About me

Yogatheesan Varatharajah,

245, Coordinated Science Laboratory,

Urbana, IL, USA.

Email: varatha[number2][at]illinois[dot]edu

I am Yogatheesan (Yoga) Varatharajah, a PhD candidate in Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. I have previously obtained my master's degree from the same university and bachelor's degree in Electronic and Telecommunication Engineering at the University of Moratuwa in Sri Lanka. I am currently in my 2nd year of the PhD program and I am advised by Prof. Ravishankar Iyer.

My interests span probabilistic modeling approaches for addressing challenges associated with complex, real-world, dynamical systems. In that context, my PhD research focuses on developing probabilistic models and artificial intelligence techniques to address complex clinical challenges, related to the most complex biological system, brain. I have extensive expertise in statistical signal processing techniques and machine learning methods, both in their fundamentals and practical application. I leverage my expertise in both of these areas and clinical domain knowledge to develop unique analytic frameworks that provide actionable intelligence and biological insights. I am thankful to a number of neurologists and neuroscientists at the Mayo Clinic, with whom I collaborate extensively in order to gain domain expertise related to the clinical challenges I work on. My PhD research is being generously supported by the Mayo Clinic-Illinois Alliance Fellowship for Technology based Healthcare Research.

You can find my latest cv here. And a list of my publications is here.

Receiving best student paper finalist award from Dr. Nigel Lovell of the IEEE.

Delivering my talk at the Bigdata Neuroscience Workshop.

Recent news

  • Mar 2018 - Received the RAMBUS COMPUTER ENGINEERING FELLOWSHIP for the 2018-2019 academic year!
  • Mar 2018 - Post Bulletin article on my work.
  • Jan 2018 - Daily Illini article on my work.
  • Jan 2018 - My work was featured in UIUC and CSL news.
  • Dec 2017 - Presented my work at the 31st annual NIPS conference in Long Beach, LA.
  • Nov 2017 - Presented my poster at the American Epilepsy Society annual meeting in Washington DC.
  • Oct 2017 - Gave a talk at the first Feedback Friday meeting of Fall 2017, Coordinated Science Laboratory, UIUC.
  • Sep 2017 - Spotlight talk at the ACNN Bigdata Neuroscience Workshop, Indiana University.
  • Sep 2017 - My paper titled 'EEG-GRAPH: A Factor Graph Based Model for Capturing Spatial, Temporal, and Observational Relationships in Electroencephalograms' gets accepted at 31st Annual NIPS conference.
  • Jul 2017, My poster titled 'Unsupervised Analysis of Transcriptomic Data for Demystifying the Cause of Alzheimer's Disease' was featured at the Alzheimer's Association International Conference in London, UK.
  • May 2017 - My paper titled 'Inter-ictal Seizure Onset Zone localization using unsupervised clustering and Bayesian Filtering. ' was selected as one of the best six student authored papers at the 8th International IEEE/EMBS Conference on Neural Engineering. (link)
  • Feb 2017 - I was selected as an excellent graduate teaching assistant for ECE 313: Probability with Engineering Applications. (link)
  • Aug 2016 - Received the inaugural Mayo Clinic-Illinois Alliance Fellowship for Technology based Healthcare Research.
  • May 2016 - Passed my PhD qualifying examination!

Videos on my research