Lily Ho

Monterey Park, CA 805-***-**** advmoc@r.postjobfree.com www.linkedin.com/in/lily-ho-machinelearning Results-driven and analytical Mechanical and Machine Learning Engineering Professional with 15+ years in researching designing, developing, and implementing machine learning and deep learning systems. Demonstrated success in creating novel applications to make critical predictions and calculating optimization algorithms to facilitate data-driven decision- making capability. Expertise in data analysis, R&D, CFD modeling and simulation, application development, process improvement, project management, and deep neural network. Professional Experience

Department of The Navy China Lake, CA

Machine Learning Engineer June 2002 - December 2022 Department of The Navy China Lake, CA

Mechanical Engineer June 2002 - December 2022

Core Competencies

Machine Learning, Deep Learning, Application Development, Analytics Development, Research and Development, Machine Learning Approach and Algorithm, Efficiency in Windows and Linux system Technical Skills

Python, C++, TensorFlow, keras in Jupyter Notebook, Numpy, Pandas, Scikit-learn, Fortran 90, Java, VBS, MATLAB Programming, SQL

Education/Trainings

Master of Science in Thermal Fluid, California State University Bachelor of Science in Chemical Engineering, Guangxi Engineering Institute Training in Stanford CS 229 Machine Learning, CS 230 Deep Learning, CS 231N Computer Vision, Stanford University

Supported 3 clients in making data-driven decisions through the creation of 3 customized applications, designed to make critical predictions and calculate optimization algorithms that elevated clients’ experience

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Improved model performance in solving machine learning trained model problems through development of CNN image classification models using data augmentation techniques and residual and inception architecture

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Successfully solved lower prediction accuracy and higher false alter problems in radar image classification and increased 8% accuracy for helicopter detection system via design and execution of CNN deep learning models

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Integrated 3 trained models, identified 2 performance improvement opportunities, and executed process improvements through cross-functional collaboration with 4 multi-disciplinary product development teams

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Proposed novel machine learning models for data extraction and analysis after assessing available video records of project testing as training, testing data sets, and researching technical details

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Researched and studied new technologies to support machine learning applications and drive operational performance across organizations’ initiatives

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Optimized analysis processes by formulating conversion modeling between 3 application software, resulting in higher productivity

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Identified appropriate datasets and data representation methods, implemented machine learning tests and experiments and performed analysis and fine-tuning using test results

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Aided the department of the navy in improving cutting-edge weapon systems by researching to analyze the feasibility, design, operation, and performance of air-breathing solid ramjet, motors, and test systems

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Modified 4 instrument designs to meet requirements and eliminate malfunctions to achieve successful standard missile tests on scheduled under budget in aero- thermal test facility

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Presented design improvements in design review meetings and built multiple computational models using Computational Fluid Dynamics tools and thermal tools for life cycle analysis to support different programs

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Supported a client in generating $1M of cost-savings within the space program by suggesting cost-saving proposals for the customer's test facility to avoid outsourcing the contract

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Generated system concepts to satisfy product requirements and assessed the final product's thermal environment to contribute to the Joint Strike Fighter weapon's certificate

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