Hi I am Mahsa Hajotfalia
Personal Information
• First and last name: Mahsa Hajlotfalia
• Date and place of birth (city-country): 3 July
1993 Yazd-Iran
• Phone: +4915733791092
• Email: mahsa.lotfalia@partner.kit.edu
• github:
www.github.com/mlotfalia
• LinkedIn:
www.linkedin.com/in/mahsa-lotfalia-243a7752
Education
1-Amirkabir University of Technology, Tehran,
Iran(2020-2022/October)
• 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 system
• Supervisor: Dr. Mehdi A. Sarram
Research
1-The 17th National Conference on Computer Science and Engineering and Information Technology(2022-october)predicting overal position of startups using machine learning(persian)You can see the certification here.
2-The first international conference on business development and digital transformation(2022-November)Startup success prediction using machine learning(English-persian) here.
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 data, machine learning, natural language processing, extracting deep feature from social media, news and text data.
Honours and Awards
1-Ranked first (among 12 Msc students) of Information Technology Engineering(E-Commerce) whom started their graduate studies in the academic year of 2020-2022(October).
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.
Forecasting the future trend of Iranian stock market using ARIMA model. You can see the project stock market prediction here.
4-Extracting deep features from textIntroducing a model for sentiment analysis by CNN text classifier and BERT algorithm. You can see this project here.
5-image detectorDetecting the image by CNN. You can see this project here.
6-Developing strategy for Iran alloy steel companyDiscover the processes and steps to build a prospect and strategy for the next 5 years-2021
7-Digital transformation in insurance companyFinding and assessing the digital transformations trends in the insurance companies in the United State of America-2021
8-Investigating the relationship between digital marketing and AIBy investigating the latest articles and interviewing with experts-2021
9-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.
Teaching Experience
1-Articial Intelligence Teacher Assistant at the Yazd University
under supervision Dr.Derhami (Winter 2014).
2-Reengineering Business process, Assistant at the Amirkabir
University, Under supervision of Dr. Kermani (Winter 2021)
* Responsibilities included holding problem solving sessions,
course lectures, setting and grading homework, projects and exams.
3-Tutoring
• Python: For new students entering Yazd Institute (Summer 2017)
Job Experience
1-Vira Group as a member of the Asp.net programming team(HTML/CSS,
JavaScript, 2016-2018).
2-Isatis Pouya Group as a member of the machine leaning team
(2018-2021).
3-Work as a freelancer designing and developing web
application(2021-2022)
4-Development of Iranian alloy steel as a member of the
development group (from 2022).
Technical Skills
1-Programming languages: Python, Html/Css, Javascript, React.2-Machine Learning Libraries: Numpy, Pandas, Scikit-Learn.
3-Deep Learning Platforms: Keras, TensorFlow, Scikit-Learn.
4-other software skills: Latex, git, github, Power BI, WordPress, Figma, Visio.
5-Language:
• Persian(native)
• English(fluent, IELTS score: 6.5 )
• Germany(Elementary).
Extera 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
3-Dr.S.Alireza Hashemi Golpayegani
• Assistant Professor
• Department of Computer Engineering
• Amirkabir University of Technology
• Email : sa.hashemi@aut.ac.ir
• Phone: +9821-64542726
View all projects
