Paul R Griffin, Associate Professor in SMU.
Quantum Computing in Practice
Quantum Computing in Practice
Look out for my new chapter in the - Handbook of Blockchain, Digital Finance, and Inclusion, Volume 3:
Handbook of Blockchain, Digital Finance, and Inclusion, Volume 3 - 1st Edition | Elsevier Shop
Quantum Technologies in Decentralization
PAUL GRIFFIN, RUDY RAYMOND, AND TSUYOSHI IDE
1. Introduction
2. Overview of quantum technologies
3. Quantum attacks on blockchains
4. Quantum improvements for blockchains
5. Quantum distributed average computation
6. Concluding remarks
My new 5 days public course on Quantum Computing Essentials for Financial Services is now available.
Article on our QML for credit rating paper: Quantum Machine Learning for Credit Scoring
New paper - Exponential qubit reduction in optimization for financial transaction settlement
Next job disruptor, quantum? | The Straits Times - Podcast
#MySecurityTV📺 Adopting Quantum for Blockchain - interview on Adopting Quantum for Blockchain - YouTube
Quantum computing is emerging from being purely theoretical and quantum hardware is increasing in larger capacity, higher quality and more accessible. The properties of quantum computing are uniquely different than conventional computing and the potential for disruption is huge in many areas especially for solving non-deterministic problems.
While there are many potential applications of quantum computing in many industries, I am researching the application of this technologies for finance in particular. Current work focusses on credit scoring and DLT consensus in collaboration with industry partners with externally funded projects.
Apply here : https://smu.recruiterpal.com/career/jobs/v51lo
Job Description
The candidate will be responsible for conducting research on non-universal quantum computers in finance. Successful candidate will be part of an active research team led by Prof Paul Griffin from School of Computing and Information Systems, Singapore Management University.
Candidate's core responsibilities are:
Review classical and quantum approaches to stochastic Asset-Liability Management and Risk Parity Portfolio Construction
Design the hybrid quantum/classical process flow
Setup the development environment
Develop and test the code
Report on the results
Other Duties as assigned
QUALIFICATIONS
Bachelor's or Master's degree in Computer Science or Finance with strong computational focus
Proficiency in programming software/languages such as Python is required
Proven track record and professional experience with classical optimization frameworks (e.g., CVXPY, Gurobi)
Ability to break down complex problems and design effective solutions
Familiarity with benchmarking experiments
Innovating new approaches and thinking outside the box
Applicants with research publications in computational science will be advantageous
Ability to work cooperatively as part of a small, agile academic research team is essential
Self-motivated individual who can work independently and collaboratively with team members
"QuLTSF: Long-Term Time Series Forecasting with Quantum Machine Learning", Hari Hara Suthan Chittoor; Paul Robert Griffin; Ariel Neufeld; Jayne Thompson and Mile Gu, https://www.scitepress.org/PublicationsDetail.aspx?ID=D2dkFAwUa0k=&t=1
"Exponential Qubit Reduction in Optimization for Financial Transaction Settlement", Elias X. Huber, Benjamin Y. L. Tan, Paul R. Griffin, Dimitris G. Angelakis, https://arxiv.org/abs/2307.07193
Quantum Machine Learning for Credit Scoring, Nikolaos Schetakis, Davit Aghamalyan, Michael Boguslavsky, Agnieszka Rees, Marc Raktomalala, Paul Griffin,https://www.mdpi.com/2227-7390/12/9/1391
Review of some existing QML frameworks and novel hybrid classical–quantum neural networks realising binary classification for the noisy datasets, N. Schetakis, D. Aghamalyan, P. Griffin & M. Boguslavsky, https://www.nature.com/articles/s41598-022-14876-6
An application framework for implementing quantum computing, by Griffin, Paul R.; Boguslavsky, Michael; Huang, Junye; Kauffman, Robert; Tan, Brian R.. (2021)
P. Griffin and R. Sampat, "Quantum Computing for Supply Chain Finance," https://ink.library.smu.edu.sg/sis_research/6923/
A Practical Comparison of Quantum and Classical Leaderless Consensus, Paul Robert Griffin, Dimple Mevada, to be published, https://ink.library.smu.edu.sg/sis_research/7175/
Masters of IT in Business (MITB) - Quantum Computing in Financial Services - 10 weeks Curriculum / Graduation Requirements | School of Computing and Information Systems (SMU)
Quantum Computing in Financial Services MITB
Techinnovation 2022