Rosman is a researcher who specialises in mobile intelligent autonomous systems. He is also a visiting lecturer at the School of Computer Science and Applied Mathematics at the University of the Witwatersrand, where he leads the Robotics, Autonomous Intelligence and Learning laboratory.
Rosman holds a PhD degree in informatics from the University of Edinburgh.Rosmanâ€™s research interests focus primarily on learning and decision-making in autonomous systems, in particular studying how learning can be accelerated through abstracting and generalising knowledge gained from solving previous problems. He also works in the area of skill and behaviour learning for robots.
A large part of his research focuses on transferring knowledge and constructing skill hierarchies in reinforcement learning, as well as extending these ideas to scenarios with rich sensory information and partial observability. He is also the chair of the Institute of Electrical and Electronics Engineers, South African joint chapter of Control Systems and Robotics and Automation.
Expertise: Robotics; Autonomous intelligence; Machine learning; Decision theory
Claire is currently a lecturer and Administrative Officer at UTAMU in charge of Elearning. Her background is in computer science specializing in Artificial Intelligence and Network Security. She carries a great enthusiasm for data science and machine learning with a zeal of harnessing the potential of AI in improving service delivery. She is also part of the Artificial Intelligence and Data Science Research Lab Makerere University as a mentor and a research assistant.
Mutembesa is a Project Head & Lead Researcher for an Adhoc Surveillance Project focusing on the smart-phone application tool kits that has been developed by the mcrops team to facilitate and provide automated diagnosis and improved vector & symptom measurement for Cassava viral diesease and pests it also looks at crowdsourced Crop health data through an Ad-hoc Surveillance system. Daniel is also an Instructor of Oracle & Database Systems Eng. at the Department for Professional Skills Development, Makerere University and an Assistant Tutor of Dr. Ernest Mwebaze at the Department of Computer Science College of Computing & information systems at the same University.
Neema Mduma is a Tanzanian academic and computer engineering professional, she is currently an Assistant Lecturer and a PhD candidate in the school of Computational and Communication Science and Engineering at the Nelson Mandela African Institution of Science and Technology. Her focus is on supporting education and presently she is conducting a study on developing a data-driven approach for predicting student dropout in secondary schools.
Jeremy is a software engineer by profession with a passion for machine Learning. He works as a Research Assistant at the AI Research Lab where he develops software solutions to address challenges faced by the health and agricultural community.
Benjamin Bimanywaruhanga is an AI enthusiast , practitioner and researcher. He serves as the lead at feyti analytics a company that uses AI to solve problems in Africa. He is passionate about Generative adversarial Networks, natural language processing and computer vision. He is also a pharmacist at Mulago hospital. He has passion for health care technology.
Ezabo Baron is the Chair for the IEEE Uganda Section and Co-founder of the Woxsan City project, the worldâ€™s first artificial intelligence-powered virtual trade city. He serves as the Coordinator for AI Neural Network Systems in the project and former Robotics Research Coordinator at Nakawa Vocational Training College (NVTC), a college under the Ministry of Education and Sports Uganda. He was responsible for leading a team of innovators from the institute to the Annual East Africa Robotics Challenge Cup held in Nairobi, Kenya an initiative of Japan International Cooperation Agency (JICA). Also, he is the Volunteer Outreach Coordinator for the IEEE Photonics Society in Uganda and Dark Skies Africa Volunteer for the United States National Science Foundationâ€™s (NSF) Optical-Infrared Astronomy Research Laboratory in Uganda.
Pascal has more than 15 years of experience across diverse industries such as Software Engineering, Finance, Marketing and Oil and Gas and He is currently working for OneFi | Carbon (previously Paylater) as Head of Data Science at the London-based headquarters office. Expert in algorithm conception and feature engineering using domain knowledge, He offers a strong expertise in high-level complexity Data Science, Machine Learning modelling and deployment, Data Architecture solutions and design. He is overall a strategic thinker for complex problem solving with a strong understanding of business. Besides Data Science related to smartphone data, mobile technology within fintech and digital banking, He has other areas of specialisation and interests such as Distributed Machine Learning, Edge Computing, Network Data Science, Graph Databases and Algorithms, IoT Data Analytics, Business & Technology Innovation, Alternative Data Strategy as well as Data Science applied to Social Sciences and Behavioural Analytics. Pascal is also a regular contributor, mentor and speaker for AI & Data Science Education, Universities Programs and NGOs all over the world.
Timothy has more than 5 years in the field of Information Technology and experience in major areas of Computing, Networks. He is currently working for Uganda Technology and Management University (UTAMU) as a Lecturer in the School of Computing and Engineering. He has growing interest in the areas of Machine Learning, Data Science, Cloud Computing and Blockchain Technology.
Kris is currently a postdoc at Mila, working in Yoshua Bengio's lab on problems related to Humanitarian AI. He completed his PhD in Statistics at Stanford University, advised by Susan Holmes. His thesis was on Discovery and Visualization of Latent Structure with Applications to the Microbiome. Kris was a 2016 Data Science for Social Good fellow and helped organize projects with Statistics for Social Good and DataKind SF.
He is most interested in questions at the interface of statistics (reasoning about uncertainty) and machine learning (data-driven systems), especially those that would enable applications in heterogeneous settings. Kris thinks that sharing reproducible workflows and accessible distillations is as important as making discoveries and proposing algorithms. His ideal researcher is an insightful scientist, as well as a skilled technician. He occasionally post notes to his blog. Many of his projects are public on github.
Silver Springs Hotel
Plot 76A/D, Portbell Road
In Uganda there are quite few researchers working on different aspects of artificial intelligence from machine learning, algorithms, logic-based and scientific computing perspectives. INDABAXUG is intended to bring together researchers, industry and academia interested in these areas of AI.
The central theme of INDABAXUG is combinations of, and synergies between, machine learning and symbolic AI. The workshops will focus on recent trends, aiming at finding common ground and interests that point forward to the coming years.
The outcome of the workshops will ideally be to identify where the field as a whole is heading and to pinpoint how we can use the competences in Uganda to exploit the potential synergies and stay at the front in research, teaching and industrial collaboration.
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Deep Learning IndabaX-Ug is a locally-organized
conference that seeks to spread knowledge and
capacity in Machine Learning across the African
continent. Deep Learning events bring together
students, researchers and industry experts who
are passionate about the field of Artificial
intelligence and its growth.
Since 2018, a total of 39 IndabaX events have been organized in different countries across Africa, growing the community by over 2,000 attendees.
This year, the conference will be organized by Uganda Technology and Management University (UTAMU) and over 200 participants are expected to be part of this event that will take place in Kampala, Uganda at Springs hotel, Bugolobi from 28th-29th May 2020.
The conference will provide an opportunity for researchers and practitioners to share their understanding and use of Artificial Intelligence (AI), in solving societal problems, as well as to look at possibilities for setting-up new trends in this area under the theme, â€œThe social Impact of AI"
Furthermore, there will be an online hackathon provided by Zindi (a data science competition platform with the mission of building the data science ecosystem in Africa) for country engagement.