Our <A+> Alliance Women at the Table 2021 Tech Fellows are announced!
We are incredibly excited to announce the first Women at the Table / <A+> Alliance Tech Fellows, Abhishek Mandal and Sofia Kypraiou !
Visionary colleagues who will explore how machine learning and artificial intelligence can impact the lives of women and girls for good.
We were humbled by the response to our call for Fellows to work with us to pilot algorithms with affirmative actions that would foster gender and race equality into systems.
is a first year PhD student working on biases and imbalances in computer vision datasets and algorithms, jointly supervised by Dr Suzanne Little at Dublin City University and Dr Susan Leavy at University College Dublin, Ireland.
His research work focuses on auditing various social biases such as gender bias, racial bias and stereotypical bias and imbalances present in popular computer vision dataset and pre trained models.
Abhishek will be working with us on primarily on the G-app project to measure gaps in representation, participation and influence of Women in International Assemblies & multilateral fora.
Abhishek will be working on optimizing the novel algorithm so that it truly captures the gender dimensions of international conferences through a blend of Natural Language Processing and Topic Modelling,
and will be liaison for another critical component of the G-app project with Professor Susan Leavy of University College Dublin (UCD) to set up the long term research infrastructure at UCD for the longitudinal research component of the G-app.
Abhishek will also be technology liaison with Women at the Table’s new Tech We Need project as we finish the sociological portion of our research on the needs of women and girls in informal settlements where women and girls will articulate their own innovations and solutions.
Abhishek will then work with Women at the Table and the <A+> Alliance to bring forward the methodology and the technology when we enter into the phase two of the project.
is a final-year master’s student in Data Science at EPFL.
Sofia will be working alongside us to create the first of its kind, stand alone <AI & Equality> Human Rights Toolbox that maps out lines of theory and of practice to make a human rights-based approach a practice in the fundamental set of questions necessary to conceive and write accountable and effective algorithms.
During her fellowship we will deliver a series of EPFL workshops and other University seminars at University of Zürich, ETHZ, and University of Lausanne as Sofia does her Data Science Masters Thesis on the Women at the Table / OHCHR / EPFL project exploring and enhancing this practical toolbox for AI and Human rights with a unique Jupyter notebook with resources, wiki and website.
To see one of Sofia’s many other wonderful projects, check out her project Wikigender:
Created with a team from the Applied Data Analysis course at EPFL, the Wikipedia dataset was extracted and analysed to explore how women are described in Wikipedia. A machine learning model using logistic regression was used and the results were presented as a data story. The paper on the project was accepted at the WikiWorkshop 2020. Explore WIKIGENDER https://wiki-gender.github.io/Last modified: February 21, 2022