Big Data approach for algae production
research project predictive data models
Shyam Krishnan is doctoral researcher as part of Marie Skłodowska-Curie Actions DigitAlgaesation Network. He is PhD candidate at the University of Antwerp, Adrem Data Lab, supervised by Prof Dr. Kris Laukens and Dr. Luc Roef. In the coming 3 years, his research is dedicated to bridging the gap between ICT and microalgae industrial production at Proviron.
Shyam, can you briefly tell us something about your project?
I am working on developing data mining approaches for decision support of PBR processes. The research is focused on developing predictive models for monitoring and optimization of algae production and growth conditions.
My key objective is to extract the industrial data stored by SCADA systems and use it for growth optimization of microalgae using machine learning and data mining practices. Starting with the development of an interactive/integrative data mining platform for heterogeneous monitoring data and using it for the prediction of process outcomes in microalgae cultivation, we hope to discover best real time growth parameters for each species of algae.
What is your background?
I completed my master’s in Bigdata Analytics and Artificial intelligence from Letterkenny Institute of Technology, Ireland, and Bachelor of Technology in Information Technology from India. I was co-founder of a startup named NESTOR Technologies and worked as a product manager in the Electrical service, Production, and manufacturing domain.
And beside your work?
I am a passionate kayaker and book lover.
I live in the beautiful city of Antwerp where my biking skills are growing as fast as my favorite algae Rhodomonas-salina.
