About
I am a PhD student. I completed my Master's Degree in Electrical & Computer Engineering with an emphasis on Data Science and Machine Learning from the University of Arizona, and Bachelor's Degree in Electrical Engineering from Boise State University. I am passionate about turning complex data into actionable insights, providing a data-based decision, and putting old ideas together in new ways to come up with creative, simple solutions to complicated, nebulous problem statements. I am constantly working on developing my technical skills as well as soft skills, in order to become a data scientist.
Graduate Assistant
In progress ....
- Lab Website: In progress
- City: Boise
- Degree: Doctorate
- Email: robiny@email.arizona.edu
- Freelance: Available
About projects and dissertation plans coming soon....
Skills
Bayes Theorem, Central Limit Theorem, Hypothesis Testing, Forecasting
Pandas, NumPy, Scikit-learn, TensorFlow, Keras
nltk, SpaCy, genism, TextBlob, Topic Modelling, Sentiment Analysis
NumPy, SciPy, Pandas, dpylr, Plotly
matplotlib, seaborn, ggplot2, Tableau, PowerBI, Pyplot
AWS EC2, AWS SageMaker, GCP
Resume
Education
Doctor of Philiosphy -
Aug. 2021 - Present
University , City, State
Master of Science - Electrical & Computer Engineering
Aug. 2018 - May 2020
The University of Arizona, Tucson, AZ
Bachelor of Science - Electrical Engineering
Aug. 2015 - May 2018
Boise State University, Boise, ID
Experience
Graduate Teaching Assistant
Aug. 2018 - May 2020
The University of Arizona, Tucson, AZ
- Delivered lectures on lab topics; instructed 300+ undergraduate students on process of debugging and testing electrical and electronic circuits using test equipment
- Assisted professor in grading assignments and preparing all necessary lab components
- Provided students with thorough introductions and explanations for each step of the experiments, clearly answering all questions
Graduate Research Assistant
Aug. 2018 - Jan. 2020
The University of Arizona, Tucson, AZ
- Researched various quantization-optimization algorithms (QSGD, SignSGD, TernGrad, k-level Quantization) to study how these algorithms can reduce the amount of information sent between ML systems without losing the essential data
- Derived the mathematical relationship of algorithms with a Distributed Machine Learning system setup
- Analyzed, extracted, and flattened complex data structures to utilize different data formats
- Assisted Ph.D. students in setting up a complete machine learning pipeline for model training to perform mathematical simulation
Data Scientist - Internship
May 2019 - Aug 2019
Vercend (now Cognitive), Kathmandu, Nepal
- Performed data integrity checks, data cleaning, exploratory analysis, and feature engineering using R and Python
- Trained data with different classification models such as decision trees, SVM, and random forests
- Executed data transformation method for rescaling and normalizing variables in collaboration with Senior Data Scientist and Application Development Engineer
- Owned, designed, and built end-to-end auto machine learning engines to automate data scientists’ work at scale
- Presented data insights and model key metrics through Tableau dashboard to 4–5 senior leaders and clients
Eelctrical Engineering - Internship
Feb. 2018 - July 2018
WMDTech Inc., Boise, ID
- Performed electrical prototyping by simulating the circuits to use as the schematics in the PCB board using SPICE simulator
- Created, maintained, and updated symbol and footprint libraries for the components used in PCB board
- Planned cost reduction while selecting components for the PCB without reducing functions of the components in the PCB Board
- Implemented PCB layout by coordinating with the customer and maintaining PCB manufacturing requirementsTested PCB board functionality using oscilloscope, logic analyzer, multimeter after placing electronic components on PCB boardPresented data insights and model key metrics through Tableau dashboard to 4–5 senior leaders and clients
- Collaborated on a team with 4–5 members; utilized planning skills to ensure that component costs were within limits