A French startup pioneering innovation in Quantum Technologies, Post-Quantum Cryptography, and Artificial Intelligence, bridging science, technology, and industry.
To pioneer innovation in Quantum Technologies, Post-Quantum Cryptography, and AI by building a global network to accelerate quantum-secure and AI-driven infrastructures through open-source platforms and partnerships.
To bridge science, technology, and industry, empowering secure quantum technologies via collaborative research and openness for global impact in cybersecurity, optimization, and innovation.
Associate Professor at Indian Institute of Technology Bombay
Researcher in Quantum Chemistry, Quantum Computing
Professor in Physics, Swinburne University of Technology
Researcher in Adiabatic Quantum Computation, Quantum Optimization, Quantum Finance & QKD
Design variational and hybrid quantum algorithms for optimization, chemistry, AI, and PQC. Platforms: OpenVQE, OpenVQA, OpenHybrid.
Develop, benchmark, and validate quantum-resistant cryptographic algorithms (ML-KEM, ML-DSA) with integrated AI-based fault detection.
Build AI-driven validation frameworks for automated PQC testing, anomaly detection, and side-channel resilience.
Provide expert consulting in quantum technologies, PQC migration, and hybrid system integration, supported by strong industrial partnerships.
Deliver hands-on workshops, online courses, and mentoring through the OpenVQA Hub, engaging 40+ engineers and global advisors.
Organize and participate in international quantum events, innovation hackathons, and research conferences across Europe, Asia, and the Middle East.
Collaborate with Eviden (Atos Group), Zanasi & Partners, and academic institutions on European and global quantum innovation projects.
Maintain active open repositories on GitHub for PQC, quantum chemistry, and AI–quantum hybrid tools.
Advise on quantum adoption strategies, governance, and regulatory frameworks for public and private sectors.
Develop integrated AI–Quantum simulation environments, PQC verification pipelines, and hybrid cloud-based SDKs.
WYW specializes in variational and hybrid quantum algorithms for optimization, chemistry, AI, and secure computation. Our in-house platforms include:
| Platform | Focus Area | Key Features | Link |
|---|---|---|---|
| OpenVQA Hub | Quantum Education & Algorithmic Research | 40+ engineers and 10 advisors developing VQE/VQA-based hybrid algorithms. | www.openvqa.com |
| OpenVQE | Variational Quantum Eigensolver Framework | Open-source toolkit for chemistry and optimization simulations. | GitHub – OpenVQE |
| OpenHybrid | AI–Quantum Hybrid Development | Upcoming integrated suite combining AI, PQC validation, and variational algorithms. | openhybrid.net |
These platforms provide foundational infrastructure for PACT-PQC: scalable testing, algorithm integration, and hybrid AI-assisted PQC validation.
WYW's PQC division has implemented NIST PQC standard algorithms, focusing on ML-KEM (CRYSTALS-Kyber) and ML-DSA (Dilithium), both lattice-based and quantum-resistant mechanisms.
Example: The "ML-KEM Wrapper" developed at WYW provides a Python interface for Kyber variants (512/768/1024) using liboqs. It includes benchmarking, security validation, and integration utilities for PQC simulation and performance testing.
📦 GitHub Repository: https://github.com/WYW-PQC/Post-Quantum-Cryptography
Capabilities include: Implementation and benchmarking of PQC algorithms. Automated validation pipelines (encapsulation/decapsulation correctness, performance profiling). Leakage and side-channel analysis using dudect, valgrind, and ct-verif integration. Generation of reproducible datasets for PQC analysis. Hybrid deployment strategies: combining classical + quantum backends.
These efforts promise resilience against quantum adversaries, ensuring that PQC solutions remain robust in the era of NISQ (Noisy Intermediate-Scale Quantum) and Fault-Tolerant Quantum Computing (FTQC).
