and portfolio artifact. Program fees support the digital research workflow, AI-assisted tools, templates, review processes, hosting, and portfolio-development infrastructure.
Optional non-accredited enrichment only. NanoTRIZ does not provide AQF qualifications, CRICOS enrolment, visa outcomes, migration services, scholarship awards, employment, university admission, or guaranteed publication outcomes. Internal NanoTRIZ program titles are used for program structuring only and do not constitute university appointments or accredited academic awards.
Meet Our Administration & Principal Investigators
Dr. Ilya Vinnikov
Dr. Brij Briz Mohan
Mrs. Inessa Gor
Dr. Alessandro Bernardi
Dr. Alexander Solovev
Research Projects Available for Students
Harvard Research Experience and Informal Scientific Advisory Support
NanoTRIZ is informed by Professor Alexander Solovev’s international research experience, including his time as a Visiting Scholar in the laboratory of Professor David Weitz at the Harvard John A. Paulson School of Engineering and Applied Sciences. Professor Weitz, a world-leading scientist in soft matter, microfluidics, and translational science, has also provided informal scientific advice to Professor Solovev in a personal academic capacity. This advisory relationship helps shape NanoTRIZ’s broader translational perspective: research should not stop at publications alone, but should be structured, communicated, validated, and, where appropriate, developed toward practical applications.
NanoTRIZ applies this philosophy through responsible AI-assisted research workflows, SciViD-style scientific communication, innovation sprints, student research enrichment, and early-stage technology roadmapping.
Professor Weitz’s informal advice is provided in a personal academic capacity. No institutional endorsement, partnership, sponsorship, or formal affiliation with Harvard University is implied.
Global Seminars: Building a Competitive Edge
TRIZ + AI + Meta-Skills for Researchers
The NanoTRIZ approach combines three complementary capabilities. TRIZ-informed problem framing helps researchers identify contradictions, constraints, and alternative solution pathways. Responsible AI-assisted workflows support literature analysis, cross-disciplinary synthesis, drafting, visualization, and structured comparison of ideas. Meta-skills — including critical thinking, research judgment, communication, and ethical reasoning — help the human researcher evaluate, refine, and defend the final output. Together, these elements support a more systematic research-development workflow: not only testing existing models, but also identifying better questions, generating clearer hypotheses, comparing possible solution directions, and communicating results with greater discipline.
From Classical TRIZ to Discovery-Oriented Research
Classical TRIZ, developed by Genrich Altshuller, proposed that technological innovation is not purely accidental: inventive progress often follows identifiable patterns, contradictions, and resource transformations that can be systematically analysed. NanoTRIZ builds on this foundation by extending TRIZ-informed thinking into modern scientific research practice. It combines structured problem framing, data-driven analysis, responsible AI-assisted workflows, and research meta-skills to support the exploration of scientific contradictions, available resources, emerging hypotheses, and discovery pathways across disciplinary and interdisciplinary fields.
Collaboration with Industry
NanoTRIZ supports industry and institutional partners through flexible research and innovation engagement models. Depending on the challenge, this may include a focused Rapid Innovation Sprint for early feasibility assessment or a deeper Sponsored Research Track for structured problem framing, technical analysis, solution mapping, and prototype-oriented planning.
Our approach combines TRIZ-informed problem solving, responsible AI-assisted research workflows, scientific review, and translational thinking to help partners clarify technical bottlenecks, compare solution pathways, reduce avoidable trial-and-error, and develop evidence-based R&D roadmaps. Project scope, confidentiality, intellectual property, deliverables, timelines, and commercial terms are defined in a separate written agreement before work begins. Where relevant, Australian companies may consider whether eligible R&D activities and expenditure qualify for the Australian R&D Tax Incentive, subject to independent professional advice and applicable registration and claim requirements.
