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The last Women in STEM Networking event took place on Monday 25th April. You can find out more below. Dates are tbc for 2022-2023.

After a successful online event last year, we are looking forward to enabling the community to meet face-to-face. The event provides a chance to meet Oxford's Women in Science, Engineering and Maths societies, speak with inspiring women and find out more about the many University support networks available.

This event has been so well received in the last two years and we are keen to provide an opportunity that allows as many Women in STEM to meet, network, learn and be inspired by their peers.

To take part as a speaker at this exciting event, please see more information below!

Oxford Town Hall, St. Aldates, Monday 25th April 18.00 - 20.30

Women researchers at a networking event© John Cairns

speakers 2022!

Last year we had fantastic contributions from across the full range of STEM departments - please see the below list for examples of speakers and topics.

We are now looking for inspiring women to speak to our attendees about their applied science/research/programmes, and the impact they have on our daily lives. Talks will once again follow a 'Soapbox' style format with each speaker engaging with visitors for short periods of time, using nothing but props and engaging information (no PowerPoints!).

Queries? Please email Louisa to register an interest in speaking or Carlyn Samuel [she/her] at the Department of Zoology, who is coordinating this aspect and can answer any specific questions.




Sara Khalid

NDORMS, Senior Research Associate in Biomedical Data Science and University Research Lecturer

Biomedical Data Science Health Informatics

Machine Learning for Planetary Health            

An introductory talk covering my work on machine learning, remote monitoring, and health informatics with applied examples e.g. mining big data in healthcare, remotely tracking plastics from land to sea, cancer and the environment.

Irina Chelysheva

, Paediatrics, Medical bioinformatician, Post Doc

Immunology, vaccinology, bioinformatics          

Why having a dream is more important than having a plan?               

I will tell you my career development story as someone who never planned to come to Oxford, neither had a plan to do vaccine research. Now I am in the team, which developed a vaccine from COVID, and I am one of those who worked all these months on Oxford COVID vaccine. As a single mum of a child who suddenly became disabled in one day - I was not even sure if I manage to finish my PhD in a foreign country (Germany) without academic support - my supervisor gave up on me seeing this life-story. I was open to all those challenges in my life and never gave up on myself. I got success, publications, teaching, opportunities for supervision, and mentoring... My only dream was to contribute to science, which would save lives. And even so, none of my plans became true, my dream did.             

Daria Tserkovnaya

Nuffield Department of Population Health, DPhil student

Digital Epidemiology

Navigating your ship  in a sea of Misinformation?                 

In my talk, I will tell about my interdisciplinary path into STEM, which started in humanities and social sciences with my first degree in medical journalism and ended in public health and computer science. I will talk about my choices fueled by the desire to help as many people as I can, and the pursuit of making complex qualitative issues quantifiable. I will cover my work in Covid19 digital epidemiology and will focus on the history of mistrust in vaccines and science, misinformation online, and digital innovation in the age of epidemics.         

Susie Speller

Materials, Professor of Materials     

Superconducting materials    

Superconductors and how to make them super                    

My talk will focus on the materials science of the real technological superconductors such as the ones that are used in magnetic resonance imaging systems found in hospitals and the Large Hadron Collider.  I will also talk about the more complex superconductors that are needed in nuclear fusion confine the plasma that is as hot as the sun.  

Mila Fitzgerald

Engineering Science, DPhil Student / Graduate Scientist Scientist                                           

Nuclear Fusion

Renewable Fusion                 

My talk will cover the current state of nuclear fusion. This consists of two main branches, magnetic confinement fusion and inertial confinement fusion, both with their own challenges.     This will lead into why nuclear fusion is always '20 years away', and some of the projects taking place globally to solve it. I will expand on my own work at First Light Fusion and with my research group, and the problems we are tackling.    The final topic will cover the importance of generating renewable energy from a range of sources. Nuclear fusion shouldn't be the final answer, it is a piece of a far larger puzzle in reducing our carbon emissions to net zero by 2050. 

