PhD students Sampriti Mahanty and Chimdimma Onah are both presenting papers at IDEAL 2019 in Manchester.
The paper "Evolving controllably difficult datasets for clustering" by PhD student Cameron Shand received a best paper nomination at GECCO 2019.
We have recently released an updated version of the multi-objective clustering algorithm MOCK. The accompanying paper has been accepted for publication in the IEEE Transactions on Evolutionary Computation and the code is available here.
Dr. Julia Handl
Email: julia.handl at manchester.ac.uk
Short bio: I am an Alan Turing Fellow and Professor in the Decision and Cognitive Sciences Research Centre at the University of Manchester.
Prior to this I was an MRC Special Training Fellow at the University of Manchester and the University of Washington.
I hold a PhD from the University of Manchester, a Masters degree in Computer Science from the University of Erlangen-Nuremberg and a Bachelor (Hons) degree from Monash University.
My research interests relate to the development and application of advanced analytical techniques (concretely, optimization methods,
machine learning and simulation) for complex real-world problems, and I have on-going collaborative projects in a number of different
application areas, both within and outside academia. Projects at Manchester Business School are typically focused around logistics, forecasting or segmentation problems.
Many of the methods I work with have applications across disciplines, and I am involved in a number of cross-faculty collaborations at the University of Manchester e.g. through initiatives such as the Data Analytics and Society and the Quantitative Biology CDT (as the methodological rather than domain expert).
Key research themes:
One of my core research areas is data science, and I have a particular interest in the use of multiobjective optimization in the
development of improved machine learning techniques. This work investigates the advantages of multiobjective
formulations for a number of different classification problems including clustering, cluster validation, feature selection
and semi-supervision. The overall goal of this work is to increase the scalibility, flexibility and uptake of
multiobjective data-mining approaches. We are further exploring the benefits of multi-objective clustering in applications related to
- Forecasting of analogous time series
- Market segmentation
- Customer relationship management
- Healthcare reference costs
More details are available here on the topics of cluster validation,
cluster generators and the multiobjective clustering algorithm MOCK.
Optimization and, specifically, the design and application of meta-heuristics for single and multi-objective
problems present a second overarching theme of
my research. Research interests include the development of suitable heuristic
optimization techniques e.g. for:
- Simulation-optimization (and robustness) in production planning
- Green vehicle routing
- Fragment-assembly methods for computational structure prediction
Some of my early research
focused on clustering techniques that are inspired by the behaviour of
real ant colonies, and I conducted my Masters thesis in Marco Dorigo's lab at IRIDIA.
Publications: Most of my publications can be accessed from my Google Scholar citation profile.
Funding: Current and previous funding sources include EPSRC, MRC, Gottlieb-Daimler and Karl-Benz foundation, German Academic Exchange Service, Alliance Donation and Innovate UK.
Service and Leadership:
I am an Associate Editor for the IEEE Transactions for Evolutionary Computation (CABS 4), and on the editorial board of Evolutinary Computation (CABS 3).
Having previously acted as PGT Coordinator for my division and program director of the MSc Business Analytics: Operations Research and Risk Analysis (ranked 2nd in the UK, QS Ranking 2020), I am currently serving a three year term as Associate Head of Teaching for the MSM division. In 2016/2017, I was awarded AMBS' Academic of the Year award, based on nominations by colleagues.
I have a passion for teaching and regularly contribute to teaching on core modules of the MSc Business Analytics (e.g. Simulation & Risk Analysis and Data Analytics), as well as the supervision of
MSc dissertations. At undergraduate level, I am involved in modules covering Quantitative Methods and Data Science fundamentals.
Within Alliance Manchester Business School, I have been awarded Academic of the Year for Postgraduate Taught Programmes (nomination by students) on two occasions (2016/2017 and 2018/2019). I was recently (2019) nominated by students for the Faculty of Humanities' Outstanding Teaching Award. The Blackboard pages designed for one of my undergraduate modules has been regularly shortlisted for the Faculty's Best on Blackboard competition, and received the award of Highly Commended in the academic year 2014/2015. I enjoy activities related to the public communication of science and technology, e.g. in my role as a STEM ambassador I have been running a weekly Scratch club, introducing coding to children at primary school level, for > 4 years and this continues to be a highlight of my week.
Current and previous members of my group:
PhD / DBA Students (supervisions and co-supervisions):
Research Associates, Research Fellows and Visitors:
Some of these (celebrating the award of a PhD to Juan) are included in the picture below.
- Thu Trang Dinh
- Andrea Brake
- Sampriti Mahanty
- Camilla Mapstone
- Basma Albanna
- Chimdimma Onah
- Emiao Lu (now working as a Data Scientist for Tencent in China)
- Juan Diaz Esteban (now Professor in Ecuador)
- Raza Khan (now in an Academic Post in Pakistan)
- Shaun Kandathil (now Research Associate at UCL)
- Chris Myers (now Enterprise Risk and Capital Management Strategist)
- Andrew Webb (now Research Associate at the University of Manchester)