R&D

Behrad Zeinali

Toledo, Ohio · 1-832-***-**** · *************@*****.*** · linkedin.com/in/behrad-zeinali-b42aa2b8 PROFESSIONAL SUMMARY

Hybrid R&D Engineer and Physics-Informed AI Specialist bridging advanced experimental instrumen- tation, multiphase fluid dynamics, and predictive machine learning. Proven track record of solving high-cost industrial problems—from developing thermodynamics-informed algorithms for commercial furnaces to executing NSF- and NIH-funded R&D in thermal management and aerosol dynamics. SELECTED ENGINEERING IMPACT

• Reduced industrial energy waste by a forecasted 3-5% via predictive modeling of furnace performance.

• Improved predictive model accuracy from R2 0 to 0.8 by algorithmic drift correction across 5 years of historical manufacturing data.

• Prevented costly mechanical system failures and client machine recalls via the complete redesign of fluid and conveyor systems.

TECHNICAL SKILLS

• Core Expertise: Physics-Informed ML, Predictive Time-Series Modeling, Sensor Drift Correction, Experi- mental Fluid Dynamics, Thermal System Optimization, Root Cause Analysis.

• Data & Software: Python (Pandas, Scikit-learn), MATLAB, OpenFOAM, LabVIEW.

• Mechanical & Hardware: SOLIDWORKS, GD&T, LDA, Ultrasound, PM Sensors, Arduino. ENGINEERING & RESEARCH EXPERIENCE

The University of Toledo — Toledo, OH 06/2021 – Present R&D Engineer (Doctoral Research)

• Physics-Informed Industrial AI: Corrected critical thermal sensor drift across 5 years of historical manu- facturing data, improving predictive time-series model accuracy (R2) from 0 to 0.8.

• Energy Optimization: Forecasted a 3-5% reduction in energy waste by validating thermodynamics-informed predictive models against long-term commercial furnace operation.

• Advanced Instrumentation (NIH-Funded): Designed and built high-precision experimental testbeds (LDA, Ultrasound) to quantify aerosol decay rates and validate predictive flow models for confined environments.

• Harsh-Environment Sensors: Engineered a custom 4-layer physical rod sensor for corrosive, high-temperature glass melt furnaces, performing material compatibility analysis for corrosion and thermal resistance.

• Technical Leadership: Managed 40+ engineering students, modernizing the lab curriculum with hands-on Arduino hardware integration. Awarded ”TA of the Year.” University of Maine — Orono, ME 09/2019 – 05/2021

R&D Engineer (Master’s Research)

• Advanced Thermal Simulation (NSF-Funded): Built high-fidelity numerical models to analyze the tun- ability of graphene for heat transfer, demonstrating its commercial viability as a high-efficiency heat sink for energy systems.

Iran Radiator Industrial Group — Rasht, Iran 09/2015 – 07/2017 Production Team Member

• Fluid System Remediation: Prevented costly external leaks and product failures by redesigning the bleeder nozzle geometry of a float-operated vent system.

• Surface Engineering & Cost Analysis: Led a commercial feasibility study on applying superhydrophobic internal pipe coatings, optimizing for increased heating capacity against mass-production constraints. Omidi Industrial Machinery — Lahijan, Iran 06/2013 – 08/2015 Research and Development Engineer

• Mechanical Design & Crisis Mitigation: Engineered a custom 20-meter vertical conveyor to navigate strict underground spatial constraints, directly preventing a high-cost client machine recall.

• Thermal Systems Engineering: Delivered end-to-end 3D CAD designs, BOMs, and strict GD&T compliance for custom industrial air/water cooling tunnels.

EDUCATION

Ph.D. in Mechanical Engineering — The University of Toledo Expected 08/2026 Master of Science in Mechanical Engineering — University of Maine 05/2021 Master of Science in Mechanical Engineering — Zanjan University 05/2017 Bachelor of Science in Mechanical Engineering — Guilan University 01/2013

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