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Shayan Aamir
Aspiration Statement
I want to pursue a career in Data Science and Machine Learning. My plan is to pursue a Master's degree in Machine Learning and work in different domains of Machine Learning, including Deep Learning, Natural Language Processing, and Computer Vision.
Core Skills
- Adaptability
- Communication Skills
- Deep Learning
- Machine Learning
- Natural Language Processing
- Python
- Time Management
Academic Awards / Achievements
- President’s List, 2022
- Dean’s List, Fall 2022
- Dean’s List, Spring 2022
- President’s List, 2021
- Dean’s List, Fall 2021
- Dean’s List, Spring 2021
- Achieved Regional Distinction - CAIE Examination, 2016
Experience
Leadership / Meta-curricular
- Winner, IFTP 2023, Habib University
- General Secretary, Artificial Intelligence Club
- Treasurer, Young Leaders Club
- President, STEM Society
Internship / Volunteer Work
- Teachers Assistant, Deep Learning, Habib University (August 2022 – December 2022)
- Researcher, Summer Research Program (June 2022 – August 2022)
- Backend Team, Securiti.ai (June 2022 – July 2022)
- Free Lance Technical Writing, Habib University (December 2019 – February 2023)
- Teachers Assistant, Probability and Statistics, Habib University (January 2022 – May 2022)
Publications / Creative Projects
- Published: Urdu Music Genre Classification Using Convolution Neural Networks in IEEE Xplore
- Working on Sentiment analysis on Urdu and Roman Urdu for publication
Final Year Project
Project Title
Mai - A Transformer-Based Urdu Chatbot for Menstrual Health and Hygiene
Description
In rural areas of Pakistan, young women do not have access to accurate information regarding menstruation and proper sanitary products. Even though menstruation is a regular and natural event for women, it is still a delicate and taboo subject, particularly in Pakistan. Our project (Mai) is a transformer-based chatbot that will serve as a safe space to get women’s questions answered without the fear of being judged or punished for educating themselves about an essential part of their anatomy. It is trained on a dataset that has been verified by multiple doctors and aims to provide accurate information to the users.