Alexander Ek, PhD
Research Fellow
Dept. of Econometrics and Business Statistics
Monash University, Australia
Summary
My name is Alexander Ek and I am passionate about data-driven decision-making under uncertainty. My current position mainly focuses on combining optimisation and data science for statistical post-election audits and other work surrounding elections and election integrity.
Research interests include:
- Interdisciplinary research with real-world impact
- Constraint-based optimisation modelling.
- Combinatorial/discrete optimisation, and automated planning and scheduling.
- Operations research/analytics, applied mathematics, and decision science.
- Online/dynamic/real-time optimisation and robust/stochastic optimization.
- Statistics, data science, and machine learning.
- Constraint programming, and other solving technology.
- Logistics, supply chain management, energy systems, vehicle routing, rostering, and scheduling.
- Economics, fair division, fair resource allocation, and social choice theory.
- Game theory, and bargaining theory
- Election auditing, and election security
- Mixed-integer-continous-discrete optimisation, including non-convex optimisation.
Latest News
I presented a talk for our paper titled "Efficient Weighting Schemes for Auditing Instant-Runoff Voting Elections" at the 9th Workshop on Advances in Secure Electronic Voting (Voting'23) of the 28th Int'l Conf. on Financial Cryptography and Data Security, which took place 8 March 2024 in the sunny caribbean city Willemstad, Curaçao.
Link: https://www.ifca.ai/fc24/voting/
I presented a talk for our paper titled Improving the Computational Efficiency of Adaptive Audits of IRV Elections at the 9th Int'l Joint Conf. on Electronic Voting (E-Vote-ID'24), which took place 2 - 4 October 2024 in beautiful Tarragona, Spain.
Link: https://e-vote-id.org/
I presented a talk titled "Post-Election Audits using Machine Learning and Combinatorial Optimisation" in Optimisation Seminar Series at Uppsala University, Sweden.
Link: https://www2.it.uu.se/research/group/optimisation