Krishnakant V. Saboo

Krishnakant V. Saboo

Postdoctoral Scholar

University of California San Francisco

Biography

I am a Postdoctoral Scholar at the University of California, San Francisco. I am advised by Prof. Edward Chang. My postdoc research leverages machine learning to model and optimize brain stimulation-based treatment of epilepsy.

I have a PhD in Electrical and Computer Engineering from University of Illinois, Urbana-Champaign where I was advised by Prof. Ravishankar K. Iyer. During my PhD, I developed ML tools for diagnosis and understanding of Alzheimer’s disease and epilepsy. I graduated with a B.Tech. and M.Tech. in Electrical Engineering from Indian Institute of Technology, Bombay. I worked with Prof. Vivek Borkar on topics in semi-supervised learning and resource allocation.

Research

I am broadly interested in topics at the intersection of machine learning, neurology, and neuroscience. My goal is to develop and apply machine learning techniques to (i) create tools for assisting clinicians in disease diagnosis and intervention, and (ii) delineate relationships among brain structure and activity, brain disorders, and cognition. For more details, see Projects.

During my PhD, I worked on Alzheimer’s disease and epilepsy in collaboration with Dr. Gregory Worrell (Mayo Clinic), Prof. Michal Kucewicz (Mayo Clinic), Prof. Prashanthi Vemuri (Mayo Clinic), and Dr. David Jones (Mayo Clinic). I have also worked with Dr. Jasmohan Bajaj (VCU) on analysing the relationship between gut microbiome, liver cirrhosis, and cognitive impairment.

Recent News

  • 10/2023: Started my postdoctoral position in the Chang Lab at UCSF!
  • 07/2023: I defended my PhD thesis!
  • 05/2023: Awarded the Schmidt Science Fellowship! Media: CSL, Forbes, The India Abroad
  • 04/2023: Our work on individualized seizure cluster prediction was invited for a submission to the IEEE Transactions on NanoBioscience journal’s special issue. Link
  • 10/2022: Our work on predicting seizure clustering got accepted in IEEE BIBM 2022 for an oral presentation.
  • 08/2022: Awarded the Young Investigator Award at AES 2022 Annual Meeting!
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Experience

  • 2022 Summer intern @Microsoft Research, MA
  • 2017 Summer intern @Cisco, CA
  • 2015 Summer intern @Innovation Labs, TCS, Bangalore
  • 2014 Summer intern @Texas Instruments, Bangalore

Education

  • PhD in ECE, 2023

    University of Illinois, Urbana-Champaign

  • MTech in Communication and Signal Processing, 2016

    Indian Institute of Technology, Bombay

  • BTech in Electrical Engineering, 2016

    Indian Institute of Technology, Bombay

Awards & Honors

  • Schmidt Science Fellow cohort of 2023.
  • Young Investigator Award, American Epilepsy Society (AES) 2022 Annual Meeting.
  • Landmark paper, European Association for the Study of the Liver. Paper link.
  • Graduate College’s Dissertation Completion Fellowship 2022-23, UIUC.
  • Paul D. Doolen Scholarship for the Study of Aging 2021-22, University of Illinois System.
  • Elsa and Floyd Dunn Award, 2020-21.
  • Mavis Future Faculty Fellowship, 2020-21.
  • Rambus Fellowship in ECE, UIUC, 2019-20.
  • Mayo Clinic/Illinois Alliance Fellowship for Technology-based Healthcare Research, 2017-19, 2019-20.
  • Outstanding Instructor, UIUC, Spring 2019.
  • Undergraduate Research Award 03, IIT-B, 2016.
  • Institute Academic Prize, Dual Degree EE Program, IIT-B, 2015.
  • Gold medal, Indian National Chemistry Olympiad, 2011.

Publications

(* denotes equal contribution and † denotes alphabetical ordering)

Journal

  1. K. V. Saboo, Y. Cao, V. Kremen, V. Sladky, N. M. Gregg, P. M. Arnold, P. J. Karoly, D. R. Freestone, M. J. Cook, G. A. Worrell, R. K. Iyer (2023). Individualized seizure cluster prediction using machine learning and chronic ambulatory intracranial EEG. IEEE Transactions on NanoBioscience.

  1. C. Topcu, V. S. Marks, K. V. Saboo, M. Lech, P. Nejedly, V. Kremen, G. A. Worrell, M T. Kucewicz (2022). Hotspot of human verbal memory encoding in the left anterior prefrontal cortex. eBioMedicine.

