website/content/pages/Resume.md

+++
date = "2017-05-03T10:30:52-04:00"
title = "Resume"

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Printable single page version [here](/andrei-stoica-resume.pdf)

Education
---------
* **Bachelor of Science - Computer Science**,				{{< date "2018" >}}
<br>*Ontario Tech University, Oshawa, ON* 

* **Master of Science - Computer Science**,
	{{< date "Expected Completion 2020" >}}
<br>*Ontario Tech University, Oshawa, ON*

Work Experience		
--------------------
* **Teaching Assistant**
*University of Ontario Institute of Technology (UOIT), Oshawa, ON* 
<sup>{{< date "Sept. 2017 - May 2020" >}}</sup>
	- Lead classes of 20-25 junior and senior level undergraduate
		students on in-class activities
	- Corrected student work and provided feedback for improvement
	- Courses:
	{{< shortlist >}}
		  Mobile Devices
		- Programing Workshop
		- System Development and Integration
		- Web Development
		- Interactive Media
		- Compilers
	{{< /shortlist >}}

* **Graduate Research Assistant**
*University of Ontario Institute of Technology (UOIT), Oshawa, ON* 
<sup>{{< date "Aug. 2018 - Present" >}}</sup>
	- Lead the research on text mining and natural language processing
	queries in relational databases
	- Topics and Technologies used: PostgreSQL, topic modeling, NLP,
	Python, web services

Software Development Experience
--------------
*	**Programing**
{{< shortlist >}}
		Python
	- Java 
	- Clojure and ClojureScript
	- C/C++
	- Kotlin
	- Scala
{{< /shortlist >}}

* **Data Science**
{{< shortlist >}}
		Numpy
	- Scipy
	- NLTK
	- Gensim
	- Pandas
	- Ipython Notebooks
{{< /shortlist >}}

* **Database**
{{< shortlist >}}
		PostgreSQL
	- MongoDB
{{< /shortlist >}}

* **Web Serices**
{{< shortlist >}}
		Flask
	- NodeJS
{{< /shortlist >}}

* **Web Frontend**
{{< shortlist >}}
		HTML
	- CSS
	- ClojureScript
	- JavaScript
	- Reagent
	- React
	- JQuery
{{< /shortlist >}}

* **ML/AI**
{{< shortlist >}}
		Tensorflow
	- scikit-learn
	- word2vec
	- fasttext
{{< /shortlist >}}


Project Experience
------------------
* **NLP Relational Queries And Its Applications** - *Thesis Project*
	- Developed LDA extension to PostgreSQL to allow Topic Modeling of
		text columns inside of SQL
	- Created a web front end to visualize the change in topics over time for
		academic authors and venues
	- Published 2020 IEEE International Conference on Information Reuse
		and Integration for Data Science

	Technologies: 
	{{< shortlist >}}
			Python 
		- SQL/PostgreSQL 
		- Flask
		- HTML
		- CSS
		- D3.js
	{{< /shortlist >}}


* **Scalable Analysis of Open Data Graphs**
	- Performed analysis of similarities between documents through
		Canada’s Open Data portal
	- Provided insight into organization and connectedness of Canada’s
		Open Data
	- Scalable and Distributed code base to allow for large dataset and
		scaling with time
	- Published and Presented at 2019 IEEE International Conference on
		Information Reuse and Integration for Data Science
	
	Technologies:
	{{< shortlist >}}
			Python
		- SQL/PostgreSQL
		- Apache
		- Spark/PySpark
		- Matplotlib
		- GCP Storage
		- GCP Dataproc
	{{< /shortlist >}}


* **Canadian Political Twitter Analysis**
	- Built tools to track and analyse the conversation surrounding
		Canadian politics on Twitter
	- Tracked key figures and CDNPoli hashtag and predicted standings in
		2019 election

	Technologies:
	{{< shortlist >}}
			Python
		- Tensorflow
		- SQL/PostgreSQL
		- Matplotlib
	{{< /shortlist >}}

Publications
------------

* Stoica, A., K. Pu, and H. Davoudi (2020).  “NLP Relational Queries And Its
	Applications”. In: 2020 IEEE 21th International Conference on Information
	Reuse and Integration for Data Science (IRI).

* Stoica, A., M. Valdron, and K. Pu (2019).  “Scalable Analysis of Open Data
	Graphs”.  In: 2019 IEEE 20th International Conference on Information Reuse and
	Integration for Data Science (IRI), pp. 334–341. DOI: 10.1109/IRI.2019.00059.

Hobbies
-------

* Free and open source software enthusiast
* Maintain a home media and storage server for family running the latest
	Ubuntu LTS
* Build computers for others, source and consult on components required,
	install and teach them to install themselves