About

Viswajith Siruvallur Vasudevan is a faculty member at the Cornell Duffield Engineering within the Meinig School of Biomedical Engineering. He holds the position of ALI Postdoctoral Fellow. His work is part of a highly collaborative and dynamic intellectual community known for excellence in educating students, conducting groundbreaking research, and advancing technological innovations that impact people, communities, and the world. The page indicates his association with Cornell's engineering programs and highlights the collaborative environment of the Duffield Engineering community, but does not provide specific details about his research focus, background, or key contributions.

Research topics

• Cardiology
• Internal medicine
• Medicine
• Computer science
• Risk analysis (engineering)

Selected publications

• Exploring the Efficacy of Generative AI and ChatGPT in BME Instructional Labs: A Case Study on GABA Receptors and Synaptic Potentials

  2025-08-21

  article1st authorCorresponding
  PublisherDOI

• BOARD # 33: Work in Progress: Understanding the Biomedical Engineering Student: Using Maslow’s Hierarchy of Needs

  2025-08-21

  article1st authorCorresponding
  PublisherDOI

• Embedding Studio-Based Learning in the Biomedical Engineering Curriculum to Improve Quantitative Problem-Solving Skills

  Biomedical Engineering Education · 2025-09-15

  articleOpen access

  Abstract Purpose We present a curriculum transformation initiative within the BME Department at Cornell University, focused on integrating studio-based pedagogy to enhance students’ technical and creative problem-solving abilities. We outline the structure of the proposed BME studio model and share initial findings, inviting instructors to consider this approach as means of driving meaningful change in the BME education field. Methods Throughout the course, we collected studio artifacts, post-studio student reflections, and administered an end of the semester survey to the students. We used a mixed-methods approach, using open-ended responses from reflection assignments, closed-response data from a post-course survey, and completed studio worksheets. Likert scale data were analyzed quantitatively, while open responses were thematically coded to identify trends, with key insights illustrated through representative quotes and sample student works. Results Integrating quantitative cellular signaling principles into the course improved students’ ability to formulate mathematical equations for biological systems, with iterative studio practice leading to increased proficiency, as measured by our performance indicator rubric. Our studio model enhanced problem-solving skills through repetitive practice and collaboration, with many students planning to continue using these methods beyond the course. A Google Slides/Documents platform was developed to document and track student work, fostering collaboration and idea-sharing across teams. We believe these platforms can used to create portfolios for documenting students’ proficiency development throughout their studies. Conclusions Embedding studio-based learning throughout the engineering curriculum, rather than as standalone courses, offers a transformative approach to develop active, engaged, and adaptable engineers equipped to tackle real-world challenges.

  PublisherOA PDFDOI

• Engineering Studio Pedagogy – First Experience in Integrating Novel Studio Sessions in Biomedical Engineering Courses

  2024-10-13 · 1 citations

  article1st authorCorresponding

  This innovative practice full paper describes the first experience introducing Engineering Studio Pedagogy in Biomedical Engineering courses at Cornell University. Biomedical Engineering is undergoing a thorough introspection to improve the curriculum and teaching methods for undergraduate courses. Innovations in teaching techniques have been shown to impact student learning positively. With many evolving needs in preparing tomorrow's biomedical engineers, identifying key skills is paramount to a successful program. At Cornell University, following the adaptations that were necessitated due to the events at the turn of the decade, an initiative by the University was taken up to foster active learning amongst students. Our biomedical engineering program aimed at providing a pedagogical method that would challenge students with real-world “open-ended” engineering problems, promote teamwork and in a low-stakes setting. We called this pedagogical method the Engineering Studio Pedagogy. This paper summarizes the experience of implementing this as a pilot at Cornell University in Fall 2023, outlining how these studios were designed, the student experience obtained through surveys, and the instructional team's experience. The studio sessions demonstrated noticeable improvements in students' learning, teamwork, and motivation, particularly in a low-stakes setting. However, the results for tackling “open-ended” engineering problems were more mixed.