  1. K. V. Saboo, C. Hu, Y. Varatharajah, S. A. Przybelski, R. I. Reid, C. G. Schwarz, J. Graff-Radford, D. S. Knopman, M. M. Machulda, M. M. Mielke, R. C. Petersen, P. M. Arnold, G. A. Worrell, D. T. Jones, C. R. Jack Jr., R. K. Iyer*, P. Vemuri* (2022). Deep learning identifies brain structures that predict cognition and explain heterogeneity in cognitive aging. NeuroImage.

  1. K. V. Saboo, N. Petrakov, A. Shamsaddini, A. Fagan, E. A. Gavis, M. Sikaroodi, S. McGeorge, P. Gillevet, R. K. Iyer, J. S. Bajaj (2022). Stool microbiota are superior to saliva in distinguishing cirrhosis and hepatic encephalopathy using machine learning. Journal of Hepatology.

  1. V. S. Marks, K. V. Saboo, C. Topcu, T. P. Thayib, P. Nejedly, V. Kremen, G. A. Worrell, M. T. Kucewicz (2021). Independent dynamics of slow, intermediate, and fast intracranial EEG spectral activities during human memory formation. NeuroImage.

  1. K. V. Saboo*, I. Balzekas*, V. Kremen, Y. Varatharajah, M. T. Kucewicz, R. K. Iyer, G. A. Worrell (2021). Leveraging electrophysiologic correlates of word encoding to map seizure onset zone in focal epilepsy: Task-dependent changes in epileptiform activity, spectral features, and functional connectivity. Epilepsia.

  1. K. V. Saboo*, A. Shamsaddini*, M. V. Iyer, C. Hu, A. Fagan, E. A. Gavis, M. B. White, M. Fuchs, D. M. Heuman, M. Sikaroodi, R. K. Iyer, P. M. Gillevet, J. S. Bajaj (2021). Sex is associated with differences in gut microbial composition and function in hepatic encephalopathy. Journal of Hepatology.

  1. C. Hu, V. Anjur, K. V. Saboo, K. R. Reddy, J. O’Leary, P. Tandon, F. Wong, G. Garcia-Tsao, P. S. Kamath, J. C. Lai, S. W. Biggins, M. B. Fallon, P. Thuluvath, R. M. Subramaian, B. Maliakkal, H. Vargas, L. R. Thacker, R. K. Iyer, J. S. Bajaj (2021). Low predictability of Readmissions and Death Using Machine Learning in Cirrhosis. American Journal of Gastroenterology.

  1. K. V. Saboo, Y. Varatharajah, B. M. Berry, V. Kremen, M. R. Sperling, K. A. Davis, B. C. Jobst, R. E. Gross, B. Lega, S. A. Sheth, G. A. Worrell, R. K. Iyer, M. T. Kucewicz (2019). Unsupervised machine learning classification of electrophysiologically active electrodes during human cognitive task performance. Nature Scientific Reports 9.

  1. M. T. Kucewicz, K. V. Saboo, B. M. Berry, V. Kremen, L. R. Miller, F. Khadjevand, C. S. Inman, P. Wanda, M. R. Sperling, R. Gorniak, K. A. Davis, B. C. Jobst, B. Lega, S. A. Sheth, D. S. Rizzuto, R. K. Iyer, M. J. Kahana, G. A. Worrell (2019). Human verbal memory encoding is hierarchically distributed in a continuous processing stream. eNeuro 6.1.

  1. V.S. Borkar†, R. Karumanchi†, K. V. Saboo† (2017). An index policy for dynamic pricing in cloud computing under price commitments. Applicationes Mathematicae Journal.

Conference (peer-reviewed proceedings papers)

  1. C. Hu, K. V. Saboo, A. H. Ali, B. D. Juran, K. N. Lazaridis, R. K. Iyer (2023). REMEDI: REinforcement learning-driven adaptive MEtabolism modeling of primary sclerosing cholangitis DIsease progression. Machine Learning for Health (ML4H).

  1. Y. Cao, K. V. Saboo, V. Kremen, V. Sladky, N. M. Gregg, P. M. Arnold, S. Pappu, P. J. Karoly, D. R. Freestone, M. J. Cook, G. A. Worrell, R. K. Iyer (2023). A Transfer Learning-based Model for Individualized Clustered Seizure Prediction using Intracranial EEG. International IEEE EMBS Conference on Neural Engineering (NER).

  1. K. V. Saboo, Y. Cao, V. Kremen, V. Sladky, N. M. Gregg, P. M. Arnold, P. J. Karoly, D. R. Freestone, M. J. Cook, G. A. Worrell, R. K. Iyer (2022). Individualized seizure cluster prediction using machine learning and ambulatory intracranial EEG. International Conference on Bioinformatics and Biomedicine (BIBM). (Oral presentation).

