Sign-Up Link: https://forms.office.com/e/UAVpHCAabq

One of the advantages of using sequent systems as a framework for logical reasoning is that the resulting calculi are often simple, have good proof theoretical properties (like cut-elimination, consistency, etc) and can be easily implemented, eg using rewriting.

Hence it would be heaven if we could add axioms in mathematical theories to first order logics and reason about them using all the machinery already built for the sequent framework. Indeed, the general problem of extending standard proof-theoretical results obtained for pure logic to certain classes of non-logical axioms has been the focus of attention for quite some time now.

The main obstacle for this agenda is that adding non-logical axioms to systems while still maintaining the good proof theoretical properties is not an easy task. In fact, adding naively axioms to sequent systems often result in non cut-free systems. One way of circumventing this problem is by treating axioms as theories, added to the sequent context. This is already in Gentzen’s consistency proof of elementary arithmetic. Now the derivations have only logical axioms as premises, and cut elimination applies.

But we can do better by transforming axioms into inference rules. In this talk, we will propose a systematic way of adding inference rules to sequent systems. The proposal will be based on the notions of focusing and polarities. We will also discuss how our framework escalates to hypersequents and systems of rules, and the application of this to modal logics, proofs explanation and SMT solvers.

This is a joint work with Dale Miller, Sonia Marin, Marco Volpe, Francesca Poggiolesi and Yoni Zohar.

Seeking OxWoCS Alumni! We are excited to announce our first alumni social, please spread the word to any alumni pals! Register your interest using this form and save the date. If you can't make this date but keen to join for future events, please also fill in the below form.

Sign up for alumni events here: https://forms.gle/7VowhQzYfaSPpBCX6

If you've enjoyed some of the OxWoCS events and would like to be more involved join the committtee by filling out the form to stand for a position! The OxWoCS AGM is a friendly, inclusive environment and we encourage everyone who has enjoyed the OxWoCS events to get involved. As a personal aside, being part of this committee has been one of the best and most rewarding things I've done at Oxford, and I've made amazing friends on the committee. So do consider standing for a position :)

If you have questions and want to know more, we are hosting a 'meet the committee' lunch in the Computer Science department in the week before the AGM, so come along and ask any questions you might have.

Sign up: https://forms.office.com/e/3NPcyGdV2r

We are incredibly excited to announce the ninth Oxbridge Women in Computer Science Conference, which will be held on the 29th of April 2023 in Cambridge, UK. The annual conference brings together computer scientists of all age-groups and career stages at Cambridge and Oxford, with the aim of encouraging collaboration via formal and informal discussion. Highlights of the conference include talks by key speakers from academia and a panel-discussion on overcoming obstacles faced by minorities in computer science.

Registration

Everyone is welcome to register for attending the conference, including people from other Universities. We will prioritise members of the Women@CL and OxWocs networks due to capacity reasons. Remaining places will be allocated to members of the computing department and then on a first-come-first-serve basis.

There is no registration fee; and breakfast, lunch, refreshments and a conference dinner will be provided free of charge. Coach transportation will be provided free of charge for all participants travelling from Oxford. The deadline for registration is the 22nd of March 2023 via the following form.

Call for Submissions

We strongly encourage current undergraduates, postgraduates, research assistants and postdocs to submit abstracts of their research for presentation, demonstration and/or the poster session. We have two types of presentations of different lengths. Full presentations will be 20 minutes followed by 10 minutes of Q&A. Lightning talks will be 5 minutes. We also accept submissions for demonstrations/workshops. There will be no proceedings for the conference, so posters and papers can be under submission for other conferences/workshops. Submission of abstracts is done via this form (different to the registration form).

The Reviewing Committee will review all presentation and poster abstracts. Notifications of acceptance will be sent by the 29th of March.

We will be booking a coach to and from Oxford so need numbers ASAP, so please sign up at your earliest convenience! If you have any questions, please email me: madeleine.wyburd@cs.ox.ac.uk

The aim of the conference is to promote research within the community and get valuable feedback in a constructive and friendly environment. We hope to see many of you join us for the conference!

For more information please visit https://www.oxbridge2023.com/

International Women's Day Lunch

Join us for a lunch in the Department on the 8th of March to celebrate International Women’s Day together! The lunch will start at 1 pm in the atrium, and will be provided by Vaults & Garden! Please register by Wednesday the 1st of March, so we have an idea of numbers for the food order.

As we expect a lot of interest in this event, this event is primarily aimed at people that identify as women or non-binary.

Sign up before 1st of March: https://forms.office.com/e/Ms53wtxecF

Intelligent systems in cancer care

Abstract: The breakthrough successes of deep learning-based solutions in various fields of research and practice have attracted a growing number of researchers to work in the field of medical image analysis. However, are we really solving the right problems?