  PublisherDOI

• TRANS-AORTIC VALVULAR FLOW DYNAMICS AND LEFT VENTRICULAR EJECTION FRACTION FOR MONITORING RECOVERY OF PATIENTS WITH LEFT VENTRICULAR SYSTOLIC HEART FAILURE

  medRxiv · 2023-04-26

  preprintOpen access1st author

  A bstract Durable mechanical circulatory support in the form of left ventricular (LV) assist device (LVAD) therapy is increasingly considered in the context of the recovery of native cardiac function. Progressive improvement in LV function may facilitate LVAD explantation and a resultant reduction in device-related risk. However, ascertaining LV recovery remains a challenge. In this study, we investigated the use of trans-aortic valvular flow rate and trans-LVAD flow rate to assess native LV systolic function using a well-established lumped parameter model of the mechanically assisted LV with pre-existing systolic dysfunction. Trans Aortic Valvular Ejection Fraction (TAVEF) was specifically found to characterize the preload-independent contractility of the LV. It demonstrated excellent sensitivity to simulated pharmacodynamic stress tests and volume infusion tests. TAVEF may prove to be useful in the ascertainment of LV recovery in LVAD-supported LVs with pre-existing LV systolic dysfunction.

  PublisherOA PDFDOI

• BIO19: Patient-Specific Econotherapeutic Closed-Clinician/Engineer-in-the-loop Framework for VAD Physiological Control

  ASAIO Journal · 2023-06-01

  article1st authorCorresponding

  Background: Mechanical circulatory support therapy essentially restricts patients to the hospital. Numerous clinical publications and national/international presentations indicate the need for early patient discharge, both from a quality of life and economic viewpoint. An alternative strategy is to look at providing time-appropriate VAD support to temporize patients for transplantation or other definitive therapy. However, current VAD systems do not possess high-level feedback control targeting therapy-specific objectives. Current Controllers (i) operate in open-loop fixed-average-speed mode (do not adjust to match physiological demand or cardiac function) and (ii) have minimal ability to assess and respond to adverse events. Therefore, our group is embarking on developing an Intelligent VAD ControllerTM (iVC™) with advanced, modern features that address the deficits of prevailing technologies. Methods: As an initial step towards the design of an Intelligent VAD ControllerTM (iVC™), we developed an Econotherapeutic framework based on concepts of modern control theory, inter-operator communication (Kanban Method), and industrial supply-demand management (Tanpin-Kanri System). The design inputs included considerations for 1. collaboration of clinician and engineer; 2. patient-specific therapeutic goals; 3. fusion of multiple control objectives; 4. non-invasive monitoring of the patient and hardware, and 5. considerations of the financial/resource cost. From the perspective of a control problem, we extend the engineering theory behind its implementation by including, in our framework, the therapy and healthcare protocols to the control problem as constraints. Results: The resulting Econotherapeutic framework is depicted schematically in Figures 1 and 2 below. Figure 1 outlines the framework’s architecture, which includes two sub-frameworks: Therapeutic and Economical. The outlines of the framework’s functions are provided to optimize patient-specific therapy and follow-up and the economic burden of care and control. Figure 2 outlines the inter-operator communication (inspired by Kanban Methods) protocols that form the basis for the framework in terms of roles and responsibilities, design aspects of the control, and implementation steps (including support). The framework addresses the design inputs with the outlines mentioned in Figure 1 as to what the framework addresses, with the implementation of the framework specific to a patient carried out by the protocols outlined in Figure 2. Conclusion: A VAD closed-loop physiological control is, in essence, a multi-disciplinary optimization problem driven by both medical and engineering considerations. The econotherapeutic framework derived above provides a framework for developing an iVC. We will now proceed to develop, in conjunction with clinicians, the possible details of the framework and, using The PediaFlowTM Pediatric VAD, conduct feasibility studies of the iVC that tests the framework.Figure 1. Architecture of the Econotherapeutic FrameworkFigure 2. The Design, Management and Monitoring Communication protocols of the Econotherapeutic Framework for iVC for every individual patient.

