CQER-IQ conducts frontier research across multiple scientific domains using a structured human–AI collaborative methodology. Active collaborations with world-leading research groups. Spin-outs fund the science.
Each stream follows a common pathway: hypothesis, computational validation, laboratory partnership, commercialisation. Every line produces evidence-based, reproducible results.
Disruption-prediction algorithms for tokamak plasmas. Co-authorship on submitted manuscript with CTU Prague (GOLEM tokamak). Algorithm validated on UKAEA MAST data across nearly 700 shots.
Sodium-ion battery technology advancing from concept to laboratory validation. Laboratory partnerships forming for synthesis, characterisation, and electrochemical testing.
Computational analysis of cancer cell behaviour across multiple public single-cell datasets spanning approximately 100,000 cells and five cancer types. Active collaborations with genomics and machine learning groups.
Designing laboratory experiments using Bose–Einstein condensate analogue systems to test predictions about quantised coherence structure in gravitational entanglement.
Internal deployment of reasoning and workflow stack across research and M&A applications. Commercial industrialisation under review.
Processor architecture progressing from simulation to fabrication partnerships. Room-temperature photonic cores.
Discrete fine-tuning and evaluation methods enforcing physical constraint principles. Early adopter programme in preparation.
Theoretical investigations into early-universe dynamics and large-scale structure, connecting quantum gravity frameworks to observational cosmology and CMB signatures.
Geometric and topological approaches to Standard Model parameters, including derivation of mixing angles and mass hierarchies from first principles.
Foundational framework treating information as a physical substrate. Connecting entropy, coherence, and computational complexity to emergent physical phenomena.
All research is conducted through a structured methodology combining domain expertise with advanced AI systems. The human provides intuition, cross-disciplinary pattern recognition, and strategic direction. AI systems provide computational speed, literature access, and iterative capacity.
Systematic ingestion and synthesis across scientific literature. Hypothesis generation grounded in established theory.
Automated code, simulation, and testing pipelines that execute mathematical proofs and validate predictions against real data.
Structured internal and external review ensuring rigour, reproducibility, and honest acknowledgement of limitations at every stage.
Experimental validation through institutional collaborations. Predictions tested in real laboratories before any claim is made public.
Structured capital raising across grants, angel investors, family offices, venture capital, and private equity — matched to the stage and risk profile of each programme.
Proof-of-concept deployment with pilot customers or partners. Validated unit economics and market fit before scaling.
IP commercialised through dedicated spin-out companies or licensing agreements. Revenue from spin-outs funds the next wave of research.
Trade sale, strategic acquisition, or IPO. Returns recycled into the research engine to launch the next programme.
Active partnerships and collaborations across leading research institutions. All collaborators are fully informed of CQER-IQ's human–AI research methodology.
A precision team combining frontier research, AI systems, and venture execution — amplified by proprietary automation.
Theoretical physicist, entrepreneur, and M&A strategist with 25+ years turning complex technology into enterprise value. 20+ sell-side mandates completed. MBE (2024) for Services to Global Technological Advancement.
LinkedIn
Quantum systems and energy specialist. Co-IP holder on battery technology. Royal Society Newton International Fellow (2022–24). University of Portsmouth.
LinkedIn
ML-for-physics and fundamental-theory researcher. Manuscript reviewer. Cambridge & UCL educated. University of Southampton.
LinkedInPre-prints available on Zenodo. Open-source contributions to national fusion data infrastructure.
Richard H Harris MBE
Founder & Principal Investigator, CQER-IQ
Level 1, Devonshire House
1 Mayfair Place, Mayfair
London W1J 8AJ
Active research programmes with institutional collaborators across four scientific domains. Contact us for NDAs and executive summaries.
Book a call →