Sudeshna Das earned her PhD from the Centre of Excellence in Artificial Intelligence, Indian Institute of Technology Kharagpur, India. Her doctoral research concentrated on AI-driven Gender Bias Identification in Textbooks. She is currently a Postdoctoral Fellow at the Department of Biomedical Informatics, School of Medicine, Emory University, USA, where she is part of the Sarker Lab. Her research interests lie at the intersection of AI and Social Good, with a particular focus on gender equity in education and healthcare. Prior to her doctoral research, she studied computer science and engineering, leading to an MTech from the National Institute of Technology Durgapur, India, and a BTech from West Bengal University of Technology, India.

Dr. Chao’s current research focuses on supporting students in resource-constrained environments to learn to program using mobile devices. Computer programming is a core course in most IT-related degrees. The ubiquity of mobile phones makes them valuable tools for students to practice programming on their phones. However, limitations of mobile phones, such as small screens and small keypads, impede their use as typical programming environments. Dr. Chao is designing supporting techniques to enable learning of computer programming on such limited devices.

Since obtaining her Ph.D. in Computer Science from the University of Cape Town in 2015, Dr. Chao has received several recognitions for her academic achievements, demonstrated leadership skills, and community involvement. She was a winner of the 2014 Google Anita Borg Memorial Scholarship and a recipient of the 2015 Schlumberger Faculty for the Future award for women in STEM. She was also named as one of the 2017 Quartz Africa Innovators, was selected as a 2017 Techwomen Fellow, was awarded a Leadership ‘Zuri’ award for her positive contribution to the Kenyan community in 2018, and was named as one of the 2018 Faces of Science in Kenya. In 2019, Dr. Chao was recognized by Okay! Africa as one of the women of African descent who are making a positive and impactful contribution to the youth in their communities. In addition to publishing her work in several international peer-reviewed journals and conference papers, Dr. Chao is also actively involved in the local and international Information Technology scene and is an active advocate for quality education and research. She was one of the committee organizers for the 2019 Mozilla Festival and is Founder and Program Lead for KamiLimu, an impactful structured mentorship program for university students studying computer science.

Temitope Adeniyi is a PhD researcher at Cleveland State University working at the intersection of quantum computing, artificial intelligence, and data-driven healthcare. Her research focuses on quantum sensing, reinforcement learning, and machine learning for early disease detection. She is the Programme Lead at the Africa Quantum Consortium, advancing talent development and research collaboration across Africa. Her work has been recognized through selection to UNESCO’s Quantum 100 and as the 2024 Femtum Quantum Rising Star Award winner, and she actively supports quantum education through university teaching and high school outreach initiatives.

Tumai is a PhD candidate at the University of the Witwatersrand, South Africa, advancing African precision public health through integrated disease modelling using machine learning. Her research develops Africa-specific cardiometabolic disease risk prediction models that challenge Eurocentric approaches, which leave African populations underserved by global health innovation. As DS-I Africa Partnership and Outreach Working Group Co-chair (2026), she fosters collaborations between the consortium and key data science players across Africa. She is also passionate about mentoring young scientists.

As a computer science undergraduate at Philander Smith University, she has co-led a team to design an award-winning AI-driven literacy-support prototype to assist students in Detroit and has worked on a National Science Foundation project to develop an intelligent learning support AI-powered iOS app.

Sudeshna Das earned her PhD from the Centre of Excellence in Artificial Intelligence, Indian Institute of Technology Kharagpur, India. Her doctoral research concentrated on AI-driven Gender Bias Identification in Textbooks. She is currently a Postdoctoral Fellow at the Department of Biomedical Informatics, School of Medicine, Emory University, USA, where she is part of the Sarker Lab. Her research interests lie at the intersection of AI and Social Good, with a particular focus on gender equity in education and healthcare. Prior to her doctoral research, she studied computer science and engineering, leading to an MTech from the National Institute of Technology Durgapur, India, and a BTech from West Bengal University of Technology, India.

Ângela Gonçalves originally trained in Computer Science at the University of Coimbra in Portugal, where she focused on the development of biologically inspired artificial intelligence algorithms. Following a research stay at the European Space Agency, she was awarded a fellowship to pursue a PhD in Computational Molecular Biology at the European Bioinformatics Institute, earning her doctorate from the University of Cambridge in 2012. During her PhD, she investigated the evolution of gene expression regulation during mammalian speciation and developed some of the earliest computational methods for RNA sequencing analysis.

She went on to conduct postdoctoral research in population genomics at the Wellcome Trust Sanger Institute. In 2017, she received a pump-priming grant from the Cambridge Cancer Centre Early Detection Programme, initiating work on the use of menstrual fluid as a model system for tracking somatic mutations in normal tissues over time.

Since 2018, Ângela has led a joint wet- and dry-lab research group at the German Cancer Research Center (DKFZ) in Heidelberg. Her research focuses on modeling healthy aging and the evolution of somatic mutant clones in normal and pre-malignant tissues, with the goal of developing methods for cancer prevention and early detection. Since 2022, she has also served as co-lead of the Digital Cancer Prevention group at the National Cancer Prevention Center. Since 2024 she is full Professor at Heidelberg University.