Ileana Pirozzi, from Colleferro (Roma), Italy, is pursuing a PhD in Bioengineering at Stanford School of Engineering as a Knight-Hennessy (KH) Scholar. As part of the KH program, Ileana completed three years of global leadership training. In fulfillment of her PhD work, Ileana is leading a variety of projects to push the next generation of smart medical devices to prevent and treat heart failure. Her clinical focus is congestive heart failure and congenital heart disease, and her engineering approach includes biomimetic device design leveraging computational modeling, optimization techniques and soft robotics. Ileana is also interested in exploring novel approaches integrating AI and sensing for improved patient monitoring and long-term care.
Before coming to Stanford, Ileana was at Brown University, she earned a bachelor’s degree in bioengineering and biomedical engineering. Ileana was a research intern at the NASA Ames Research Center and at the Tripathi Biomedical Engineering Lab at Brown. She was elected President of the Rhode Island Alpha Chapter of Tau Beta Pi, the National Engineering Honors Society. Additionally, she was named a Vincent and Ruby DiMase Research Fellow at Brown’s School of Engineering and was a recipient of the Domenico Ionata Award for excellence in research and creativity in engineering, the Outstanding Senior in Biomedical Engineering Award, the Distinguished Thesis Prize and the K.T. Romer Undergraduate Teaching and Research Award. With a team of Brown University and RISD students, Ileana developed an implantable medical device for use in cardiopulmonary bypass surgeries. Further development of the device was pursued through a startup company under the name of EmboNet. The company was awarded several national and international prizes and grant awards.
Honors & Awards
Fifty 50 - Top 50 scientists and researchers from top American institutions, Fifty Years Venture Fund (May 2021)
Knight-Hennessy Scholars Fellowship, Stanford University (February 2018)
First Prize at Johns Hopkins Healthcare Design Competition in Advanced Healthcare division, Johns Hopkins University (April 2018)
Distinguished Thesis Prize, Brown University (May 2018)
Domenico A. Ionata Award for Excellence in Research and Creativity in Engineering, Brown University (May 2018)
Outstanding Senior Award, Brown University (May 2018)
Di Mase Engineering Summer Fellowship, Brown University (May 2017)
K. T. Romer Undergraduate Teaching and Research Award, Brown University (May 2015)
Professional Affiliations and Activities
Member, Tau Beta Pi - the National Engineering Honors Society (2016 - Present)
Education & Certifications
Master of Science, Stanford University, BIOE-MS (2021)
Sc.B. (Honors), Brown University, School of Engineering, Biomedical Engineering (2018)
- RVEX: Right Ventricular External Device for Biomimetic Support and Monitoring of the Right Heart ADVANCED MATERIALS TECHNOLOGIES 2022
A new open-access platform for measuring and sharing mTBI data.
2021; 11 (1): 7501
Despite numerous research efforts, the precise mechanisms of concussion have yet to be fully uncovered. Clinical studies on high-risk populations, such as contact sports athletes, have become more common and give insight on the link between impact severity and brain injury risk through the use of wearable sensors and neurological testing. However, as the number of institutions operating these studies grows, there is a growing need for a platform to share these data to facilitate our understanding of concussion mechanisms and aid in the development of suitable diagnostic tools. To that end, this paper puts forth two contributions: (1) a centralized, open-access platform for storing and sharing head impact data, in collaboration with the Federal Interagency Traumatic Brain Injury Research informatics system (FITBIR), and (2) a deep learning impact detection algorithm (MiGNet) to differentiate between true head impacts and false positives for the previously biomechanically validated instrumented mouthguard sensor (MiG2.0), all of which easily interfaces with FITBIR. We report 96% accuracy using MiGNet, based on a neural network model, improving on previous work based on Support Vector Machines achieving 91% accuracy, on an out of sample dataset of high school and collegiate football head impacts. The integrated MiG2.0 and FITBIR system serve as a collaborative research tool to be disseminated across multiple institutions towards creating a standardized dataset for furthering the knowledge of concussion biomechanics.
