Ben Carnovale, B.S.

Ben exemplifies academic excellence with recognition as a University Scholar in the top 2% of his graduating class. His outstanding performance earned him the designation as Outstanding Graduate in Electrical Engineering, demonstrating exceptional mastery of technical and analytical skills.

As a Junior Research Fellow at SCOLI, he bridges engineering expertise with medical applications, contributing to cutting-edge research in neurosurgery while pursuing his medical degree at the University of Pittsburgh School of Medicine.

Ben has established himself as a prolific researcher with an impressive publication record spanning neurosurgical education, spine injuries, and clinical outcomes research. His work addresses real-world clinical challenges through innovative analytical approaches:

• Neurosurgical Education Research: Investigating the readability and accessibility of digital educational resources like AtlasGPT for neurosurgical training

• Sports-Related Spine Injuries: Comprehensive analysis of spine and paraspinal disease in golf players, contributing to understanding activity-related injury patterns

• Pediatric Injury Research: Studies on spinal injuries from weightlifting in minors and neurological injuries from recreational activities

• Clinical Outcomes Analysis: Machine learning applications for predicting patient-reported outcome measures using radiographic and demographic data

• Healthcare Accessibility: Research on language barriers in neurosurgical care and health disparities

As a key member of the Agarwal Lab within SCOLI, Ben plays a vital role in advancing spine research through multiple responsibilities:

• Clinical Research: Analyzing pre- and post-operative patient data to identify predictors of surgical outcomes and improve patient care

• Statistical Analysis: Conducting advanced statistical modeling for research papers and clinical studies

• Mentorship: Training new students and interviewing incoming intern classes, contributing to SCOLI's educational mission

• Grant Writing: Supporting funding acquisition efforts to sustain and expand research initiatives

• Patient Engagement: Consenting patients for research participation and blood collection in clinical studies

Ben has demonstrated exceptional innovation in medical device development, earning recognition through multiple prestigious competitions:

• Spine Bionics: Second place winner in the Pitt Big Idea Competition for intelligent spinal implants, securing $15,000 in funding and advancing to multiple national competitions

• IntelliKnee: Finalist in the Michael Wells Student Healthcare Competition for intelligent total knee replacement technology

• Robotic Vision Systems: Best Overall Engineering Project award for vision language action model for robotic manipulation

• NSF I-Corps Certification: Completed rigorous entrepreneurship training program, validating commercial potential of innovations

Ben demonstrates commitment to patient care and community service through diverse volunteer activities:

• Scoliosis Patient Support Groups: Coordinating quarterly meetings and providing emotional support to patients and families navigating spine surgery

• Hospice Care: Providing companionship to hospice patients through the Athena Institute Pre-Med Hospice Program

• Community Food Bank: Long-term volunteer organizing food distributions for families in need

• IEEE Leadership: Vice President of Eta Kappa Nu honors society, leading K-12 STEM outreach initiatives

• Teaching Assistant: Guiding students in PCB design and electrical engineering fundamentals

Academic Excellence: • MD Candidate – University of Pittsburgh School of Medicine (2025-Present) • BS Electrical Engineering – University of Pittsburgh (2025) • Chemistry Minor • University Scholar (Top 2%) • Outstanding Graduate in Electrical Engineering

Major Awards: • IEEE PES John W. Estey Outstanding Scholar (2024) • IEEE PES Scholarship Plus Award (2023) • Pitt Big Idea Competition – 2nd Place • Best Overall Engineering Project • Multiple national competition recognitions

Core Competencies: • Machine Learning & Statistical Analysis • Medical Image Segmentation • Power Systems Engineering • Finite Element Analysis • C/C++, Python, MATLAB • SolidWorks, COMSOL