Overview
As part of SGInnovate's Developers Meetup series, we are reaching out to developers who want to share their knowledge and expertise on various technologies.
Whether you are a budding or experienced developer, or just curious, come explore the realm of Quantum Computing and Machine Learning with these insightful presentations by developers!
Date 24 June 2020, Wednesday
Time: 11:00am - 12:00pm (UTC +8)
Programme:
11:00am - 12:00pm:
- Introduction to Quantum Computing through TensorFlow Quantum and Cirq by Archana Iyer, Graduate Research Student, National University of Singapore (NUS) and Women Who Code Leadership Fellow
Uncover the basics of Quantum Computing and Machine Learning from a developer's standpoint. Set your fundamentals straight by learning about Quantum Computing circuits, qubits and their behaviour. Discover the major players in the market and their accessibility to developers, with a highlight on recent developments in Quantum Supremacy by Google.
Following the brief introduction to Quantum Computing, delve into Quantum Machine Learning by exploring how to create Quantum circuits using Cirq, as well as creating hybrid Quantum-classical neural networks using TensorFlow Quantum.
- Exploring Horizons of Quantum Machine Learning by Kishor Bharti, Theoretical Physicist, Centre for Quantum Technologies
One of the desired outcomes of Quantum Machine Learning (QML) is to perform Machine Learning more efficiently. Discover from a researcher's point of view into the meaning of QML, its motivations and the pioneering contributions in this area. Learn about the practical and foundational implications of QML in science and society, and the many challenges and unanswered questions which the QML field faces.
Speaker's Profile:
Archana Iyer, Graduate Research Student, National University of Singapore (NUS) and Women Who Code Leadership Fellow
Archana is a graduate research student at the National University of Singapore (NUS) and is a Women Who Code Leadership Fellow.
Her area of research covers the application of deep learning techniques to smart grids. As a part of her study, Archana utilises various Google frameworks, tools and hardware. Her expertise includes TensorFlow, TFLite, Colab, TPU and Edge TPU board.
As a course instructor for Udacity's "AI for Edge IoT Nanodegree", she teaches her students how to choose the right hardware when deploying their model at the edge. Archana has also contributed to many women in tech organisations and is passionate about conducting talks, workshops and being a mentor to budding developers.
Kishor Bharti, Theoretical Physicist, Centre for Quantum Technologies
Kishor is a theoretical physicist working at the Centre for Quantum Technologies (CQT). He has a keen interest in Quantum Machine Learning, combinatorial optimisation and Quantum information. His research works have been published in high-impact journals such as Physical Review Letters. He also leads CQT's Quantum Machine Learning journal club, where they discuss findings from around the world.
