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RESEARCH AND PROFESSIONAL EXPERIENCE

 

Delsys Inc., Altec Research Natick, MA

Research Scientist June 2024 - Present

  • Lead technical research developing and deploying machine learning and signal processing algorithms on optical sensors and embedded systems in scientific research instruments

  • Pioneered a long-range signal processing framework consisting of a deep neural source separation network and a time-evolving Bayesian Inference process, which enabled high-level understanding of the physical processes underlying noisy measurement data

  • Translated high-level Python algorithm prototypes into optimized, cross-compiled C++ code to run in a low-latency, multi-threaded embedded system

  • Managed a cross-functional team of 5 researchers and engineers in the design and implementation of a software system architecture for a wearable sensor prototype; conducted design meetings, code review, testing, version control, profiling, debugging, and documentation

  • Communicated findings to senior research personnel and funding partners through monthly written reports and presentations; currently writing research paper as first author for greater scientific community 

 

Research Engineer September 2023 - June 2024

  • Executed Monte Carlo simulations of light propagation in tissue and used results to design a multi-axis optical sensor that resolved anisotropic lensing effects in human tissue; this sensor became a cornerstone technology used across two separately funded research projects in my group

  • Built symbolic regression and feature clustering pipelines to process sensor data from experiments

  • Built and tested acoustic communications protocol for a multi-nodal sensor communication network

 

rStream Recycling, R&D Intern, Machine Learning Sommerville, MA | Summer 2023

  • Developed a graph-based clustering algorithm for hierarchizing image masks generated by DNN segmentation models that did not rely on semantic prompts to enhance object classification and localization

  • Prepared a custom data set of images and their hierarchized segmentation masks for model fine-tuning

 

Adept Materials, R&D Test Engineering Intern Providence, RI | Summer 2023

  • Developed quantitative models to predict passive moisture and temperature regulation in novel sustainable materials

  • Designed and constructed hardware prototypes to evaluate materials on their performance and durability

 

Stein Lab, Brown University Department of Physics, Undergraduate Researcher Providence, RI | May 2020 - May 2023

  • Developed theoretical models of laser light interactions with peptides for single-molecule sequencing

  • Spearheaded the design, assembly, and programming of an automated laser alignment system for imaging a nanometer-scale target

  • Optimized beam alignment using classical- and deep-learning-based non-linear regression to analyze laser-scan images

  • Acquired University-backed patent for methods and technology for photofragmenting peptides


 

EDUCATION

 

Brown University – Cumulative GPA: 3.9/4.0 Providence, RI | September 2019-May 2023

Sc.B. with Honors  – Physics

  • Honors Thesis, Department of Physics: Applications of Laser Light in Single-Molecule Protein Sequencing: An Analysis of Peptide Photofragmentation and Nanostructure Imaging and Localization by Laser Scanning

A.B. – English Literature

SKILLS, LANGUAGES, AND INTERESTS

 

  • Python, C++, Git/Github, Machine Learning/AI for Science, command line tooling and development in Windows/Linux/MacOS, familiarity with LLVM and Static Single Assignment intermediate representations

  • Technical writing and presentation (LaTex, Microsoft Office suite)

  • Quantum Physics, AMO Physics, laser optics, analog and digital circuit design

  • Fluent in English and proficient in Spanish (reading, writing, speaking)

  • Avid rock climber, hiker, skier, cyclist, and environmentally-conscious outdoor recreation enthusiast


 

PUBLICATIONS

 

  • Vietorisz, J.S., Chiodini, J., Iyer, A., DeLuca, G., Kline, J.C. Physiological Sparse Inference from Multi-Axis Photoplethysmography: A time-evolving sparse Bayesian inference framework for motion-robust vital sign estimation [research paper], currently writing (2025).

  • Drachman, N., Vietorisz, J.S., Winchester, A., Vest, R., Cooksey, G., Pookpanratana, S., Stein, D. Photolysis of the peptide bond at 193 nm and 222 nm [research paper], accepted by Journal of Chemical Physics (2025).

  • Stein, D. M., Vietorisz, J. S., and Drachman, N. Systems and methods for analysis of peptide photodissociation for single-molecule protein sequencing. U.S. Patent US-20240361331-A1. (2024).

  • Drachman, N., Vietorisz, J.S., and Stein, D.M. UV photofragmentation of peptides for single molecule protein sequencing by mass spectrometry [conference session], Conference on Single-Molecule Protein Sequencing (SMPS3), Delft University of Technology, Delft, Netherlands (2022). 

  • Vietorisz, J.S., Drachman, Nicholas, and Stein, D. M. An Analysis of Peptide Photofragmentation for Single-Molecule Protein Sequencing [poster presentation]. (2022, August 4-5). Summer Research Symposium, Brown Digital Repository, Brown University Library, Providence, RI.  https://doi.org/10.26300/m7pz-9050

  • Vietorisz, J.S., Drachman, N., and Stein, D.M., Analysis of peptide photofragmentation for single-molecule protein sequencing [research paper]. Submitted to iScience  (2021).

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