P
PRAMAN Shrikant Bhosale
First-Principles Inquiries · Formal Paradigms

Research & Theoretical Paradigms

Operating outside institutional silos, Shrikant Bhosale conducts rigorous independent research across non-Euclidean geometric computation, cognitive phase-field physics, and finite silicon cybernetics.

Program 0 · Neuromorphic AI & Metric Manifolds

GeoFormer: Quantized Propagation Geometry

Solving Few-Shot Abstraction via Endogenous Metric Manifolds & Neuromorphic In-Memory Computing
Working Abstract: Contemporary foundation Transformers treat sequence space as an immutable, flat Euclidean coordinate system, leading to catastrophic forgetting, topological blindness, and compositional collapse (0.0% on multi-hop transitive reasoning). GeoFormer resolves this crisis through Endogenous Propagation Geometry (Q-PG) and Two-Timescale Metric Plasticity: frozen 1.58-bit ternary synaptic weights (θ ∈ (-1, 0, 1)) are decoupled from a dynamic metric conductance lattice W. Information flow actively carves zero-resistance Geodesic Highways (dij → 0) during in-context inference, continuous thermodynamic relaxation (Q-TAC) routes multi-hop transitive paths, and the architecture compiles directly to 1T1R memristor crossbars at 443.9 picajoules per inference (9,462× lower energy than GPU FP32).

Key Theorems & Verified Breakthroughs

  • Two-Timescale Metric Plasticity separating frozen ternary cortical weights from dynamic fast metric conductances.
  • 80,000× memory compression via Sparse Hippocampal Relational Working Memory (100,000 entities in < 10 MB RAM).
  • 443.9 pJ physical neuromorphic memristor crossbar compilation (9,462× lower energy than GPU FP32 baselines).
  • Formal verification of all 6 governing algebraic invariants certified UNSAT by Microsoft Z3 SMT Theorem Prover.
  • Clinical Emergency Differential Diagnostic Assistant tested with 100.0% accuracy across casualty scenarios in 0.16 ms – 0.40 ms.
@software{bhosale2026geoformer,
  author    = {Bhosale, Shrikant},
  title     = {GeoFormer: Quantized Propagation Geometry and Neuromorphic In-Memory Foundation Models},
  year      = {2026},
  url       = {https://github.com/bhosaleone/geoformer},
  publisher = {Hugging Face & GitHub}
}
Program I · Non-Euclidean Computational Thermodynamics

The Bhosale–Pandit Paradigm

Zero-Thermodynamic Debt in Discrete Geometric Computation
Working Abstract: Classical information thermodynamics posits a mandatory dissipation tax (the Landauer bound of $k_B T \ln 2$ per erased bit). The Bhosale–Pandit Paradigm demonstrates that this dissipation is an artifact of coordinate-dependent Euclidean representations. By mapping computational states to closed, coordinate-invariant geometric lattice manifolds, state transitions occur with zero net thermodynamic erasure tax.

Key Theorems & Formal Contributions

  • Dismantling of the classical thermodynamic erasure tax through coordinate-invariant geometric transformations.
  • Elimination of accumulated numerical rounding debt in ultra-precision physics simulators and autonomous control.
  • Derivation of zero-entropy state transformations in topologically closed computational lattices.
  • Direct engineering blueprint for non-dissipative microarchitectures operating at room temperature.
@book{bhosale2026paradigm,
  author    = {Bhosale, Shrikant},
  title     = {The Bhosale–Pandit Paradigm: Geometry Owes the Universe Nothing},
  year      = {2026},
  publisher = {Praman Press},
  isbn      = {B0GXGN5VXJ}
}
Program II · Finite Automata & Substrate Physics

Finite Automata & Silicon Boundary Security

The Physical Security Limits of Finite Turing Implementations
Working Abstract: Software engineering assumes the mathematical infinite Turing tape. In physical silicon, every computational machine is a finite state automaton subject to voltage propagation, clock jitter, and thermal emission. The discrepancy between abstract compiler contracts and physical silicon boundaries creates subterranean doors for side-channel collapse and memory corruption.

Key Monograph Treatises

Turing Incomplete →

Exposing how infinite tape assumptions cause speculative execution leaks (Spectre, Meltdown) in finite silicon.

