Machine Learning Computer Vision

“Emma” Noosh Nabizadeh, PhD

*******.****@*****.***

804-***-****

San Jose, CA 95125

Linkedin.com/in/nooshin-nabizadeh

WORK EXPERIENCE

AI Solutions Scientist

Intel, Corp. Santa Clara, CA Sept. 2018 - Present

• Drove development and adoption of Intel's OpenVINO toolkit in the healthcare space (directly responsible for over $20 million revenue in sales).

• Analyzed and optimized machine learning workloads for natural language processing and computer vision applications for dozens of healthcare companies.

• Delivered presentations at Intel Innovation Conferences and authored blogs on developed proofs of concept

(POCs).

• Conducted product demos and training sessions for new customers, e ectively showcasing the product's capabilities and resulting in a high onboarding rate.

• Collaborated with product managers, developers, and team leads to manage and deliver customer demands.

• Managed the OpenVINO development team's backlog, aligning with stakeholder needs.

• Mentored junior team members and provided guidance on competitive analysis and product ownership. Senior Machine Learning Software Dev Engineer

SIEMENS, Fremont, CA Aug. 2016 - Aug. 2018

• Developed a Deep Learning API for regression and classi cation using Keras.

• Led a project to accelerate OPC recipe production in VLSI design with deep learning techniques.

• Designed algorithms for runtime prediction and lithographic hotspot detection using CNNs.

• Co-advised a team of Ph.D. students on computer vision research in the medical eld.

• Software development and debugging in C++ and Python. copyright © 2024 Nooshin Nabizadeh, PhD

SKILLS

FIELDS OF EXPERTISE: Natural Language Processing (Transformer/BERT), Large Language Models, GenAI, Machine Learning, Deep Learning, Reinforcement Learning, Computer Vision, Data Mining, Data Engineering PROGRAMMING LANGUAGE: C/C++, Python, SQL, MATLAB

SOFTWARE PACKAGES: TensorFlow, Keras, PyTorch, LangChain, OpenVINO, OpenCV, Dlib, SPSS, Tableau, SAP SUMMARY

With over a decade of experience in Machine Learning and AI, I have a proven track record of developing and optimizing innovative solutions. My ability to meet critical deadlines and attention to detail ensures high-quality outcomes. I am passionate about leveraging new knowledge and cutting-edge AI technologies to drive e ciency and success in complex projects.

EDUCATION

UNIVERSITY OF MIAMI Coral Gables, Florida 2015

Doctor of Philosophy - Electrical and Computer Engineering / Machine Learning SHAHROOD UNIVERSITY OF TECHNOLOGY Shahrood, Iran 2009 Master of Science - Electrical Engineering - Computer Vision ISFAHAN UNIVERSITY OF TECHNOLOGY Isfahan, Iran 2006 Bachelor of Science - Electrical Engineering - Signal Processing SELECTED PUBLICATIONS

More than 20 papers with over 700 citations

Google Scholar: https://goo.gl/emWc6f

HONORS & AWARDS

IEEE International Symposium on Biomedical Imaging (ISBI) travel award 2015 Postdoctoral fellowship from Center for Computational Science, University of Miami 2015 Received a full scholarship for Ph.D. studies at the University of Miami 2010 - 2015 Received a full scholarship for Ph.D. studies at the Florida International University 2009 - 2013 Received a full scholarship for Ph.D. studies at the Virginia Commonwealth University 2009 - 2011 Graduate Academic Scholarship, Shahrood University of Technology, Iran 2007 - 2009 IMMIGRATION STATUS

US Citizen

copyright © 2024 Nooshin Nabizadeh, PhD

Computer Vision Engineer

ABSIST Miami, FL Nov. 2015 - June 2016

• Designed and implemented an automated vertebrae labeling system for spine MRI analysis using

exible mixture of parts algorithm (developed in C++ using OpenCV). Research Associate Fellow

CENTER FOR COMPUTATIONAL SCIENCE, UM Miami, FL June 2015 - May 2016

• Developed and released Drug Target Ontology (DTO) version 1.0 and 1.01 implemented in OWL Web Ontology Language.

• Collaborated in developing LINCS-DTO (LINDO) ontology using SQL, C++, and XML. Research Assistant

MILLER SCHOOL OF MEDICINE, UM Miami,FL Sept. 2010 - May 2015

• Designed and implemented a fully automatic algorithm to detect and segment stroke and tumor lesions in brain CT and MR images based on classical ML techniques.

• Designed and implemented a fully automatic algorithm for face detection and facial expression recognition using facial landmark and neural networks classi cation.

• Implemented a fully automatic algorithm for gesture/pose recognition using deformable part model and random forest classi cation.

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