Who we are
I am Kritika Pandey, working in Quantum Algorithms. I hold the NUS-DELTARES Fellowship at NUS, Singapore, and the Q-Master Fellowship in Quantum Matter at EUR QMat, University of Strasbourg, France. I have four published papers in top materials journals, and I hold a patent that was later developed further and commercialised as USESORB. I have previously pitched my Quantum Fraud Detection work to DBS Bank, Singapore, and I am currently developing that work into a formal venture.
I am Vandan Patel, an Application Developer at IBM with a strong interest in quantum computing and quantum software development. I work with Qiskit and have experience building quantum algorithms, simulators, and quantum random-walk systems. I was a mentor at Qiskit Global Summer School 2026 and enjoy exploring the intersection of quantum computing, AI/ML, and software engineering.
I am Adithya Phani Thota, an AI Developer at Tata Consultancy Services (TCS), where I design and deploy AI solutions for the healthcare and operations domains. I served as a mentor for the QWorld’26 QML project and the Quant-a-thon hackathon. My core specialisation lies in quantum software development using SDKs like Qiskit, Amazon Braket, and PennyLane, alongside active open-source contributions to repositories including Qiskit Machine Learning, qBraid, CUDA-NVIDIA, and Amazon Braket.
About the project
Small energy differences often decide which structure, composition, or electronic state is favoured in materials chemistry, but hybrid quantum-classical workflows introduce noise that can make these close rankings unstable without that instability being visible in the final result. We are developing a framework to characterise where that instability comes from and how reliable a ranking-based conclusion really is, using quantum simulators to test the findings, with real hardware validation planned next. The aim is to make reliability measurable, not just reported.