Director · MagicLenz — Independent Researcher
Technology Leader & Independent Researcher
I build AI-driven enterprise software by day and chase a single question by night: whether the particles and symmetries of physics fall out of pure rotational geometry. i is where those two lives meet.
Profile
I'm Randeep Chaudhary — a technology leader and independent researcher with a long-running interest in mathematics, theoretical physics, artificial intelligence, and software engineering. I split my time between building real systems for real businesses and chasing a private research question about how geometry gives rise to the physical world.
I currently serve as Director at MagicLenz, where I lead work on advanced AI solutions, enterprise software, computer vision, and intelligent automation. My career has moved through software architecture, distributed systems, cloud computing, and large-scale enterprise application development — always with an eye toward turning cutting-edge technology into something a business can actually use.
My independent research asks whether the symmetries and particles of the Standard Model can emerge naturally from geometric principles. The current thread develops iota (i) as a geometric rotor, exploring how rotation in complex spaces might unify gauge symmetries, particle properties, and mass generation. It draws on complex numbers and rotational geometry, Clifford algebras, quaternions and octonions, exceptional Lie groups (G₂, F₄, E₆), topology, differential geometry, gauge theory, and computational mathematics.
I believe rigorous mathematics and practical engineering should complement each other, not compete. The same discipline that makes a proof hold together is what makes a distributed system reliable — clarity first, elegance second, shortcuts never. I try to lead teams the way I approach a proof: define the problem precisely, then build toward the simplest structure that actually works.
This work is ultimately about bridging two worlds I refuse to treat as separate: abstract mathematical ideas and the computational models that can test them against the physical universe. Going forward, I want to keep publishing this research openly, keep building AI and enterprise systems that hold up under real-world pressure, and keep the door open for researchers, engineers, educators, and students who want to think about any of this together.
“Technology should simplify human lives.
— Randeep Chaudhary
Artificial intelligence should empower businesses.
Research should bridge mathematics and engineering.
Innovation should create lasting value.”
Capabilities
Applied AI systems for real business problems.
Model design, training, and deployment at scale.
Perception systems from prototype to production.
Connected devices and the pipelines behind them.
Resilient, cost-aware infrastructure.
Software that survives real organizations.
Systems designed to bend, not break.
Removing repetitive work from the critical path.
Security treated as a design constraint, not an add-on.
Mathematical physics and geometric unification.
Peer-Reviewed
DOI: 10.55041/IJSREM66507
DOI: 10.55041/IJSREM66509
DOI: 10.55041/IJSREM66508
ISSN 2582-3930
Open access, peer-reviewed. Impact Factor 8.659. Home to both publications above.
Open Access · CC BY 4.0
Both articles were accepted following peer review and published under a Creative Commons Attribution license, permitting open sharing with attribution.
Verified
Research Publication
Research Publication
Research Publication
Recognition
More milestones will be added here as they happen.
Journey
Behind the Work
Highlights
Get in Touch
Research · AI · Enterprise Software · Computer Vision · Automation