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SYED BILAL HODA
Class of 2020
BS Computer Science
Minor: Mathematics
Aspiration Statement
“As a career I am inclined towards data analysis and machine learning. In order to have a strong mathematical background, I have done a minor in mathematics so that it provides me the framework to engage in complex problems and assists me in my career path.”
Core Skills
- Python, C++, JavaScript, Html, CSS
- Bootstrap, SQL Server, LaTeX and Google Cloud Platform
- Data Analysis and Machine Learning
- Angular 8
- Pytorch and Scikit Learn
- Data Visualization
- Natural Language Processing (NLP)
- Algorithm Design
- Experiment Design
- Experimental Analysis
Academic Awards / Achievements
- HU TOPS 100% Scholarship
- University of Michigan Ann Arbor Summer Program - 2019
Experience
Leadership / Meta-curricular
- Science and Technology track of HPAIR (Harvard Project for Asian and International Relations) Conference held at Nur-Sultan, Kazakhstan 2019 - Participant
- Google I/O Extended - Organizer
- Habib University Artificial Intelligence Club - Vice President
Internship / Volunteer Work
- Careem (Apr 2021 - Present) - Data Analyst [Data & AI]
- Afiniti (Jun 2020 - Apr 2021) - Jr. Data Scientist [AI Production]
- Veritas Learning Circle - Curriculum Developer
- DSSE Public Lectures at Habib University - Secretary
- Teaching Assistant - Habib University
Publications / Creative Projects
- Raytracer–Computer Graphics:: Created ray tracerfrom scratch in C++to render multiple scenes and images.
- Flight Simulation–Computer Graphics: Created a flight simulation using Html, CSS, JavaScript and WebGL.
- Next Word Predictor for the Urdu Language–Artificial Intelligence: A word corpus was prepared by scraping data from online news websites. A skip-gram model was trained to learn word embedding and an RNN model was trained to predict the next word.
Final Year Project
Project Title
Prediction of Call Arrival Time and Rates
Description
The Final Year Project is in collaboration with Afiniti, a leading organization working in Artificial Intelligence. Call centres have various types of customers calling in. The problem is to devise algorithms that can predict the time of the next call, call category and call volume in an interval within a reasonable degree of accuracy. (Group Project)
Project Pictures
