Artificial Intelligence and Research Techniques

Chapa’s first training seminar

Chapa is a Financial Service and Global Data Engineering Company that is here to help users understand their specific requirements concerning metrics and analysis, Chapa gives services in identifying data needs for businesses and products. To enable data-driven decisions across Chapa, it also builds and provides efficient and scalable data pipelines.

In March of 2021, Chapa Financial Technologies SC. and the Ethiopian Artificial Intelligence Center held a training seminar.

The training seminar - consisted of 4 phases, each lasting a month - and covered the basic concepts behind Artificial Intelligence (AI), its definition, and background. How to solve problems by using algorithms and the application of AI was also an important topic covered during the seminar. This was done by showing how to implement it in various sectors such as electricity, construction, transportation, agriculture, disaster response, and more. It was a discussion-based seminar and all lectures and discussions were recorded.

It had covered the fields of Machine Learning, Deep Learning, Convolutional Neural Networks (CNNs) alongside their application in today’s modern industry - which is the application of machine learning in several real-world problems and issues. 

The relevance of Machine Learning and understanding it, received particular focus and emphasis during the seminar, covering the concepts of scoping, developing, and deploying a project to make ends meet and deliver the desired result.

The lectures were instructed by four honorable academics, each playing a significant role in the seminar. 

Professor Yoshua Bengio from Mila (Montreal, Canada), who is known for being a pioneer in Deep Learning and one of the most reputable experts in the realm of Artificial Intelligence. 

He has served as a professor in the Department of Computer Science and Operational Research at Université de Montréal since 1993. Besides being CIFAR’s Learning in Machines & Brains Program Co-Director, the professor is also the founder and scientific director of Mila, the Quebec Artificial Intelligence Institute, which is recognized for being the world’s largest university-based research group in deep learning. 

Thanks to his several high-impact contributions, in 2018 Professor Bengio ranked as the computer scientist with the newest citations worldwide. The following year, jointly with Geoffrey Hinton and Yann LeCun, he received the ACM A.M. Turing Award, ‘the Nobel Prize of Computing’, for conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing. 

Another honorable appearance was made by Dr. Freddie Kalaitzis from the University of Oxford (Oxford, United Kingdom). He is a Senior Research Fellow and Theme Lead of ML for Earth Observation and Remote Sensing in the Oxford Applied and Theoretical Machine Learning lab of Oxford University. Dr. Kalaitzis is also an ML & Project Lead at NASA's Frontier Development Lab (FDL) and the (part-time) ML Lead of Trillium Technologies, the R&D production company behind FDL.

Since FDL US 2020, Dr. Kalaitzis has been an ML & Project Lead for project Waters Of The United States (WOTUS), in partnership with the USGS, Planet, Maxar, Google Cloud, and NVIDIA, towards the ultimate vision for mapping all flowing water on Earth, at near real-time, by fusing LiDAR sensors and daily very high resolution (VHR) satellite imagery. He started his journey with FDL 2019 as a mentor, helping teams super-resolve solar magnetograms and predict GPS disruptions induced by solar weather. 

Up until April of 2020, he was an Applied Research Scientist in the AI for Good lab of Element AI in London, focusing on applications of ML and statistics that enable NGOs and nonprofits. During this period, he led the Multi-Frame Super-Resolution research collaboration with Mila Montréal, which was awarded by ESA for topping the PROBA-V Super-Resolution challenge. 

The seminar was also fortunate enough to have had the presence of Qin Wang from CUHK (Shenzhen, China) who is a graduate from Sun Yat-sen University (China) and currently a researcher and a Ph.D. student at The Chinese University of Hongkong (Shenzhen). He is a champion of several local and international machine learning competitions. His research fields include Bioinformatics, Machine Learning, Image Semantic Segmentation, Weakly Supervised Learning, and Game Development. In addition, he has also worked in Alibaba, Tencent, and Netease Games.

The fourth noteworthy appearance was made by Chapa’s own Israel Goytom (Addis Ababa, Ethiopia). He is the co-founder and CTO of Chapa Financial Technologies SC. In advance of co-founding Chapa, he was a researcher at NBU-MSE Lab, supervised by Tao Weidong, working on two-photon polymerization and their smart printing methods. And prior to that, he was working in Yoshua Bengio's lab Mila Montréal on problems related to Humanitarian AI, Multi-Frame Super-Resolution, and climate change with Kris Sankaran and Yoshua Bengio. Primarily being interested in physics and fintech real-world problems and machine learning and particularly applying deep learning algorithms to solve numerous physics and financial sector issues that have been a huge concern in Africa, his research interests also lie in machine learning, computer vision, data mining, and deep learning in particle physics.

Seminar Setting

Participants represented a large portion of the availed projects. Trainees were required and expected to attend all classes and participate in them. All global presentations with foreign attendees were held on Zoom.

To attend this seminar, prospective participants were required to gain permission from instructors. The training also required attendees to at least have previous experience in Machine Learning. However, practical experience in real-world problems was not part of the requirement - although dedication, passion, and willingness to learn more about it was noticeably appreciated.