I am a Postdoctoral fellow at the Matter lab, working with Professor Alán Aspuru-Guzik in the Department of Computer Science and Chemistry at the University of Toronto. My research focuses on near-term quantum computing algorithms. I received my Bachelor’s degree in Telecommunications Engineering from Urmia University in Iran and my Master’s degree in Mechatronic Engineering from Politecnico di Torino in Italy. During my Ph.D., I developed distributed algorithms for the Internet of Things to optimize manufacturing processes of factories, and I believe that quantum computing will play a key role in the future of manufacturing.
My current research interests include quantum-inspired optimization, machine learning, quantum computing and computation, and quantum machine learning. I am particularly interested in applying the Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimization Algorithm (QAOA) to solve complex optimization problems in the industry. In addition, I am exploring the use of quantum-inspired models to solve real-world problems in finance and machine learning.
As the computer society continues to evolve and reboot its technologies and protocols, it is crucial that we prepare our applications for quantum computing in the industry. I believe that this technology will positively impact our world by optimizing industrial processes and reducing energy consumption. Therefore, I am currently working on machine learning and optimization methods to apply quantum computing to solve some of the industry’s most challenging problems. In the future, I envision that quantum technologies will play a key role in the manufacturing industry, which will be coined Industry 5.Q. after quantum in Industry 4.0.
My Current Research Interest
- Quantum Inspire Optimization
- Machine Learning
- Quantum Computing and Computation
- Quantum Machine learning
- Internet of Things (IoT)
Applications that I am intrest:
- Drug discovery
- Industry 4.0 (Future of Factory)
- Industrial optimizations
- Self-driving labs
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