View details for DOI 10.1038/s41598-021-87085-2
View details for PubMedID 33820939
Cardiac Support for the Right Ventricle: Effects of Timing on Hemodynamics-Biomechanics Tradeoff
Lecture Notes in Computer Science
Springer, Cham. 2021; FIM 2021: 385-395
View details for DOI 10.1007/978-3-030-78710-3_37
Centrifugal Microfluidics Traps for Parallel Isolation and Imaging of Single Cells
2020; 11 (2)
Analysis at the single cell level has becoming an increasingly important procedure to diagnose cancer tissue biopsies. These tissue samples are often heterogeneous and consist of 1000-15,000 cells. We study the use of centrifugal microfluidics to isolate single cells into micro chambers. We describe the optimization of our microfluidics flow device, characterize its performance using both polystyrene beads as a cell analogue and MCF-7 breast cancer cells, and discuss potential applications for the device. Our results show rapid isolation of ~2000 single cell aliquots in ~20 min. We were able to occupy 65% of available chambers with singly occupied cancer cells, and observed capture efficiencies as high as 80% using input samples ranging from 2000 to 15,000 cells in 20 min. We believe our device is a valuable research tool that addresses the unmet need for massively parallel single cell level analysis of cell populations.
View details for DOI 10.3390/mi11020149
View details for Web of Science ID 000520181500038
View details for PubMedID 32013161
View details for PubMedCentralID PMC7074746
SELECTIVELY COMPLIANT ANNULOPLASTY RING TO ENABLE ANNULAR DYNAMICS IN MITRAL VALVE REPAIR EVALUATED BY IN-VITRO STEREOVISION
AMER SOC MECHANICAL ENGINEERS. 2020
View details for Web of Science ID 000624287000005
Enabling In-Bore MRI-Guided Biopsies With Force Feedback
IEEE TRANSACTIONS ON HAPTICS
2020; 13 (1): 159–66
Limited physical access to target organs of patients inside an MRI scanner is a major obstruction to real-time MRI-guided interventions. Traditional teleoperation technologies are incompatible with the MRI environment and although several solutions have been explored, a versatile system that provides high-fidelity haptic feedback and access deep inside the bore remains a challenge. We present a passive and nearly frictionless MRI-compatible hydraulic teleoperator designed for in-bore liver biopsies. We describe the design components, characterize the system transparency, and evaluate the performance with a user study in a laboratory and a clinical setting. The results demonstrate % difference between input and output forces during realistic manipulation. A user study with participants conducting mock needle biopsy tasks indicates that a remote operator performs equally well when using the device as when holding a biopsy needle directly in hand. Additionally, MRI compatibility tests show no reduction in signal-to-noise ratio in the presence of the device.
View details for DOI 10.1109/TOH.2020.2967375
View details for Web of Science ID 000521334300023
View details for PubMedID 31976906
Microfluidic Immiscible Phase Filtration System for the Isolation of Small Numbers of Cells from Whole Blood
CYTOMETRY PART A
2019; 95A (8): 885-897
Isolation of circulating tumor cells (CTCs) has generated clinical and academic interest due to the important role that CTCs play in cancer metastasis and diagnosis. Here, we present a PDMS and glass prototype of a microfluidic device for the immunomagnetic, immiscible phase filtration based capture, and isolation of MCF-7 breast cancer cells, from various sample matrices including PBS-based buffer, blood plasma, and unprocessed whole blood. Following optimization of surface energy of an oil-water interface, microfluidic geometry, and bead-binding kinematics, our microfluidic device achieved 95 ± 4% recovery of target cells from PBS-based buffer with 95% purity, 90 ± 3% recovery of target cells from blood plasma and recovery of ~70 ± 5% from unprocessed whole blood with purity >99% with 1 ml blood samples with 1,000 spiked target cells. From quantitative studies to assess the nonspecific carryover of contaminants from whole blood, we found that our system accomplishes a >175 fold depletion in platelets, >900 fold depletion in erythrocytes, and >1,700 fold depletion in leukocytes with respect to unprocessed whole blood, enabling us to avoid sample pre-processing. In addition, we found that ~95% of the isolated target cells were viable, making them suitable for subsequent molecular and cellular studies. We quantify and propose mechanisms for the carryover of platelet, erythrocyte, and leukocyte contamination in purified samples, rather than relying on sample pre-processing. These results validate the continued study of our platform for extraction of CTCs from patient samples and other rare cell isolation applications. © 2019 International Society for Advancement of Cytometry.
View details for DOI 10.1002/cyto.a.23736
View details for Web of Science ID 000482423800008
View details for PubMedID 30852843
Getting there and staying there: supporting and enabling persistent human life on Mars using synthetic natural rubber, self-healing materials, and biological batteries
PLOS Synthetic Biology
View details for DOI 10.1101/345496