About Me

As a cardiothoracic and obstetric anesthesiologist-clinical researcher in training with a biomedical engineering and computational research background, my academic focus is leveraging outcomes research, clinical informatics, and healthcare technology to improve perioperative care for patients with cardiovascular disease, including the cardio-obstetric population of pregnant women with cardiovascular disorders. Toward that end, graduate training provided me with skills in computational modeling, statistics, machine learning, and signal processing.

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Interests
  • Cardiothoracic Anesthesiology
  • High-Risk Obstetric Anesthesiology
  • Cardio-Obstetrics
  • Perioperative Outcomes
  • Machine Learning
Education

  • Anesthesiology Residency

    University of Michigan

  • MD-PhD, Biomedical Engineering

    Boston University School of Medicine

  • BSc Bioengineering

    University of California San Diego

Research Projects

Chronic kidney disease progression after cardiac surgery-associated acute kidney injury

University of Michigan, Department of Anesthesiology
Advisor: Michael Mathis, MD
Research Track Resident, 2023 – 2025
Applying machine learning to cardiac surgery-associated acute kidney injury data. Characterizing patient and perioperative features associated with progression to chronic kidney disease. Identifying recovery trajectories and morbidity risk profiles for kidney injury subtypes.

Global neural rhythm control by local neuromodulation

Boston University, Department of Mathematics & Statistics, Neural Dynamics Group
Advisor: Nancy Kopell, PhD
Graduate Research Assistant, June 2014 – May 2019
Created biophysical computational models of neural oscillations to better understand sleep architecture and general anesthesia. Utilized statistical learning and signal processing techniques to analyze brain electrical recordings. Developed software for neural simulation and data visualization.

Computational Modeling of Heart Cell Molecular Signaling

UC San Diego, Department of Bioengineering, Cardiac Mechanics Research Group
Advisor: Andrew McCulloch, PhD
Research Assistant, January 2011 – June 2012
Developed computational model of heart cell molecular signaling.

Tissue Modeling in a Patient-Specific Surgical Simulator

Stanford School of Medicine, Department of Otolaryngology Head & Neck Surgery
Advisor: Nikolas Blevins, MD
Research Intern, Summer 2009 – 2011
Designed workflow to create patient-specific virtual models for surgical simulator.

Publications
Anil Ramineni, Erik a Roberts, Molly Vora, Sohail K Mahboobi, Ala Nozari (2021). Anesthesia considerations in neurological emergencies. Neurologic Clinics.
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Erik Andrew Roberts (2019). Global neural rhythm control by local neuromodulation.
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Jason S Sherfey, Austin E Soplata, Salva Ardid, Erik a Roberts, David a Stanley, Benjamin R Pittman-Polletta, Nancy J Kopell (2018). DynaSim: a MATLAB toolbox for neural modeling and simulation. Frontiers in neuroinformatics.
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Leonid L Rubchinsky, Sungwoo Ahn, Wouter Klijn, Ben Cumming, Stuart Yates, Vasileios Karakasis, Alexander Peyser, Marmaduke Woodman, Sandra Diaz-Pier, James Deraeve, Others (2017). 26th annual computational neuroscience meeting (CNS* 2017): part 2. BMC Neuroscience.
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William M Howe, Howard J Gritton, Nicholas a Lusk, Erik a Roberts, Vaughn L Hetrick, Joshua D Berke, Martin Sarter (2017). Acetylcholine release in prefrontal cortex promotes gamma oscillations and theta--gamma coupling during cue detection. Journal of Neuroscience.
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