WYW actively develops AI-driven automation tools for post-quantum cryptographic validation and side-channel mitigation. Within the context of PACT-PQC, WYW proposes to lead AI-related components such as: AI-assisted Fault Attack Detection (ALFA) using deep learning and signal classification. Automated Benchmarking Framework (CAT-PoC) integrating AI for anomaly detection and pattern recognition. Development of explainable AI modules to ensure transparency in PQC verification workflows.
WYW is demonstrating real quantum advantage across high-impact computational domains, starting with finance and expanding toward complex industrial and climate applications.
Proven Achievements Our hybrid and fully quantum models have consistently outperformed classical AI systems in precision, recall, and F1 score benchmarks.
Key demonstrations include: Fraud Detection — detecting anomalies with higher precision under noisy, imbalanced datasets Credit Scoring — improving risk classification accuracy over classical models Time Series Forecasting — capturing chaotic patterns for more reliable financial trend predictions
Experiments show 5–10% accuracy improvements using hybrid quantum architectures, validated across multiple public datasets and simulation environments. Even modest accuracy lifts translate to measurable operational and financial gains at scale.
Core Capabilities The developed models are adaptable to multiple sectors: Climate and Weather Systems: applying quantum-enhanced forecasting for temperature, rainfall, and extreme event prediction Energy and IIoT Optimization: reducing computational cost in carbon-efficient systems through low-energy quantum circuits Sentiment and Behavioral Modeling: leveraging quantum neuro-fuzzy architectures for market and social sentiment analysis
Our approach integrates quantum feature engineering, noise-resilient ansatz design, and other techniques to maintain model robustness and consistent performance across diverse datasets.
Academic Validation:- The research team has established peer-reviewed credibility through IEEE Journal publications in 2025, providing independent validation of their quantum advantage claims: 1. Optimizing low-energy carbon IIoT systems with quantum algorithms: Performance evaluation and noise robustness. 🔗 https://arxiv.org/pdf/2503.00888 2. SentiQNF: A novel approach to sentiment analysis using quantum algorithms and neuro-fuzzy systems. 🔗 https://arxiv.org/pdf/2412.12731
Led by Dr. Mohammad Haidar, WYW combines a strong academic foundation with global scientific impact.
| Metric | Details |
|---|---|
| Publications | 28+ peer-reviewed papers (Quantum Computing, PQC, QED, Spectroscopy, Quantum Chemistry) |
| Citations | 352+ citations across journals and conferences |
| Research Focus | Variational Quantum Algorithms, PQC, Hybrid Systems, Spectroscopy, Quantum Field Theory |
| Education & Mentorship | Supervision of MSc and PhD students, international collaboration across Europe, Middle East, and Asia |
| Invited Talks / Keynotes | Spain, France, Dubai, Vietnam, USA, Saudi Arabia |
| YouTube Lectures (Educational Outreach) | Talk 1 • Talk 2 • Talk 3 • Talk 4 |
This combination of research leadership and open educational outreach positions WYW as an AI–Quantum connector between academia, startups, and enterprise.
| Expertise Domain | Key Capabilities |
|---|---|
| Quantum Computing | Quantum chemistry simulation, hybrid algorithms, error mitigation, NISQ to FTQC transition analysis. |
| Post-Quantum Cryptography | Lattice-based cryptography (ML-KEM, ML-DSA), side-channel hardening, AI validation of PQC algorithms. |
| AI for Security | Automated anomaly detection, signal classification for leakage analysis, explainable AI pipelines. |
| Software Development | Open-source toolkits (Python, Qiskit, Cirq, liboqs), GitHub-based CI/CD for research deployment. |
| Quantum–AI Integration | Hybrid learning models combining quantum circuits with classical AI layers. |
| Education & Training | Online courses, workshops, technical documentation, mentoring next-gen quantum engineers. |
WYW explores quantum chemistry simulations using variational and hybrid algorithms to model complex molecular systems efficiently on near-term quantum devices. Under the scientific guidance of Professor Rahul Maitra, a leading expert in quantum chemistry and quantum computing, we are developing next-generation Variational Quantum Eigensolver (VQE) frameworks within OpenVQE and OpenHybrid. This work enables high-accuracy energy calculations, reaction modeling, and chemical property prediction — essential tools for quantum-assisted materials and drug discovery.
