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Work experience

September 2015October 2015

Junior Software Consultant

MHP Romania

Participated in a training program that covered programming principles and Java basics.

July 2015August 2015

Perl Intern


Learned basics of a new programming language (Perl). Acquired knowledge about Agile software development, and SCRUM principles, respectively.  Worked on an appointment management project, where I completed tasks such as providing an algorithmic solution to a development error in appointment time calculation, and exploiting database relations in the implementation of a cascade deletion method.

May 2014May 2014

WebDesign 4 WeBiz Course

Centrul de Afaceri TRANSILVANIA Business Center Cluj

Developed a music website using Wordpress and various other e-tools. Learned about the principles of eMarketing and mobile marketing techniques.

Sep 2013Oct 2013

Web Development Internship


Developed a blog and an online shopping website using technologies such as PHP, MySQL, HTML/CSS, Javascript and Git.


Oct 2016Jul 2018

Master's Degree in Applied Computational Intelligence

Babes-Bolyai University, Cluj-Napoca (Romania)

Expanded theoretical, applicative and practical knowledge of intelligent and computational paradigms inspired from natural science, social and linguistic fields. 

Topics covered in the syllabus included Machine Learning, Statistics & Probabilities, Data Analysis, Simulation Methods, Natural Language Processing and Agent Oriented Software Paradigms. 

Oct 2012Jul 2015

Bachelor in Computer Science

Babes-Bolyai University, Cluj Napoca (Romania) 

Learned the fundamental concepts of computer science and mathematics, developing a variety of applications that introduced numerous problem-solving methods and allowed me to gain an understanding  of software development and maintenance.

Sep 2008Jul 2012

Baccalaurate Diploma

”Nicolae Bălcescu” High School, Cluj-Napoca, Romania

Attended a wide range of courses with an emphasis on mathematics and computer science.


Programming languages

Python, Java

Mobile Development


Versioning Systems

Git, Bitbucket

Operating Systems

Microsoft Windows, Linux

Database administration


Development IDE

Eclipse, IntelliJ Idea, Android Studio


Jul 2011Present

Diploma de Español como Lengua Extranjera (Nivel B2)

Instituto Cervantes
Sep 2011Present

Cambridge ESOL Level 3 Certificate in ESOL International (Council of Europe Level C2)

University of Cambridge


Studying the Language of Mental Illness in Romanian Social Media Data

The topic of my dissertation was the quantification of mental illness language in Romanian social media data with the help of computational methods. Using machine learning classifier models such as Logistic Regression and Naive Bayes, the power of selected linguistic clues to discriminate mental illness topics like anxiety, depression or schizophrenia was assessed. Results obtained suggest that vocabulary among mental disorder topics in the addressed forum is largely distinct, with the exception of anxiety and depression, which share a significant amount of words, while the use of stylistic, structural, syntactical, emotional and conceptual markers to differentiate the topics leads to worse results. However, a series of meaningful correlations between selected emotional, conceptual and language complexity features and certain mental illness topics are established. 

The project was developed in Python, with libraries such as sklearn, numpy, scipy, matplotlib used to implement classifier models and any needed functionalities. During its course, which followed steps of research, data acquisition, software development and elaborate documentation, I gained valuable insight into the process of transforming a concept into a practical application by both considering existing approaches and bringing elements of novelty that adapt the solution to the task at hand. 

Sentiment-based Classification of Movie Reviews

For the Data Analysis and Machine Learning courses I took in the first year of my Master's program, I implemented a Naive Bayes approach towards classifying movie reviews based on the sentiment they express. The project was developed in Python, and used the NLTK package for language processing tasks. As results, it obtained around 80% accuracy in classifying the reviews by the correct class, which stands in line with literature results using this method.

By writing my own implementation of a standard machine learning algorithm, I improved my reasoning and critical thinking skills, as well as the ability to apply theoretical knowledge in a practical scenario.

Document Summarization

As a project for my bachelor's thesis, I developed an application which took a document of moderate length as input and generated a summary that contained the most relevant sentences within it as output. The project was written in C#, and the implemented approach was based on clustering methods: K-means, and hierarchical agglomerative clustering, respectively. It obtained satisfying results in terms of summary relevance with respect to the original text.

The development of this solution involved a continuous process consisting of multiple steps, from research and information collection to implementation, and, ultimately, testing and result analysis. Through it, I acquired valuable planning and decision-making skills, as well as experience in closely managing the evolution of a complex project.

Panic Management Application

I am currently developing an Android application designed to help in overcoming panic attacks. The creative drive behind it is giving the theoretical knowledge of panic attack management form in an Android context, with the goal of a final product that is of real help to people facing this issue.

This project was born out of my desire to contribute in a meaningful way to society using the skills I possess, and the ambition of a continuous personal progress. I am a quick learner, and I am driven to discover new ways in which any knowledge I gather can be applied.

Other projects

For a Decision Support System course, I developed a movie recommender system based on textual similarity methods, thus combining knowledge from one of my main areas of interest, natural language processing, with theoretical concepts of decision making. In this system, a user provided a movie, and the system generated the top n choices in the database by either computing the similarity between movie summaries (content-based recommendation; cosine similarity with TF-IDF vectors) or the similarity between content and metadata strings (crew, cast). This application was done in Python, using libraries such as sklearn, numpy, nltk or pandas for computations and TkInter  for creating a graphical user interface.

Another topic approached from two different perspectives was that of generating nurse rosters, problem first solved using genetic algorithms, and secondly, using constraint programming methods. This project has taught me the importance of choosing the right method for a given problem, as I discovered that genetic algorithms performed much better than constraint programming, and pushed me to look at a diverse array of evaluation techniques to replace traditional ones, not applicable here. Both approaches were implemented in Java, having a graphical user interface.  


  • A. Briciu and M. Lupea, "Studying the language of mental illness in Romanian social media", 2018 14th IEEE International Conference on Intelligent Computer Communication and Processing (ICCP), Cluj-Napoca, 2018 
  • M. Lupea and A. Briciu, "Formal concept analysis of a Romanian emotion lexicon," 2017 13th IEEE International Conference on Intelligent Computer Communication and Processing (ICCP), Cluj-Napoca, 2017, pp. 111-118.
  • A. Briciu and M. Lupea, "RoEmoLex - A Romanian Emotion Lexicon", Studia Universitatis Babeș-Bolyai Informatica, v. 62, n. 2, p. 45-56, 2017.