Keynote Speakers
Prof. Nilton Correia da Silva
Co-ordinator, Artificial Intelligence Laboratory (AILAB) ,
University of Brasília - UnB
Brasília, Brazil
​AI Meets Healthcare: Transforming Health Ecosystem with Data-Driven Solutions and Intelligent Systems
​As we witness an era of unprecedented technological advancement, Artificial Intelligence (AI) and Machine Learning (ML) are poised to revolutionize healthcare. The convergence of AI, IoT, and data science offers a unique opportunity to accelerate digital transformation in healthcare environments. This presentation explores the potential of AI-driven solutions to enhance healthcare systems by integrating intelligent nodes from diverse data sources through Multi-Agent AI systems, which facilitate real-time decision-making and seamless information flow.
Furthermore, we have delved into the development of advanced decision support systems using Retrieval Augmented Generation (RAG), enabling highly accurate medical decisions. Generative AI has also contributed significantly to the automation of manual tasks often performed by skilled labor. By leveraging these technologies, we can pave the way for smarter, data-driven solutions that will not only improve operational efficiency but also deliver better patient outcomes. In this opportunity, we will highlight the current moment as a turning point in healthcare innovation, where AI can accelerate transformation and deliver smart, integrated solutions for the healthcare ecosystem.
Dr. Myo Thida
Senior IEEE member
Assistant professor of Computer Science, Bard College, United States
Building Equitable Futures with Artificial Intelligence
As artificial intelligence continues to shape nearly every aspect of society, we face a profound challenge—and opportunity: how can we ensure that AI advances not only technological capability, but also social equity, human dignity, and global inclusivity?
In this keynote, I reflect on my journey developing real-world AI applications for underserved communities, particularly in low-resource language settings, while also reimagining how we teach and learn AI in this new era. My work spans from predictive models that forecast patterns of gender-based conflict to designing technical resources and building community-based training programs—always with a focus on using AI to serve human needs, not overshadow them.
This talk will explore three key areas:
1. AI for Social Good – Case studies such as forecasting gender-based violence and conflict trends show how data-driven approaches can be harnessed for advocacy, intervention, and human rights work.
2. AI in Low-Resource Languages – Why language equity matters, and what it takes to develop inclusive NLP tools and machine learning applications for underrepresented linguistic communities.
3. AI Education in 2025– What it means to teach AI in 2025 when foundation models are widely accessible. Critical thinking, context, and creativity are no longer optional—they are essential. I’ll share how interdisciplinary education can cultivate the next generation of AI practitioners who are not only skilled but also socially responsible.
We don’t just build AI models—we build tools for people.
Whose lives are we improving, and how?