Mahdi Jazini is a PhD candidate in bioengineering at the University of Pittsburgh, building non-invasive cardiovascular monitors that match catheter-based references in surgical patients.
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At a glance
Name
Mahdi Jazini (also publishes as “Jazini, M.” or “Jazini, M. M.”)
Pronunciation
MAH-dee jah-ZEE-nee
Pronouns
he / him
Title
PhD candidate, Bioengineering — University of Pittsburgh, Cardiovascular Health Tech Lab. Defending December 2026.
Field
Non-invasive hemodynamic monitoring — cuffs, PPG, ECG, respiration. Hardware, signal processing, ML.
Based in
Pittsburgh, PA · available remotely worldwide
Press contact
Mahdi.Jazini@pitt.edu — usually replies within a day
Bios — pick a length
Two lengths, copy and paste.
Mahdi Jazini is a PhD candidate in bioengineering at the University of Pittsburgh’s Cardiovascular Health Tech Lab. He builds custom hardware, signal processing, and machine learning for non-invasive hemodynamic monitors — including a cuff-based cardiac-output device that matched invasive gold standards in 34 surgical patients. His work has received four awards including the Outstanding Paper Award at MACSOS 2025 and Top Prize at Safar 2026.
Fact sheet
Education
- PhD, Bioengineering (Biosignals) — University of Pittsburgh, 2022–2026 (expected Dec 2026)
- MS, Integrated Circuits — University of Tehran, 2016–2018
- BS, Digital Electronics — Amirkabir University of Technology, 2012–2016
Awards & honors
- Professional Development Award — 19th Postdoctoral Research Symposium, University of Pittsburgh Postdoctoral Association, 2026
- Top Prize — Safar Symposium, Dept. of Anesthesiology, University of Pittsburgh, May 2026
- Outstanding Paper Award — MACSOS Conference, University of Pittsburgh, Sept 2025
- Top Poster Prize — Safar Symposium, Dept. of Anesthesiology, University of Pittsburgh, May 2025
Selected publications
- Jazini, M., et al. Cardiac output monitoring via an automatic arm cuff device. medRxiv, 2025.
- Dhamotharan, V., Jazini, M., et al. A popular validated home monitor uses the maximum oscillogram amplitude to compute blood pressure. Scientific Reports, 2025.
- Momin, M.A., Jazini, M., et al. Self-powered wearable pressure sensors. Analysis & Sensing, 2024.
- Jazini, M.M., et al. Neural-network + FFT frequency estimation of SAW resonators. ICSPIS, IEEE, 2019.
Images & downloads
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