Fields of expertise
Machine learning, signal processing, spatio-temporal analysis and graph neural networks, meta learning and few-shot learning, biomedical signal analysis, interpretable machine learning, kernel-based techniques and harmonic analysis.
BiographyDr. Arun Venkitaraman is a postdoctoral researcher at the Signal Processing Laboratory LTS4, at the School of Engineering, EPFL from July 2021. Prior to that he was a postdoctoral researcher at the Division of Decision and Control Systems, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden under the Wallenberg Automation Systems and Software Programme. Arun received his PhD from the Department of Signal Processing, Division of Information Science and Engineering, KTH Royal Institute of Technology, Stockholm in 2018. Arun was also a visiting researcher at EPFL in 2018. Before his PhD Arun worked as a research intern at Philips Innovation Campus, Bangalore, India. Arun has a Masters in Science (Engineering) specialising in Signal processing from the Department of Electrical Engineering, Indian Institute of Science, Bangalore, India.
Arun’s research interests include spatio-temporal analysis and graph neural networks, meta learning and few-shot learning, biomedical signal analysis, interpretable machine learning, kernel-based techniques and harmonic analysis. He is part of the multi-disciplinary project PEDESITE aimed towards development of novel, efficient and interpretable AI approaches towards personalized seizure detection and forecasting algorithms. Arun supervises two PhD students as part of the project and has been involved in the supervision of numerous interns and Masters project students. Arun is currently a teacher for the Network Machine Learning course that deals with the recent subject of graph or network-aware machine learning methods in data science.
Arun is also a professional vocalist and violinist, trained in the (Carnatic) South Indian Classical Music tradition.