UCL DEPARTMENT OF COMPUTER SCIENCE

DR. DANIEL J HULME

Academia

Following the completion of my undergraduate degree, was awarded an Engineering Doctorate in Virtual Environments, Imaging and Visualization (UCL EngD VEIV). My research topic was Computational Complexity, and my thesis title was "The Path to Satisfaction: Polynomial Algorithms for SAT". My thesis.

The aim of my research was to understand what makes some problems tractable while others intractable, to cross-fertilize old and new ideas in computational complexity and graph theory, spawning interesting and novel methods that extend the principles used to solve restricted NP problems, to develop and implement new techniques that can be applied to many of the available scientific and industrial problems.

The Engineering Doctorate is a four-year postgraduate award intended for the UK's leading research engineers who want a managerial career in industry. It is a radical alternative to the traditional PhD, being better suited to the needs of industry, and providing a more vocationally oriented doctorate in engineering.

I was previously a Research Associate in Information Security (Cyber Security & Cryptanalysis), researching areas such as Security in complex commercial systems; Cyber security and Cryptography; Smart cards and smart card protocols; Proprietary cryptography as a source of imitability and the primary defense against hackers in business ecosystems; Marketing for security technologies; Adoption barriers for security products and technologies; Economics of security and economics of insecurity, insurance, prices, bets and derivative markets in information security; Risk management; Fraud in financial markets and financial institutions; Data security and compliance in financial institutions.

I also hold a research and teaching position in Management Science & Innovation in the area of Business Analytics and Open-Innovation, working with UCL to extend our understanding of innovation, and how large organisations and government can best to utilise open-innovation tools and methodologies to collaborate with SME's and academia. I assist UCL in building collaborative and commercial relationships with external organisations in research areas such as BigData, Visualisation, Analytics, Sustainability, Optimisation, Algorithms and Security.

I also help develop and teach New Venture Analytics, an MSc level module to enable nascent entrepreneurs gather and assess evidence, communicate the structure of their business reasoning, defend it to adversarial challenges and demonstrate that they have done a thorough and robust analysis. The objectives are to equip students with knowledge and skills in the areas of data analysis, structuring decisions, building decision models, risk assessment, and decision making under uncertainty, and gain an understanding in strategic, tactical and logistical decision-making.

My research interests range from Computational Complexity to New Economic Models, BigData Analytics to Business Decision Making.


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