  PublisherDOI

• BIO30: A Method to Monitor Ventricular Recovery Using VAD Signals Based on Parseval’s Power Theorem

  ASAIO Journal · 2023-06-01

  article1st authorCorresponding

  Study: Recent studies highlight the growing interest in achieving ventricular recovery for VAD patients, thereby eliminating the need for cardiac transplantation. Hemodynamic measurements may be performed during periodic echocardiography for patients with probable recovery. However, there are no standard methods to evaluate ventricular recovery on a continuous outpatient basis. Such a method can help assess changes in cardiac function throughout daily activities, potentially optimized by a responsive VAD control algorithm. The objective of this study was to evaluate a surrogate measure of cardiac contractility based on VAD inherent signals using an in-silico simulation model of assisted circulation. Methods: Without loss of generality, hemodynamic power can be visualized as an electrical power signal in an implanted VAD. The power of a continuous periodic signal (the VAD Flow Rate signal), given by Parseval’s Power Theorem, is equivalently the average value integral over one period of the square of the magnitude of the signal (inclusive of all harmonic components). In this in-silico simulation study, we compute the ratio of this power with the norm (over multiple cardiac cycles) of the signal under steady-state conditions. We call this ratio the Power Factor of the VAD Flow Rate, represented by λVAD. Numerical simulations were conducted for different values of ventricular contractility (Emax Maximum Ventricular Elastance) from 0.5 to 2.0 mmHg/ml over a range of VAD speeds of 1000 to 8000 RPM (HeartMate 3® VAD Model) in steps of 100 RPM. Results: The figure below illustrates the relationship of the Power Factor to VAD speed for four levels of ventricular contractility. At 1000 RPM, the Power Factor for all Emax values was found to be equal. As the VAD speed increases above approximately 4000 RPM, the λVAD values diverge, demonstrating the direct relationship with Emax: having a peak of approximately 0.8 for the greatest ventricular contractility (Emax = 2.0). As speed increases further and approaches 8000 RPM, the values of λVAD once again converge. Another discriminating feature is the location (speed) of the local maximum (“hump”) in the curves within the range of 4000 and 6000 RPM, with the peak occurring at increasing speeds for increasing contractility. The cause of the hump is due to the cooperative relationship of the VAD and native ventricle, precisely the point of the aortic valve opening, allowing forward flow. At the lowest speeds, there is a slight negative flow through the VAD and, thus, a more subdued λVAD. Conclusion: This simulation study shows that the Power Factor of VAD flow rate has the potential as a noninvasive surrogate measure of ventricular recovery that can be monitored continuously. The metric is sensitive to the interaction between the native left ventricle and the VAD and thus helpful in developing feedback control that optimizes cardiac rehabilitation.Figure 1. Simulation results for the Power Factor of VAD Flow Rate as a function of different VAD Speeds (RPM).

  PublisherDOI

• Trans-aortic Valvular Ejection Fraction for Monitoring Recovery of Patients with Ventricular Systolic Heart Failure

  Annals of Biomedical Engineering · 2023-09-04

  article1st authorCorresponding
  PublisherDOI

• Application of mathematical modeling to quantify ventricular contribution following durable left ventricular assist device support

  Applications in Engineering Science · 2022-06-01 · 7 citations

  articleOpen access1st author

  Ejection Fraction (EF), a measure of the ability of the heart to pump blood, is an important parameter for the diagnosis for heart failure as well as in the monitoring of the therapy provided. The standard method of calculating EF uses the left ventricular volume (LVV) by identifying the end-diastolic and end-systolic volumes. For patients implanted with a continuous flow (CF) left ventricular assist devices (LVADs), there are two pathways for blood ejection, Trans-Aortic Valve Flow (TAVF) which is intermittent and Trans-VAD Flow (TVF) that flows continuously throughout the cardiac cycle. Using the standard method to calculate EF in LVAD patients provides the fraction of the total blood ejected from the ventricle over a cardiac cycle. When monitoring the patient for recovery, it is vital to quantify the precise contribution of the Trans-Aortic Valve path independently from the Trans-VAD contribution. In this paper we demonstrate how this can be accomplished with a mathematical lumped parameter model of the interaction of the cardiovascular system and the LVAD. We introduce the Trans-Aortic Valve Ejection Fraction (TAVEF), which is the measure of the Trans-Aortic Valve contribution to the overall circulation. The dilated failing heart is represented by an unimodal End-Sytolic Pressure Volume Relationship (ESPVR). Our results indicate that TAVEF describes the contribution of the TAVF better as compared to standard EF over the entire range of LVAD speeds, and captures the point of aortic valve closure by becoming 0, whereas the standard EF is non-zero. TAVEF can be a useful, reliable, non-invasive mechanism for monitoring ventricular recovery.

