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School of Physical and Chemical Sciences

Dr Dimitris Kalogiros


Lecturer in Data Science

Room Number: G. O. Jones Building, Room 117
Twitter: @dkalogiros
Office Hours: I have no regular office hours. For appointments, please e-mail me.


I am based at Queen Mary University of London as well as the London City Institute of Technology. I am an Applied Mathematician, i.e. a «storyteller» with «a passion for learning» in Engineering, Biology, Medicine, Ecology, Epidemiology, Engineering and Finance. I am also a Fellow of the Higher Education Academy (Advance HE) and a Mental Health First Aider (MHFA England).

I work at the interface of modelling and data. I love teaching, i.e. learning and communicating within the university community (universus = all in one, all together). My aim is to empower students to demystify the world of data by setting them free of the fear of mathematics and programming, while using myself as a bridge for them so that they are inspired to immerse themselves into the art of mathematics and data science.

I really value student support and development, supervision, teaching and mentoring and this is why I take every opportunity to contribute to student development by applying a well-rounded approach and empowering students to grow, progress and develop professionally through their studies in a higher education institution.

I also love offering one-to-one careers advice, support and valuable insights helping them broaden their career horizons.

I am really interested in interdisciplinary research and different approaches to teaching mathematics and data science as well as in public engagement projects aimed at students and the general public.

I was awarded an MEng in Applied Mathematics and Physics from the University of Technology (NTUA) in Athens (Greece) before receiving an MSc in Applied Mathematical Sciences with Biological and Ecological Modelling (with distinction) from Heriot-Watt University in Edinburgh (Scotland, UK). During my studies, I immersed myself in a broad range of topics in the areas of mathematical modelling including mathematical ecology, mathematical biology and medicine, dynamical systems, applied linear algebra, numerical analysis, regression analysis, linear models and designs, computer science along with their applications in physics and engineering.

In late 2012, I joined the University of Dundee, The James Hutton Institute in the UK and Université Catholique de Louvain (UCLouvain) in Belgium to undertake my PhD research in mathematical modelling of plant root systems funded by the European Union forming part of the big EURoot project, when I had the opportunity to work together with ecologists, agronomists, biologists, computer scientists and modellers across 20 research institutes and universities in Europe including Forschungszentrum Jülich (Jülich Research Centre) in Germany as well as ETH in Switzerland, CIRAD (the French agricultural research and cooperation organization working for the sustainable development of tropical and Mediterranean regions) and INRA (French National Institute for Agricultural Research) in France.

After completing my PhD, I continued my studies towards the PG Cert in Teaching and Academic Practice in Higher Education at the Centre for the Enhancement of Academic Skills, Teaching, Learning and Employability at the University of Dundee. In late 2017, I joined the Centre for Mathematical Medicine and Biology at the School of Mathematical Sciences at the University of Nottingham as a Research Fellow in Mathematical Biology. Before joining the School of Physical and Chemical Sciences at Queen Mary University of London, I was a Senior Research Associate in Mathematical Epidemiology at the Bristol Population Health Science Institute at Bristol Medical School and a Teaching Fellow at the School of Mathematical Sciences at Queen Mary University of London.

I am also interested in development and application of novel mathematical and computational methods in a range of biological, ecological and engineering problems. My research interests and skills focus on innovative mathematical techniques, model parameterisation, model sensitivity analysis, numerical analysis as well as building up integrated pipelines for combining data and mathematical models.

Throughout these years, I have been preparing and delivering lectures, tutorials, lab workshops and seminars on a wide range of undergraduate and postgraduate mathematics courses and I have also been involved in assessment and examination papers. I have been responsible for the supervision of undergraduate and postgraduate students from a wide range of Schools (School of Mathematical Sciences, School of Science and Engineering, School of Life Science, School of Education, School of Biosciences, Centre for Geomechanics and Duncan of Jordanstone College of Art and Design) building upon my rich variety of teaching experience from different academic contexts and distilling the best from each of these institutions.

I am also actively involved in initiatives aimed at Early Career Researchers. Among others, I have been the Early Career Researcher (ECR) Representative for the Faculty of Science at the Research Staff Group (RSG), the Mental Health First Aiders (MHFA) Representative involved in EDI committees as well as the Representative for the Postdoctoral Research Fellows when I served on the organising committee of the 1st UK and RoI Postdoc Appreciation Week.

More information can be found on my profile.


I am actively involved in launching new modules in Data Science and Data Analytics at different levels including Foundation programmes. I am part of the Academic team of colleagues for the Data Science Degree Apprenticeship Programme which includes "Introduction to Data Programming" and "The Data Landscape".

I am the Module Organiser for DAT5901 “Data Analysis and Data Solutions” and the new module SPZ401 "Applied Data Science"as well as the Module Associate for DAT5902 "Professional Software and Career Practices".

I serve as Director of student experience for the Data Analyst students in the Data Science Degree Apprenticeship programme and I am an internal examiner in the Professional Discussions endpoint assessment for final year students of the Data Science Degree Apprenticeship programme.

I am organising the Practical Machine Learning Summer School while teaching various modules on Mathematics and Programming aimed at undergraduate as well as postgraduate students. I also co-organise the seminars for the Centre for Education Research.

Among others, I work on module proposals in Data Science and multiple initiatives on Mathematics and Data Science at the School and across the university while supervising students in their projects and dissertations.


Research Interests:

  • Data Science
  • Mathematical Modelling
  • Mathematical Biology
  • Mathematical Epidemiology
  • Mathematical Ecology



  • Z. Vural, A. Avery, L. Coneyworth, D. I. Kalogiros, S. Welham (2020), Trace Mineral Intakes and Possible Deficiencies of Older Adults Living in the Community and Institutions: A Systematic Review, Nutrients 12 (4): 1072


  • D. I. Kalogiros, M. Russell, W. Bonneuil, J. Frattolin, J. E. Moore Jr., T. Kypraios, B. S. Brook (2019), An Integrated Pipeline for Combining in vitro Data and Mathematical Models Using a Bayesian Parameter Inference Approach to Understand Spatio-temporal Chemokine Gradient Formation, Frontiers in Immunology (special issue)


  • D. I. Kalogiros, C. De La Fuente Canto, M. Ptashnyk, T.S. George, R. Waugh, A.G. Bengough, J. Russell and L.X. Dupuy (2018), Morphological and genetic characterisation of the root system architecture of selected barley RCSLs using an integrated phenotyping approach, Journal of Theoretical Biology 447: 84-97


  • D. I. Kalogiros, M. O. Adu, P.J. White, M.R. Broadley, X. Draye, M. Ptahsnyk, A.G. Bengough, L.X. Dupuy (2016), Analysis of root growth from a phenotyping dataset using a density-based model, Journal of Experimental Botany 67 (4): 1045-1058 (special issue)


  • D. I. Kalogiros (2007), Interdisciplinary Framework for Teaching Mathematics and Physics: Case Studies, Proceedings of the 26th Conference of Greek Mathematical Society, Greek Mathematical Society, Thessaloniki, Greece
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