Excited to announce starting a new position at IBM Quantum as the first ever AI for Quantum Product Owner, leading initiatives at the convergence of artificial intelligence and quantum computing.
Excited about Forbes article highlighting IBM Quantum work at the intersection of AI and quantum computing. The integration of AI and Quantum Computing has the potential to transform industries and advance quantum computing capabilities significantly.
Announcing multiple major releases at the convergence of AI and quantum computing: beta version of Qiskit transpiler service (unveiled at THINK24), research paper on AI-powered transpiler passes, and Qiskit Code Assistant with LLMs and the Qiskit HumanEval benchmark. Both projects recognized through IBM Quantum Challenge.
Published research paper on training specialized LLMs for quantum computing code generation using Qiskit. Addresses unique challenges in quantum programming, including scarcity of quantum code examples and rapid field evolution. Our model outperforms existing state-of-the-art quantum computing models.
Published research demonstrating integration of Reinforcement Learning into quantum transpiling workflows for Qiskit transpiler service. Achieves near-optimal circuit synthesis and routing with significant performance improvements over traditional optimization methods, handling Linear Function, Clifford, and Permutation circuits up to 65 qubits.
Published peer-reviewed research comparing classical and quantum approaches to natural language processing in Expert Systems with Applications. Demonstrated that quantum NLP models can obtain the same or better results for simpler text classification tasks, with experiments utilizing up to 7 qubits across multiple classification scenarios.
Extremely proud of the massive Qiskit SDK v1.0 release including two projects from my team: the Qiskit Transpiler with AI transpiling passes and the Qiskit Code Assistant. This full-stack software for quantum computing brings together cutting-edge AI and quantum technologies.
Published systematic literature review on quantum machine learning and its applications in Computer Science Review journal. Analyzed 94 studies from 2017-2023, identifying two primary algorithm categories and highlighting image classification as a key application area, while noting that quantum hardware improvements are necessary for QML full potential.
IBM Quantum team recruiting AI Engineer interns based in Spain to work on introducing new AI-based capabilities in the software stack, including AI circuit transpilers compatible with Qiskit and LLM-powered code assistants. Interns will support AI model training, deployment, software service development, and MLOps work.
Honored by major announcements from IBM Quantum Summit 2023, including IBM Heron chip with 3-5x performance improvement, 1,121-processor Condor system, operational Quantum System Two, Qiskit 1.0 release, Quantum Serverless beta, and AI integration for automated code development and enhanced transpiler tools.