WYW focuses on designing quantum optimization algorithms that solve large-scale industrial and scientific problems more efficiently than classical counterparts. Working alongside Professor Rahul Maitra, we are integrating Quantum Approximate Optimization Algorithm (QAOA) and hybrid adaptive approaches into real-world use cases such as logistics, scheduling, and machine learning optimization. These methods form the foundation for quantum-enhanced AI systems capable of addressing complex combinatorial problems in PQC, data security, and resource management.
With the support of Professor Tien Kieu, a distinguished physicist renowned for his work on Quantum Adiabatic algorithms and the foundations of quantum computation, WYW is exploring the use of adiabatic quantum processes for secure computation and cryptographic resilience. AQC is a quantum computing model that solves problems by leveraging the principles of quantum annealing and adiabatic processes. It is an analogue approach but can be tailored to quantum circuits. It is a powerful specialised tool for optimization and sampling, constrained by the need for slow operation and susceptibility to noise, but with a clear and valuable pathway to near-term practical applications, especially when used in hybrid systems. Development and applications include: Hybrid Quantum-Classical Solvers, Material and Molecular Simulations, Feature Selection and Hyperparameter Tuning in ML and AI, Logistics Optimisation, Drug Discovery and Development, Financial Modeling (portfolio optimisation and arbitrage), etc.
OpenVQA: Tools for ML, optimization, finance like routing, portfolio management.
OpenHybrid: AI-PQC for hybrid models, secure crypto systems.
Post-Quantum Cryptography, encryption resilience, and secure communication systems.
Quantum chemistry applications for molecular modeling and drug optimization.
Quantum optimization and quantum finance models for portfolio management, risk assessment, and high-speed trading.
Simulation of new materials, superconductors, and nanostructures using variational quantum algorithms.
Universities and training institutions adopting OpenVQA and OpenVQE for hands-on learning, certification, and workshops.
Collaborations with Eviden (Atos Group), NVIDIA, D-Wave, and other hardware manufacturers for benchmarking and hybrid algorithm testing.
WYW is a new and growing company, actively building partnerships and funding pipelines across Europe, the Middle East, and Asia. Our activities are currently supported through a combination of research grants, workshops, consulting services, and industry collaborations.
Funding and Collaboration Channels: Applied for European innovation funding under PQC and Quantum Technology calls. Active collaborations with Zanasi & Partners, Eviden, and academic partners in France and the Gulf region. Engagement with governmental and institutional funding ecosystems, including Horizon Europe and national quantum programs. Ongoing consultancy and advisory projects in Saudi Arabia on Quantum Technology adoption and national strategy.
Clients and Activities: Conducting paid workshops and summer schools, such as the Quantum Summer School in Paris (December 3), offering participation at €200 per professional and €80 per student. Delivering consultation sessions for research institutions, banks, and defense-related organizations interested in PQC and quantum readiness. Collaborating with financial institutions and startups exploring Quantum Finance and Optimization with platforms such as D-Wave. Developing strategic partnerships in Asia and the Middle East, including ongoing discussions for joint educational and research programs.
| Partner / Sponsor | Area of Collaboration | Link |
|---|---|---|
| Eviden (Atos Group) | Sponsor of OpenVQA; partner for HPC, cybersecurity, and quantum tool integration. | https://eviden.com |
| Sorbonne Université & TotalEnergies | Quantum simulation collaboration (2021–2023). | https://wires.onlinelibrary.wiley.com/doi/10.1002/wcms.1664 |
| OpenVQA & OpenVQE Communities | Open research collaboration, 40+ engineers contributing to hybrid quantum research. | www.openvqa.com |
Connect with WYW for software developments, consulting, or joint research projects that push the boundaries of quantum technology.
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