Machine Learning Biomedical Engineering

Megha Shinde

********@***.*** +1-757-***-**** Linkedin Google Scholar

PROFILE SUMMARY

Biomedical Engineering researcher with expertise in biosensor development, microfluidics, lab-on-chip and machine learning for data analysis. Skilled in Python, MATLAB, and cleanroom fabrication techniques, with a strong foundation in electronics. Passionate about integrating interdisciplinary approaches to advance biomedical technologies and translate research into real-world applications. EDUCATION

Ph.D. Biomedical Engineering Old Dominion University Norfolk, VA, USA May 2025 Dissertation: “Development of a non-enzymatic biosensor for the detection of dopamine” B.Sc. Electronic Engineering Pune University Pune, India Dec 2020 SKILLS

• Programming: Python, MATLAB, C

• Machine Learning: Data Processing, Algorithm Development, Model Optimization

• Software & Tools: MATLAB, Altium, KiCad, Solid works, Auto-CAD, 3D printing.

• Hardware: Arduino, Microfluidics, PCB Design, prototyping, Product optimization.

• Fabrication & Characterization: Microfabrication, Cleanroom, SEM, TEM, medical device design

• Wet lab: Cell Culture, Material synthesis, Western blot. EXPERIENCE

Graduate Research Assistant Old Dominion University Norfolk, VA, USA Aug 2023 – May 2025

• Synthesized laser-induced graphene electrodes and nanoparticles for electrochemical detection of biomarkers.

• Designed and developed biosensors for point-of-care diagnostics.

• Utilized advanced surface characterization techniques, including Scanning Electron Microscopy

(SEM) for material analysis.

• Applied Python for data processing, electrochemical analysis, and visualization.

• Designed and modified PCB boards for sensor integration and testing. Internship Cytorecovery Inc Blacksburg, VA, USA June 2023 – Aug 2023

• Led the development of a high-precision cell sorting chip integrating microfluidics and 3D printing technologies.

• Utilized MATLAB and computer modeling tools to optimize chip architecture, demonstrating expertise in engineering principles and simulation tools.

• Corrected and enhanced MATLAB code to improve generator performance, achieving significant efficiency gains.

• Applied Python for image analysis using machine learning algorithms, enabling automated cell identification and sorting.

• Gained experience in cleanroom fabrication and precision manufacturing techniques, along with exposure to KiCad and Altium.

Graduate Teaching Assistant Old Dominion University Norfolk, VA, USA Aug 2022 – May 2023

• Conducted lab sessions and instructed over 80 students on Python, C, and fundamental programming concepts.

• Assisted students with circuit design, and the use of electronic testing equipment (oscilloscopes, multimeters). VHDL

• Supported hands-on learning with electronics, fostering strong problem-solving and technical skills among students.

Software Developer Stratizant Pune, Maharashtra, India Jan 2020 – Aug 2021

• Designed and optimized backend systems using Python. Django

• Enhanced application performance through code optimization and database integration, resulting in improved application performance and response times.

, XRD

PUBLICATIONS

• Shinde, M., Arjun, A. M., & Slaughter, G. (2023). Application of MXene in the electrochemical detection of neurotransmitters: A review. IEEE Sensors Journal, 23(15), 164**-*****.

• Torati, S. R., Hanson, B., Shinde, M., & Slaughter, G. (2023). Gold-deposited laser-induced graphene electrode for detection of miRNA-141. IEEE Sensors Journal, 24(2), 2154–2161.

• Shinde, M., Torati, S. R., & Slaughter, G. (2024). Nb4C3Tx MXene-AgNPs decorated laser-induced graphene for selective detection of dopamine. Journal of Electroanalytical Chemistry, 959, 118180.

• Shinde, M., & Slaughter, G. (2025) Advanced Nanocomposite-Based Electrochemical Sensor for Ultra-Sensitive Dopamine Detection in Physiological Fluids. Front. Lab Chip Technol., Volume 4. CONFERENCES

• Shinde, M., Torati, S. R., & Slaughter, G. (2024, Sept. 25). Advanced Electrochemical Sensing: Bridging Cardiovascular and Neurological Dopamine Monitoring [Poster presentation]. Women Building Bio 2024, Norfolk, VA.

• Shinde, M., Torati, S. R., & Slaughter, G. (2024, April 25-26). Amplifying and Selectively Detecting Dopamine with Polypyrrole-MXene-Iron electrode [Poster presentation]. NanoBioTech 2024, Norfolk, VA. (Best Poster Award)

• Shinde, M., & Slaughter, G. (2023, July 27-29). Amplifying Electrochemical Dopamine Detection using MXene-Ag Nanocomposite Electrode [Poster presentation]. NanoBioTech 2023, Norfolk, VA. Nanobiotech, 2023

• Shinde, M., Mohan, A., & Slaughter, G. (2022, Sept. 22). Nickel hydroxide niobium MXene modified laser induced graphene electrodes for electrochemical detection of dopamine. [Poster presentation]. Women Building Bio 2024, Norfolk, VA. REFERENCE

Available upon request.

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