  PublisherDOI

• PEDS1: The PediaFlow Baby VAD is Back, Baby!

  ASAIO Journal · 2022-06-01 · 1 citations

  article

  Study: The PediaFlow™ is a miniature, fully-magnetically-levitated, implantable pediatric VAD intended for extended support in neonates and infants that operates over a wide range of flow to accommodate the growing child. Its design is derived from the Streamliner™ maglev VAD, and has evolved through four generations of design from 2004-2014, with support of the NIH/NHLBI Pediatric Circulatory Support and PumpKIN programs. Chronic in-vivo studies of the fourth generation, PF4, demonstrated exceptional hemocompatibility, and was published in 2018. This report describes progress with the clinical, fifth generation, PF5, which is intended for high volume manufacturing and will be carried forward to clinical trials. Methods: The PF5 retains the optimized electromagnetic architecture of its predecessor, including permanent-magnet, passive radial suspension, and Lorentz type, feedback controlled axial suspension. Upgrades were made to (1) improve manufacturability, (2) reduce the diameter of the driveline, (3) provide touchdown protection, (4) improve hydraulic efficiency, (5) increase flow output, (6) improve sensor reliability, (7) provide sensor-less physiological measurements. Results: Optimization of the flow path by computational fluid dynamics (CFD) was able to increase the maximum output from 1.5 LPM (PF4) to 3.5+ LPM (PF5), with commensurate increase of hydraulic efficiency from 27% to 34%. The inflow and outflow diameters were increased slightly from 5 mm to 6 mm while keeping the critical flow path dimensions almost unchanged; however, the overall size of the pump was reduced from 17.6 to 14.9 cc displacement. (See Figure.) The robustness of the sensor was improved by relocating circuitry within the pump, with the added benefit of reducing the driveline diameter from 6 mm to 4 mm. Design-for-manufacture and reduction of part count translated to approximate five-fold reduction in manufacturing cost. Normalized Index of Hemolysis (NIH) remains below 0.01 g/100 dL (0.01 mg/dL), comparable to PF4. Conclusions: The clinical version of the PediaFlow (PF5) features several improvements over the PF4 that increase its robustness and performance. Ongoing work includes development a miniaturized digital/clinical-use control unit with embedded physiologic feedback, suction avoidance, pump flow rate output, and diagnostic functions – capitalizing on intrinsic pressure-sensing of the levitation system. Human factors design for infants and young children is an important component of these efforts. We’re back, baby! Figure 1. Clinical version of the PediaFlow(PF5) fully magnetically levitated, mixed flow, implantable pediatric VAD and control unit.

  PublisherDOI

Frequent coauthors

• Timothy M. Maul

  9 shared

• James F. Antaki

  7 shared

• Marwan A. Simaan

  University of Central Florida

  6 shared

• Peter D. Wearden

  6 shared

• Keshava Rajagopal

  Thomas Jefferson University

  5 shared

• Salim E. Olia

  Policlinico Tor Vergata

  4 shared

• Harvey S. Borovetz

  University of Pittsburgh

  4 shared

• J. Eduardo Rame

  Thomas Jefferson University

  3 shared

Education

• PhD., Electrical and Computer Engineering

  University of Central Florida

  2020

• M.Tech, Biomedical Engineering, Applied Mechanics

  Indian Institute of Technology Madras

  2010

• B.Tech, Electrical and Electronics Engineering

  National Institute of Technology

  2008