Ping Lu

Department of Engineering Science, Post-Doctoral Research Assistant                                

Biomedical image analysis    

Geometric Deep Learning for Characterisation of Cardiac Motion 

Whilst cardiac motion analysis currently plays a role in the diagnosis of heart conditions, it is limited by the ability of visual assessment for regional wall motion abnormalities in magnetic resonance imaging MRI sequences and that the existing Deep Learning method is based upon the assumption that each individual area being measured moves independently from other areas in the heart. This assumption is clearly flawed and the use of geometric deep learning (GDL)  is a natural improvement because it recognises that each area being measured is dependent upon and influenced by other areas of the heart, clearly a more realistic model that should improve the diagnosis of heart conditions.

Yvonne Huiqi Lu

Engineering Science, Daphne Jackson Research Fellow, Fulford Junior Research Fellow

AI in Patient's Health and Care - at a turning point

Healthcare systems worldwide are entering a new and exciting phase: ever-increasing quantities of clinical data are routinely collected, concerning all aspects of patient care, throughout the life of a patient. These Big Data in health and care are a unique combination of genomics, noisy real-world clinical data, and many other data sources. Such analysis poses substantial challenges, including the high dimensionality of the data along, missing values, data heterogeneity, and scalability problems. Consequently, standard methods of medical data analysis are typically unable to handle data of this complexity. One of the most significant benefits of deploying machine learning methods is their ability to continually learn and improve from real-world experience (in data format). This is a key strength of machine learning, in which healthcare can move from reactive treatment to preventative medicine. As a result, innovations arising with machine learning approach can facilitate rapid clinical treatment, transform a hospital-only treatment pathway into a cost-effective home-based combined alternative, and improve the overall quality of health and care.

Sophie Schauman

NDCN, Postdoctoral Researcher in Neurovascular Image Reconstruction                                                      

Magnetic Resonance Imaging Physics and Signal Processing    

How I fell in love with MRI 

I will tell my story of how I first got into imaging when I realised and was fascinated by how much maths and science there was in imaging. Then on to how MRI is different from other types of imaging (e.g. x-ray or optical) and why I think it's cool. And finally a little bit on my research into how MRI acquisition can be accelerated and why that is important.

Akanksha Ahuja

Computer Science, Student

Applied Computer Science in Scientific Domains

Computing in Physics Experiments                        

How scientific needs have driven innovation in computing and how the physics disciplines use different areas of computer science in their experimental design

Heba Sailem

Engineering Science, Sir Henry Wellcome Research Fellow     

Biomedical Engineering

Biomedical engineering applications in cancer discovery       

I will highlight the role of biomedical engineering in curing major diseases including cancer. I will give an overview of my work and how I combine different disciplines from statistics, and machine learning, to genetics and data science to study cancer development. One important thing about my job is that it is not only about having the technical skills but also the creative thinking and how bring different skills together. I feel that young women can benefit from my story as it show them how engineering can be diverse and help to develop solutions to important problems.    

Julia Migne

Zoology, Programme Manager                             

Using Optimism as a Tool to Empower People to Act for Nature                                           

Join this talk to find out how Conservation Optimism is using optimism as a powerful tool to reframe the conservation narrative and how we can all put it into action and empower others to act for nature.


Women researchers at a networking event© John Cairns

The Women in STEM networking event is run on behalf of:

  • OxWoCS (Oxford Women in Computer Science)
  • Women in Engineering
  • Women in Zoology
  • Women in Physics
  • Mirzakhani Society (Maths)
  • Women in Chemistry 
  • Women in Materials
  • OxWest (Oxford Women in Engineering, Science and Technology)
Oxford Women in Computer Science logo Oxford Women in Engineering logo Oxford Women in Physics logo
Mirzakhani Society logo Oxford Women in Chemistry logo Women in Data Science Oxford logo