Hamid Ziyaee, PhD, PE

仚 San Diego, CA ***** 858-***-**** ad4yyi@r.postjobfree.com LinkedIn GitHub SKILLS

Programming: Python, Matlab, Linux, SQL, C++, HPC, OpenMP, MPI, Shell scripting Tools: TensorFlow, PyTorch, AWS, Scikit-Learn, OpenCV, JMP, KNIME, Git, GitHub,Tableau, ParaView Technical Skills: Regression, KNN, SVM, Random Forest, Optimization, Predictive Modeling, Clustering

(DBSCAN, GMM, K-Means), PCA, Deep Neural Network (MLP, CNN, RNN, nnU-Net) Designing and Modeling: NX, Solid Works, Ansys, AutoCAD EXPERIENCE

Mechanical System Engineer, Applied Materials, Santa Clara, CA Jul 2022 - Nov 2023

● Modeled data to root cause analysis of complex problems in chamber during deposition, cleaning process

● Conducted data analysis on chamber performance, system parameters to identify areas for improvement

● Created assemblies by designing components, parts using NX, and producing detailed drawings

● Optimized thermal and fluidic systems to ensure better deposition uniformity on wafers

● Analyzed the conductance of chamber components to improve deposition transition time in chamber Postdoc Fellow, Data Scientist,MD Anderson Cancer Center-Radiation Physics, Houston TX Nov 2020-Jul 2022

● Developed an automated framework to segment tumors on brain MRI images

● Created an automated model to classify patient MRIs based on tumor type, necrosis or progression

● Applied deep learning methods to detect lesions on whole body PET - CT images

● Developed a novel tool to quantify changes in tumor characteristics over time using radiomic features, improving understanding of disease progression and treatment efficacy Data Science Fellow, Insight Data Science, Los Angeles, CA Sep 2020 - Nov 2020

● Developed an automated framework for monitoring the water flow activity using acoustic signals received from sensors mounted on pipes in the residential or commercial buildings

● Identified any sort of unusual flow in water consumption using semi-supervised machine learning methods Research Assistant, University of Houston, Houston TX Apr 2017 - Jan 2020

● Developed machine learning models to predict thermal conductivity of non-metal materials

● Developed a novel semiconductor material, Boron Arsenide (BAs), with ultrahigh thermal conductivity, leading to breakthroughs in thermal management and energy-efficient electronics

● Conducted experimental measurements of thermal conductivity, heat capacity, and thermodynamic properties of BAs, contributing to the development of reliable models for predicting material behavior Mechanical Project Engineer, General Electric, Houston TX Apr 2013 - Apr 2017

● Developed predictive models to assess the capacity of gas turbines across operational hours

● Handled incoming technical issues by offering solutions to manufacturing and project management teams

● Took charge of projects by meticulously preparing equipment lists, bills of materials, and piping and instrument diagrams, demonstrating strong organizational and project management skills EDUCATION

● PhD in Mechanical Engineering, University of Houston Jan 2020

Miner in High Performance Computing and Data Analysis

● MS in Mechanical Engineering, University of California San Diego Mar 2012 LICENSE/ CERTIFICATE

● Licensed Professional Engineer (PE) - Texas Board of Professional Engineers

● Machine learning certificate - Stanford University

● Deep learning and data mining/ Programing with Python/ Data visualization/ HPC - University of Houston

● Computer vision nanodegree/ Machine learning nanodegree/ SQL for data analysis/ Git & Github- Udacity RELATED PUBLICATION

● Automated Brain Metastases Segmentation With a Deep Dive Into False-positive Detection H Ziyaee, CE Cardenas, DN Yeboa, J Li, L Court, et al Advances in Radiation Oncology journal 2023

● Thermodynamic Calculation and Its Experimental Correlation with Growth Process of Boron Arsenide Hamid Ziyaee, H Sun, Zhifeng Ren, et al Journal of Applied Physics 2019

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