Public Status · Version 2026.08

Independent concept site — eligibility not established

This website does not represent an accredited university, nonprofit research institute, verified principal investigator, or Anthropic partner. Profiles, grants, events, facilities, and affiliations are illustrative unless independently verified.

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BBQ Independent Research InitiativeIndependent research initiative · not an accredited institution · Warsaw, Poland
Operating Form
Online initiative
Domain
bbq.edu.pl
Eligibility
Not established

Proposed Research Directions

Five planning records explore possible work in AI, quantum computing, high-performance systems, formal verification, and computational biology. They do not establish operating laboratories.

Illustrative lead: Prof. dr hab. inż. Janusz Kowalczyk · Proposed area: Department of Computer Science & Intelligent Systems

Laboratory for Machine Cognition & Neural Systems (MCNC Lab)

Investigating deep learning theory, foundational representations, neuro-symbolic reasoning, and verifiable neural architectures on high-performance compute clusters.

Illustrative lead: Dr hab. Elena Markiewicz · Proposed area: Department of Quantum Computing & Information Physics

Laboratory of Quantum Information & Algorithmic Foundations (QIAF Lab)

Exploring quantum algorithmic speedups, tensor network simulations, fault-tolerant quantum error correction codes, and hybrid classical-quantum distributed architectures.

Illustrative lead: Prof. dr hab. Tomasz Wiśniewski · Proposed area: Department of High-Performance Systems & Scientific Provenance

Scientific Provenance & High-Performance Systems Lab (SP-HPC Lab)

Developing exascale workflow infrastructure, immutable provenance tracking, deterministic execution runtimes, and reproducible open science ecosystems.

Illustrative lead: Dr inż. Karolina Nowak · Proposed area: Department of Computer Science & Intelligent Systems

Autonomous Systems & Formal Verification Lab (ASFV Lab)

Creating certified neural network control policies, automated formal verification engines, and provably safe robotic architectures for real-world environments.

Standards for Future Real Work

  1. Verified leadership. Replace synthetic names with real investigators and authoritative host-institution profile links.
  2. Reproducible methods. Register protocols, version code and data, document compute, and report limitations.
  3. Authorized facilities. Publish equipment or cluster access only where the host institution confirms allocation and permitted use.
  4. Documented collaboration. Name partner organizations only with consent and an independently verifiable source.