Recent highlights (more news can be found here)
- Together with Dan Ashlock (University of Guelph, Canada) and Sansanee Auephanwiriyakul (Chiang Mai University, Thailand), I am organizing a Special Issue on Computational Intelligence Techniques in Bioinformatics and Bioengineering in the IEEE Computational Intelligence Magazine. Here you can find the Call for Papers.
- Together with Jussi Hakanen, Dmitry Podkopaev, and Karthik Sindhya, I am organizing a Special Session on Data-Driven Multiple Criteria Decision Making at MCDM 2017. Here you can find the Call for Abstracts.
- Thanks to the EMO/MCDM Dagstuhl seminar series, together with colleagues I have published two papers in the Journal of MCDA (see list of publications).
Manchester has won the bid to host the forthcoming IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2017). More information to the conference and the CFP can be found here.
- Together with researchers from Biochemical and Chemical Engineering at UCL, I have published a paper on Life-Cycle and Cost of Goods Assessment in Biotechnology Progress. Download paper.
I am Richard Allmendinger, a Lecturer in Data Science at the Alliance Manchester Business School (AMBS), which I joined in September 2015.
Prior to my appointment at MBS, I was a Postdoctoal Researcher and Honorary Lecturer at the Department of Biochemical Engineering and the
EPSRC Centre for Innovative Manufacturing in Emergent Macromolecular Therapies at University College London.
I spent around 4 years at UCL and still collaborate intensively with my previous research and industry colleagues.
Looking even further back in time, I have obtained a PhD in Computer Science from The University of Manchester,
and a (5-year German) Diplom in Business/Industrial Engineering from the Karlsruhe Institute of
Technology (KIT) in Germany and the Royal Melbourne Institute of Technology (RMIT) in Australia.
My research focusses on the development and application of simulation, optimization and machine learning techniques to real-world problems arising in
areas such as manufacturing, biology, economy and logistics. In particular, I am interested in problems that possess features that make a problem difficult
to simulate and/or optimize, such as expensive evaluations, uncertainty, large decision space, constraints, and multiple objectives. Working with industrial
partners on these problems is especially fun. For details on my published work please refer to the publications page.
I enjoy teaching, supervision, and mentoring students as much as research. My current teaching activities include the Coordination and Teaching of a
1st Year UG module on Quantitative Methods for Business and Managament (around 400 students) and an MSc module on Programming in Python for
Business Analytics (around 60 students). I have developed the Python module together with Manuel López-Ibáñez; it is the first time that AMBS is
offering such a heavy programming-focused module. Finally, I am an Academic Advisor for around 30 UG students and 10 MSc students.