  1. K. V. Saboo, A. Choudhary, Y. Cao, G. A. Worrell, D. T. Jones, R. K. Iyer (2021). Reinforcement learning-based disease progression model for Alzheimer’s disease. Advances in Neural Information Processing Systems (NeurIPS).

  1. K. V. Saboo, C. Hu, Y. Varatharajah, P. Vemuri, R. K. Iyer (2020). Predicting longitudinal cognitive scores using baseline imaging and clinical variables. IEEE International Symposium on Biomedical Imaging (ISBI). (Oral presentation).

  1. K. V. Saboo, Y. Varatharajah, B. M. Berry, M. R. Sperling, R. Gorniak, K. A. Davis, B. C. Jobst, R. E. Gross, B. Lega, S. A. Sheth, M. J. Kahana, M. T. Kucewicz, G. A. Worrell, R. K. Iyer (2019). A computationally efficient model for predicting successful memory encoding using machine learning-based EEG channel selection. International IEEE EMBS Conference on Neural Engineering (NER).

  1. Y. Varatharajah, M.J. Chong, K. V. Saboo, B. M. Berry, B. Brinkmann, G. A. Worrell, R. K. Iyer (2017). EEG-GRAPH: A factor graph-based model for capturing spatial, temporal, and observational relationships in electroencephalograms. Advances in Neural Information Processing Systems (NeurIPS).

  1. C. P. Narisetty*, K. V. Saboo*, B. Rajendran (2015). Composer classification based on temporal coding in adaptive spiking neural networks. International Joint Conference on Neural Networks (IJCNN).

Book Chapter

  1. M. T. Kucewicz, K. V. Saboo, G. A. Worrell. How can we identify electrophysiological iEEG activities associated with cognitive functions? Intracranial EEG: A Guide for Cognitive Scientists.. Springer, 2023.

Workshop

  1. Y. Varatharajah, K. V. Saboo, R. K. Iyer, S. Przybelski, C. Schwarz, R. Petersen, C. R. Jack Jr., P. Vemuri (2019). A joint model for predicting structural and functional brain health in elderly individuals. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), BHI Workshop.

  1. K. Avrachenkov, V.S. Borkar and K. V. Saboo (2016). Distributed and asynchronous methods for semi-supervised learning. Workshop on Algorithms and Models of the Web-Graph (WAW).

Patent

  1. K. V. Saboo, S. Rao. Gesture recognition using frequency modulated continuous wave radar with low angle resolution. U.S. Patent 9,817,109.

Talks

  • UCSF Deep Brain Stimulation Data Analysis Meeting, San Francisco CA. Mar 2023. (Invited)
  • CSL Student Conference Computational Biology and Healthcare session, UIUC. Feb 2023. (Conference)
  • IEEE International Conference on Bioinformatics and Biomedicine, Las Vegas NV. Dec 2022. (Conference)
  • American Epilepsy Society Annual Meeting, Nashville TN. Dec 2022. (Conference)
  • Data Science for Mental Health SIG, Alan Turing Institute, UK. Nov 2021. (Invited)
  • Coordinated Science Lab Social Hour, UIUC. Oct 2021. (Invited)
  • The Center for AI Driven Health Data Systems and Analytics, UIUC. Apr 2021. (Invited)
  • IEEE International Symposium on Biomedical Imaging, Iowa. Apr 2020. (Conference)
  • Coordinated Science Lab Social Hour, UIUC. Sep 2019. (Invited)
  • CompGen Student Lightening talk, Institute for Genomic Biology, UIUC. Sep 2017. (Invited)
  • DARPA Restoring Active Memory Project update. May 2017. (Invited)

Teaching

I thoroughly enjoy teaching and have worked on several aspects of conducting a course such a lecture development, conducting discussions, creating assignments and exams, and mentoring student projects. I also developed and taught my own course on machine learning in Summer 2020.

  • Head TA, Data Science and Analytics, ECE, UIUC. Spring 2021.
  • Instructor, Machine Learning Summer Course, Virtual. Summer 2020.
  • Head TA, Data Science and Analytics, ECE, UIUC. Spring 2019.
  • TA, Introduction to Probability, ECE, UIUC. Spring 2017.
  • TA, Introduction to Probability, EE, IIT-B. Spring 2016.
  • TA, Signals and Systems, EE, IIT-B. Fall 2015.

Projects

Alzheimer's disease

Alzheimer’s disease

Epilepsy

Epilepsy

Memory

Memory

Microbiome

Microbiome