Carnegie Mellon University

Professor Manuela Veloso on Machine Learning and AI at the Next Einstein Forum 2018

April 03, 2018

Manuela Veloso Presented at NEF2018, University of Rwanda and CMU-Africa

Byron Spice
  • Director of Media Relations
  • 412-268-9068

NEF2018 - Professor Manuela Veloso Professor Veloso, Head of the Machine Learning Department at Carnegie Mellon University was invited to present at the Next Einstein Forum 2018 which took place this year in Rwanda, Africa where several Scientists and WorldLeaders were invited to present at the Global Gathering 2018 - #NEF2018 to speak about Machine Learning, Artificial Intelligence, Computer Science, Mathematical Sciences, Education, Healthcare, Social Sciences, etc.

NEF Global Gatherings are exciting biennial global events where the world of Science and Technology meet on Africa soil to unveil breakthroughs in Science, respond to existing challenges, look and plan towards the future.

NEF2018 - Professor Manuela Veloso

Professor Veloso’s presentation at the Next Einstein Forum 2018 was on “Leveraging Artificial Intelligence to Improve Health Outcomes” – Where she emphasized that improving health outcomes could rely on several technologies and practices including biotechnologies, patient care, preventive care, etc. Recently, with the emergence of big data and Artificial Intelligence. Health data is being mastered to improve health outcomes in surveillance, cancer, heart disease, etc. Several challenges exist in implementing AI in Healthcare.

NEF2018 - Professor Manuela Veloso

She also gave a public lecture on “Artificial Intelligence and Machine Learning – Current Research and Future Perspectives” – at the University of Rwanda which was attended by more than 500 students. Finally her last presentation was on CMU-Africa where she gave a lecture on “Understanding Artificial Intelligence.”

Professor Veloso’s was impressed with Rwanda, and mentioned that Kigali and its surroundings are deeply beautiful, on last note she emphasized that Rwanda’s people showed great enthusiasm for AI and Machine Learning.

Machine Learning Department -