Membership

We are always happy to welcome new members to the chapter. If you're interested in joining us, the first step is to become a SIAM member (see below). General members have no responsibilities, but if you are interested in taking a more active part in the chapter then please get in touch with one of the committee members. We're very open to any suggestions, and encourage new members to get involved!

Joining SIAM

Joining SIAM gives you exclusive access to SIAM journals, specialised SIAM activity groups and funding opportunities for conferences across the world. To join, click here and make sure you select the Heriot-Watt University & University of Edinburgh Student Chapter! Once you have registered please send us an email at the address below to get involved locally.

Contact Us

Please don't hesitate to get in touch with us at siam-ima@maths.ed.ac.uk if you have any questions, comments or suggestions. Our committee members would also be happy to receive your email personally, or have a chat at one of our events.

Committee

John
Panagiotis Kaklamanos

p.kaklamanos@sms.ed.ac.uk

President

My research focuses on the theory and applications of dynamical systems that feature multiple timescales, such as the Koper model from chemical kinetics and the Hodgkin-Huxley equations from mathematical neuroscience. In parallel, I also look into the existence and stability of travelling waves in reaction-diffusion equations with cut-off functions.

John
Atish Dixit

ad181@hw.ac.uk

Treasurer

My research is related to efficient statistical forecasting using Deep-Learning Reduced Order Models. In particular, I employ reinforcement learning algorithms to solve optimal well control problem in reservoir engineering.

Jonna
Jonna Roden

j.c.roden@sms.ed.ac.uk

Committee Member

I am modelling (industrial) processes, which can be described by particles that are submerged in a fluid, such as in nano-filtration, brewing or printing. Moreover, I am looking at the optimization of these models using optimal control techniques and implement these computationally.

David
David Torkington

dt45@hw.ac.uk

Committee Member

My mathematical research is motivated by the need to handle energetic materials (materials with large stores of chemical energy) with care. I develop models to describe a sample's thermo-mechanical response to a given low-energy mechanical insult, focusing on the physics underlying the material's behaviour, so as to inform safety principles. When analysing the models, I tend to opt for pen-and-paper techniques, such as matched asymptotics and PDE methods.

Matthew
Matthew Holden

mdh4@hw.ac.uk

Committee Member

I am working on new data-driven computational methods for Bayesian inverse problems, motivated by problems in image processing. These allow us to exploit the performance of machine learning while retaining the flexibility and interpretability of rigorous statistical models.

General Members

Cassandra Khan
Andrés Miniguano Trujillo

Faculty Advisors

Kostas Zygalakis
Ahmed ElSheikh

Former Members

Lukas Eigentler (President 2019-20)
Tiffany Vlaar (Vice-President 2019-20)
Daniella Ayala Garcia (President 2018-19)
Mark Ashworth (Vice President 2018-19)
Gissell Estrada-Rodriguez (Secretary 2018-19)