AI & ML interests

Specializing in cognitive AI architectures and quantum-simulation frameworks. We leverage NVIDIAยฎ CUDA and TensorRT to optimize high-performance models. This organization serves as the official hub for the MQ Research Scholars cohort, bridging the gap between deep-tech research and industrial application in Bengaluru. Our work focuses on agentic workflows and sovereign AI infrastructure.

Recent Activity

Niroop2007ย  updated a dataset 3 days ago
mah-quantum/domain-adaptive-corpus
Niroop2007ย  published a dataset 3 days ago
mah-quantum/domain-adaptive-corpus
Niroop2007ย  updated a model 3 days ago
mah-quantum/quantised-llm-checkpoints
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Organization Card

โ–ฃ MAH QUANTUM // COGNITIVE ARCHITECTURES

NVIDIA NGC CUDA TensorRT Hopper MSME Scholars Indexing


MAH Quantum is a Bengaluru-based deep-tech research organization and accelerated computing node. We architect decentralized cognitive AI pipelines, custom quantization frameworks (PTQ/QAT), and high-fidelity quantum emulation layers engineered to maximize compute density across modern GPU clusters. All enterprise infrastructure maps to NGC Org 0963318590610147 on Hopper and Blackwell silicon, bound natively to a cloud-only production staging mandate.


โฌก RESEARCH VERTICALS

[01] Decentralized Cognitive AI โ€” Fault-tolerant, distributed LLM inference pipelines. Multi-node serving architectures with dynamic load balancing across CUDA 12.x cluster topologies. Target: sub-50ms TTFT at 70B+ parameter scale.

[02] Quantization Frameworks โ€” Custom PTQ and QAT pipelines with mixed-precision support (INT4/INT8/FP8). TensorRT-LLM integration with layer-wise sensitivity profiling and calibration tooling for Hopper Transformer Engines.

[03] Quantum Emulation โ€” High-fidelity NISQ-era quantum circuit simulation on classical GPU backends. State-vector and tensor-network simulators with CUDA-accelerated gate kernels. Targeting 40+ qubit emulation at research scale.


โฌก INFRASTRUCTURE & TOPOGRAPHY REGISTRY

HARDWARE_COMPUTE_STREAMS
โ”œโ”€โ”€ NGC_ORG_ID        : 0963318590610147
โ”œโ”€โ”€ TargetArch        : NVIDIA Hopper (H100) ยท NVIDIA Blackwell (B200)
โ”œโ”€โ”€ CUDA              : 12.x
โ”œโ”€โ”€ AccelEngines      : TensorRT-LLM ยท DeepStream Pipeline ยท cuDNN
โ””โ”€โ”€ Deployment        : NGC Verified Container Registry (100% Cloud-Native)

ENTERPRISE_NETWORK_TOPOGRAPHY
โ”œโ”€โ”€ RootGateway       : https://mahquantum.tech (Governance & Corporate Root)
โ”œโ”€โ”€ ScholarLMSPortal  : https://workspace.mahquantum.tech (Internal LMS Node)
โ”œโ”€โ”€ ScholarlyIndex    : https://research.mahquantum.tech (CERN/EU Federated Repo)
โ””โ”€โ”€ CodeSandbox       : https://huggingface.co/mah-quantum

INTELLIGENT_GOVERNANCE_POLICIES
โ”œโ”€โ”€ CodeEnvironment   : Cloud-First Staging Mandate (No Local Machine Execution)
โ”œโ”€โ”€ Documentation     : Manual Faculty-Led AI Audit (<5% Algorithmic Tolerance)
โ”œโ”€โ”€ EvaluationCadence : 1-Year Capstone Pipeline ยท 2-Hour Weekly Architecture Crucible
โ””โ”€โ”€ AuditTransparency : Shared Master Ledger (Real-time Dean & Director Telemetry)

โฌก ACADEMIC PROVENANCE ENGINE

SCHOLARLY_INFRASTRUCTURE
โ”œโ”€โ”€ DOIRegistrar      : Zenodo Automated Minting API (CERN Infrastructure)
โ”œโ”€โ”€ DiscoveryIndex    : OpenAIRE Federated Network / EU Repository Core
โ””โ”€โ”€ SerialStatus      : E-ISSN Board Configuration Phase

โฌก REPOSITORY INDEX

Type Description
model Quantized LLM checkpoints โ€” INT4/INT8/FP8 variants optimized for Hopper TE
dataset Domain-adaptive pretraining corpora and instruction-tuning splits
space Inference demos, quantization benchmarks, emulation visualizers
toolkit PTQ calibration tools, profiling utilities, cluster benchmarking scripts

โฌก INSTITUTIONAL COHORT GOVERNANCE

MAH Quantum operates on a strict, non-spoon-fed corporate structure modeled after top-tier global research labs. Candidates are assigned complex system engineering and deep literature tracks monitored via a four-tier validation layer:

[A] Production-First Mandate โ€” Local machine development loops are banned. All system architectures must deploy as microservices, exposing functional APIs monitored via centralized infrastructure telemetry.

[B] Manual Faculty Vetting โ€” University faculty members manually audit all documentation pipelines to enforce parallel institutional understanding. Hard threshold: <5% AI text generation tolerance.

[C] Master Ledger Matrix โ€” Every development sprint, system metric, and grading evaluation is logged into a secure Master Spreadsheet, granting direct, transparent auditing access to the university Dean and institutional Directors.

[D] Root Admin Veto โ€” MAH Quantum leadership executes random spot-checks on staging repositories, retaining absolute final overwrite and candidate offboarding authority to guarantee prestige integrity and eliminate grade inflation.


MAH Quantum Research Institute ยท Bengaluru, India ยท MSME Registered ยท E-ISSN Config Phase ยท mahquantum.tech