Polyxeni Kalliga
About Polyxeni Kalliga
Polyxeni Kalliga is a Junior Machine Learning Engineer with expertise in forecasting modeling for renewable energy and consumption profiles. She has a strong educational background in Electrical and Computer Engineering and Integrated Machine Learning Systems, and currently works at Kindred Group plc after a year at Smart Power Networks.
Work at Kindred Group
Polyxeni Kalliga currently serves as a Junior Machine Learning Engineer at Kindred Group plc, a position she has held since 2023. She works in a hybrid capacity from London, England. In this role, she focuses on developing machine learning models that enhance decision-making processes within the organization. Her responsibilities include designing and implementing cloud infrastructure, as well as managing data exchange and security using AWS and Azure.
Previous Experience at Smart Power Networks
Prior to her current role, Kalliga worked as a Machine Learning Engineer at Smart Power Networks from 2022 to 2023 in London, England. During her tenure, she specialized in forecasting modeling related to renewable energy and consumption profiles. Her work involved utilizing both conventional and deep learning models to support the digitalization of energy infrastructure.
Education and Expertise
Kalliga has a strong educational background in engineering and machine learning. She earned a Master of Engineering (MEng) in Electrical and Computer Engineering from the National Technical University of Athens, where she studied from 2014 to 2019. She further advanced her knowledge by obtaining a Master of Science in Integrated Machine Learning Systems from University College London (UCL) in 2021.
Technical Skills and Specializations
Kalliga possesses expertise in designing and developing cloud infrastructure, including ETL pipelines for data ingestion, processing, and visualization. She implements predictive and optimization models, which are crucial for effective decision-making in energy management. Her multidisciplinary background supports her ability to generate insights that facilitate scalable solutions in the STEM field.
Commitment to Continuous Learning
Kalliga is dedicated to continuous learning and staying informed about advancements in the STEM field. She actively seeks opportunities to enhance her skills and knowledge, ensuring she remains updated with the latest developments in machine learning and energy systems.