Sysco Labs hosts machine learning hackathon | Sunday Observer

Sysco Labs hosts machine learning hackathon

 The winning team - ‘Team Rotis’
The winning team - ‘Team Rotis’

Sysco Labs hosted its inaugural Hackathon, ‘Overclocked 2019’ for developers across its offices with a focus on machine learning.

The finale saw teams developing and presenting their solutions to a panel of judges consisting of Uthayasanker Thayasivam, Ph.D., an expert in machine learning and how it applies to data science and big data mining; Sankha Muthu Poruthotage, Ph.D., co-founder of Linear Squared and a force behind many of Sri Lanka’s large-scale analytics initiatives; and VP Engineering, Head of Enterprise Architecture Group (EAG) at Sysco Labs, Hiranya Samarasekera.

“This event gave our engineers an opportunity to showcase their business problem solving acumen and prowess in the use of machine learning’s techniques and latest tools,” said Samarasekera. Team ‘Rotis’ comprising Keet Sugathadasa, Roshan Alwis, Dulaj Atapattu, Indunil Asanka, Heshan Sandamal and Chamin Wickramarathna emerged as winners, with their intelligent customer support and incident manager that can learn from all its interactions with customers, continuously improving its service. The solution relieves the strain that support requirements play on organisations as they try to scale.

Team ‘We Are Here for the Hoodie’ which included Jeyanthasingam Jegasingam, Tharmarajasingam Thuvarakan, Deshani Geethika, Rashindrie Perera, Kailayapathy Suthagar and Isham Mohamed, received the runners-up title for their development of a customer/potential customer profiling solution.

A profile solution that predicts future trends in customer eating habits could have massive impacts on Sysco’s business, allowing the development of better long-term relationships with customers.

“I believe the greatest danger of artificial intelligence is the fact that people assume they understand it very early on,” said Team ‘Rotis’ member Keet.

“Learning is a never-ending process. The hackathon definitely involved a great deal of learning and tested our ability to use machine learning to solve the problems we face in the industry.”

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