Hi I am Mahsa Lotfalia

Personal Information

• First and last name: Mahsa Haj Lotfalia
• Date and place of birth (city-country): 2July 1993 Yazd-Iran
• Nationality: Iranian
• Phone: +98913-259-9872
• Email: mahsa.lotfalia@gmail.com
• github: www.github.com/mlotfalia
• LinkedIn: www.linkedin.com/in/mahsa-lotfalia-243a7752

Education

1-Amirkabir University of Technology, Tehran, Iran(2020-2022)
• M.Sc. in Information Technology Engineering(E-Commerce)
Overal-GPA: 4/4
Master Thesis: Predicting the success of startups based on online data using machine learning - Score: A
Supervisor: Dr. Mohammad Akbari(akbari.ma@gmail.com)
2-Yazd University, Yazd, Iran(2011-2015)
• B.Sc. in Software Engineering
Dissertation: Implementation of electronic health records
Supervisor: Dr. Mehdi A. Sarram

Research

1-The 17th National Conference on Computer Science and Engineering and Information Technology(october-2022)

predicting overal position of startups using machine learning

2-The first international conference on business development and digital transformation(November-2022)

Startup success prediction using machine learning

3-Member of data science innovation Lab of Amirkabir University of Technology a researcher. You can see the web site here.

Research Interests

• I am interested in predictor models for commerce and health under uncertainty and instability data, machine learning, deep learning, extracting deep feature from social media, news and text data.

Honours and Awards

1-Ranked 2st among M.Sc students of Information Technology Engineering(E-Commerce) whom started their graduate studies in the academic year of 2020-2022.

2-Ranked within the top 0.1% in Iran's 2011 National Universities Entrance Exam.

Selected Projects

1-Predicting the success of startups based on online data using machine learning(Master Thesis)

Predicting the success of startups based on online data using machine learning-Due to the high uncertainty and instability of the startup ecosystem in the early stages. This research provide a solution to predict the startup's success in the future. Collecting Heterogeneous data from three different sources and introducing a late fusion model for predicting the success of startups using deep features, handicraft features, Machine Learning, Deep Learning and NLP model has been presented to facilitate the investment process of investors.

2-clustering a mall customers using customers data cards and market purchasing analysis for predicting how much they spend in future. You can see this project here.

3-Predicting the future trend of a stock exchange in Iran

Forecasting the future trend of Iranian stock market using ARIMA model. You can see the project stock market prediction here.

4-sentiment analysis by dictionary based model

Extracting the emotions of tweets using NRCLex model which is a dictionary based model made by National Research of Canada. You can see this project here.

5-Extracting deep features from text

Introducing a model for sentiment analysis by CNN text classifier and BERT algorithm. You can see this project here.

6-Front-End projects
Translation: Built using HTML, an active API, advanced CSS, and React. You can see this project here.
Weather App: Built using HTML, an active API, and advanced CSS and JavaScript. You can see this project here.
Yoga App: Built with HTML, CSS, and JavaScript here.
Market App: Built with Typescript, Tailwind, React.js, Next.js.

Job Experience

1-Vira Group as Member of the Asp.net programming team(HTML/CSS, Javascript, 2016-2018).
2-Isatis pouya Group as Member of the machine leaning team(Stock Market Prediction, 2018-2021).

Technical Skills

1-Programming languages: Python, R, Html/Css, Javascript, React.
2-Machine Learning Libraries: Numpy, Pandas, Scikit-Learn.
3-Deep Learning Platforms: Keras, TensorFlow, Scikit-Learn.
4-Software: Power BI, WordPress, Figma, Visio.
5-Language:
• Persian(native)
• English(fluent, IELTS score: 6.5)
• Germany(Elementary, B2).

Certifications

1-Nuarl Network and Deep Learning.
2-Web-Development.
3-Systematic Team Coaching(Ten Truth about CouchMe Team Coaching)
Webinar 1.
Webinar 2.

References

1-Dr.Mohammad Akbari(Supervisor)
• Assistant Professor
• Department of Mathematics and Computer Science
• Amirkabir University of Technology
• Email : akbari.ma@aut.ac.ir
• Phone: +9821-64545875
2-Dr.Mohsen Abarpour Shirazi(Director of department)
• Associate Professor
• Department of Industrial Engineering & Management Systems System & Productivity Management
• Amirkabir University of Technology
• Phone: +9821-66470312

Hobbies

1-Front End Developing
2-Self Development

View all projects
Mahsa Lotfalia

Work Inquiry

let's work together and i'll help you by my all best