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.

Research Engineer (18-month contract or till 14 Jan 2027), SCIS

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

Quantum Finance in Action Workshop 28 Feb 2023

Selected work

Get in touch at paulgriffin@smu.edu.sg