Explore Monograph →

Birth of Vulnerabilities →

A Developer’s Guide to Secure Code from the Hacker’s Perspective: Cognitive origins of exploit vectors.

Explore Monograph → 
@book{bhosale2026turingincomplete,
  author    = {Bhosale, Shrikant},
  title     = {Turing Incomplete: The Security Gaps of Finite Turing},
  year      = {2026},
  publisher = {Praman Press},
  isbn      = {B0HNSGGJQL}
}
Program III · Topological Consciousness & Cognitive Physics

The Information-Space-Lattice (ISL) Framework

A Unified Field Formulation of Memory, Time, and Experience
Working Abstract: The “hard problem of consciousness” arises from an arbitrary dualism between physical matter and subjective awareness. The ISL Framework establishes consciousness as an active phase-field stabilizer of perceptual coordinate space. Memory retention, temporal arrow asymmetry, and experiential qualia are formalized as physical boundary constraints on local topological lattices.

Core Theses & Formal Results

  • Formalization of consciousness as an active phase-field stabilizing perceptual space.
  • Derivation of the psychological arrow of time from entropy gradients across topological boundaries.
  • Unification of memory encoding with physical mass-energy distribution across discrete coordinate lattices.
@book{bhosale2026atmabhan,
  author    = {Bhosale, Shrikant},
  title     = {The Atmabhan Papers: Memory, Time, and Consciousness},
  year      = {2026},
  publisher = {Praman Press},
  isbn      = {B0GLXJLN11}
}
Program IV · Quantum Vacuum Geometry

The 137 Code: Icosahedral Vacuum Geometry

Geometric Derivation of the Fine-Structure Constant (α)
Working Abstract: The dimensionless fine-structure constant ($lpha pprox 1/137.035999$) governs electromagnetic coupling and atomic matter stability. While standard physics treats $lpha$ as an arbitrary empirical measurement, the Icosahedral Vacuum Program demonstrates that $lpha$ emerges as an inescapable geometric packing constant of icosahedral vacuum lattices and irrational resonance thresholds.

Geometric Axioms & Empirical Predictions

  • Zero-free-parameter derivation of the electromagnetic coupling constant.
  • Mathematical resolution of Dirac’s large numbers hypothesis via factorial dimensional resonance.
  • Concrete falsifiable predictions for ultra-high-energy vacuum polarization experiments.
@book{bhosale2026nest,
  author    = {Bhosale, Shrikant},
  title     = {THE IRRATIONAL NEST: The 137 Code and the Geometry of Everything},
  year      = {2026},
  publisher = {Praman Press},
  isbn      = {B0GS121K5W}
}
Program V · Invariant Cybernetics & SAST

SBH: Software Bug Hunter & Invariant SAST

Zero-False-Positive Security Engine via Universal AST Invariants & GVF Curvature
Working Abstract: Traditional SAST scanners suffer from a 40%+ false positive crisis due to superficial regex heuristics. Built on Shrikant Bhosale’s foundational security monographs Birth of Vulnerabilities and Turing Incomplete, the SBH engine implements dual-layer Abstract Syntax Tree (AST) invariant proofs, Geometric Vulnerability Framework (GVF) curvature tensors ($\kappa$), and 32-particle simulated annealing relaxation to systematically eliminate false alarms and output compliant SARIF v2.1.0 telemetry for production CI/CD pipelines.

Key Operational Breakthroughs

  • Near-zero false positive rate (< 3%) via compile-time immutability, schema normalization, and taint sanitizer tracing.
  • Rigorous GVF curvature scoring ($0.000 – 1.000$) computing true structural exploitability tensors.
  • Full compliance with OASIS SARIF v2.1.0 standard for direct integration into GitHub Code Scanning and GitLab Security.
  • Open-source core available on PyPI (sbh-scanner), GitHub Marketplace Action, and Codeberg.
@software{bhosale2026sbh,
  author    = {Bhosale, Shrikant},
  title     = {SBH: Software Bug Hunter and Invariant Security Scanner},
  year      = {2026},
  url       = {https://praman.blog/sbh/},
  publisher = {Praman Press & Codeberg}
}