ML Engineer/Informatics Engineer

Arash Parsa

1-925-***-**** *****.*******.*****@*****.*** linkedin github.com/arashmehrabiparsa github.com/arashmparsa Professional Summary

ML Scientist with expertise spanning synthetic biology engineering, ML model development, signal processing and EDA. Education

Georgia Institute of Technology Atlanta, GA

Masters of Science in Data Science/Analytics August 2022 - July 2025 University of California, Santa Cruz Santa Cruz, CA Bachelors of Science in Bioengineering/Bioinformatics Aug. 2015 – Jun 2021 Experience

Machine Learning Scientist Sep. 2022 – Present

Optelligence Berkeley, California

• Developed and trained ML models for hardware performance prediction, reducing testing time by 50%

• Implemented data preprocessing pipelines and A/B testing framework improving deployment efficiency by 25%

• Applied deep learning techniques to materials science problems using TensorFlow and PyTorch R & D Engineer Aug 2021 – May 2022

Amgen & Thermofisher Thousand Oaks, CA & Pleasanton, CA

• Processed 100+ COVID-19 testing kits daily maintaining 99.8% quality standards

• Optimized HPLC/UPLC systems reducing analysis time & operational costs by $50K annually

• Automated quality control workflows using Python scripts, data processing, and statistical analysis Scientific Researcher & Research Consultant Jan. 2016 – Nov. 2019 Apex Energetics Irvine, California

• Conducted research on 15+ nutraceutical compounds (Bacopa monnieri, Gingko Biloba) for clinical applications

• Analyzed 200+ research papers monthly, creating comprehensive database reports that saved 20 hours/week DARPA Research Assistant 2018 – 2019

UC Berkeley SWARM Lab Berkeley, CA

• Developed GUI for microdrone assembly systems, eliminating need for additional technical hires

• Created user-friendly software interface for robotics project, saving lab thousands in personnel costs Research Collaborator Dec. 2024 – Present

TECH Lab, UCSF (Washington Lab) San Francisco, CA

• Reviewing and synthesizing literature on AI/ML applications in mobile health to support novel digital diagnostic and therapeutic tool development, with anticipated co-authored publications Projects

Progesterone Biosynthesis (iGEM) Metabolic Engineering, Synthetic Biology 2018

• Engineered Y. lipolytica for progesterone biosynthesis via metabolic pathway engineering; designed 5-gene cassette

• Executed 3 parallel cloning strategies: Gibson Assembly, yeast-mediated cloning, and Cre-Lox recombination

• Led international outreach across 15+ countries; co-authored 60-page published research report Nanotech Stroke Rehabilitation System Signal Processing, Data Analysis 2025 - present

• Engineered DAQ system w/ carbon nanotube arrays; performed signal processing and data preprocessing

• Developed non-invasive rehabilitation devices with real-time data processing and microfluidics for disease detection IoT CO2 Monitoring System (Patent Pending) IoT, Data Processing, Python 2021

• Designed autonomous monitoring system with 24-hour battery life; filed provisional patent

• Integrated embedded systems with cloud-based analytics for real-time data processing and monitoring Technical Skills

Programming: Python, SQL, C++, JavaScript, R, MATLAB, HTML/CSS Machine Learning: TensorFlow, PyTorch, scikit-learn, XGBoost, model training, hyperparameter tuning Data Science: Data preprocessing, feature engineering, signal processing, statistical analysis, time series analysis Cloud & DevOps: AWS, Docker, Kubernetes, Git, Linux, Node.js, REST APIs, microservices, distributed systems, cloud architecture, CI/CD, Redis

Data Analysis: Pandas, NumPy, Matplotlib, PostgreSQL Molecular Biology: PCR (standard, OE-PCR, colony PCR), Gibson Assembly, yeast transformation, homologous recombination, Cre-Lox, plasmid cloning, primer design, DNA isolation, gel electrophoresis, Sanger sequencing Synthetic Biology: Metabolic pathway engineering, gene cassette design, CRISPR, heterologous expression, recombinant DNA Bioinformatics: KEGG, sequence alignment, plasmid design, genome analysis

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