A key component of Intelligent medical systems is their perception. While the current state of the art in interventional healthcare largely relies on conventional imaging modalities, we challenge common practice by proposing intelligent medical systems based on novel biophotonics-based techniques that go beyond human perception with modern machine learning methods.

Promising as they may appear, however, these systems can only be as ‘intelligent’ as the validation that was conducted on the algorithms used. Although validation is the basis for measuring all scientific progress as well as a key prerequisite for successful clinical translation, current common practice in the entire field of medical image analysis is heavily flawed, with strategies and metrics used frequently not reflecting the underlying medical problem. We challenge these shortcomings and propose solutions compiled by an international consortium of medical and machine learning experts from over 70 institutions worldwide.

Computer science meets big data and healthcare: a journey from PhD in machine learning to Associate Professorship in labour monitoring

Abstract: This talk will focus on both the career journey and the science behind it, building up to the Oxford Labour Monitoring group that Georgieva is leading. She journeyed from a BSc in Applied Mathematics in Sofia (Bulgaria), through a PhD in Machine Learning and Artificial Neural Networks in Portsmouth (UK), to a junior post-doc at Oxford in fetal monitoring based at the JR Hospital, to now as a successful leader of a multidisciplinary research group, which is about to test for the first time at the bedside her data-driven decision support tool for triage at the onset of labour (the Fit for Labour test).

Across the globe, each day, we continue to have term babies arrive at delivery wards in good condition in utero, only to be born hours later with neurological injuries. The consequences are profound and life-long for the babies, parents, siblings, and their wider family. Clinical staff involved in the obstetric management are severely impacted in multiple ways. On the other hand, Caesarean section to avoid oxygen deprivation during labour carries multiple risks for mother, fetus, future pregnancies; as well as costs. But achieving safe spontaneous delivery is sometimes challenging due to poorly understood and complex fetal physiology, and often, conflicting healthcare needs for mother and baby.

Oxford Labour Monitoring is committed to preventing injury of babies during labour and delivery, caused by lack of oxygen in utero - rare but devastating events. Our work will potentially benefit families, clinicians and healthcare systems by reducing brain injuries, the deaths of babies during labour or after birth and unnecessary medical interventions in childbirth.

Our multidisciplinary team is focused on developing and implementing novel technologies for continuous monitoring and risk assessment of the fetus in-utero at the onset of and during labour. We employ a range of data-science methods to provide automated and data-driven analysis of physiological signals alongside clinical risk factors (for example, fetal or maternal age, co-morbidities, maternal temperature, etc). We already have a prototype decision support tool, derived from a large birth cohort (100,000 term deliveries) by systematic analysis of computer-based fetal monitoring characteristics (a time series called CTG) and clinical risk factors in relation to perinatal outcomes. In tests 'off-line' with the data, the current prototype has shown to perform better than clinicians in clinical practice. We have developed a tablet app that runs OxSys in real time data at the John Radcliffe Hospital, analysing all CTGs as they are being taken (maternity admission unit, delivery suite or wards). We are continuously improving the app's interface in collaboration with the clinicians. The app takes in information from the user about any risk factors if present and modifies the analysis accordingly."

Speaker Bio of Prof. Antoniya Georgieva: "I have developed my career in biomedical research, building on my expertise in machine learning, computing and mathematics, but specialising in intrapartum (in labour) fetal monitoring. I am now leading an ambitious programme to develop data-driven decision-support software in this clinical field. I am uniquely positioned to achieve this by working with the world’s largest and most complete birth cohort of routine labour data (100,000 deliveries).

I obtained a BSc (Hons) in Applied Mathematics from the Technical University of Sofia (Bulgaria) and a PhD in Computer Science from Portsmouth University. I joined the Nuffield Department of Obstetrics and Gynaecology and the Institute of Biomedical Engineering at Oxford for a post-doctoral position in 2007. In 2016 I was awarded a NIHR Career Development Fellowship to grow my independent research group. In the same year, I became a Research Fellow at Wolfson College and also joined the newly formed Big Data Institute at Oxford.""

Celebrate Christmas with OxWoCS and enjoy a festive formal dinner at St Peter’s College with like-minded friends. Tickets will be released on 30th Oct at noon so set a reminder in your calendar (https://www.eventbrite.co.uk/e/438683262447)!

Dinner Run-down:
18:45-19:30 Drinks reception & Networking
19:30-22:30 Formal dinner (3 course dinner with St Peter's mints, truffles and coffee)

Due to the popularity of this event and limited capacity, we initially ask only women and non-binary people to purchase tickets.

Save the date!

OxWoCS is teaming up with Cohere AI to organize an event to learn about career opportunities at the company 🙂

A little bit about the company, Cohere is kickstarting a new chapter in machine learning by giving developers and businesses access to NLP powered by the latest generation of large language models. Come join us to learn more about the company, followed by a delicious complimentary dinner 😋