ALI MUHAMMAD ASAD

ALI MUHAMMAD ASAD

Class of 2025
BS Computer Science
Minor: Mathematics

Aspiration Statement

AI, ML, DL, LLMs, Robotics, Cloud Services and Devops, Graph Data Sciences, Research, Graduate Studies etc.

Core Skills

  • C++, Cypher, Linux, Neo4J, PostgreSQL, Python, Research Skills, SQL, Tex

Academic Awards / Achievements

  • HU awarded a 50% Grant

Experience

Leadership / Meta-curricular

  • GSCP (Including STRP1 and STRP2) Stanford Summer Exchange Program, 2024 (HU awarded a 50% Grant), Treasurer, Natural Science Club, 2022-2023, Gen Sec, CSEC 2023-2024, Content Lead, Gaming Club, 2023-2024, Operations Member, Serve Club, 2023-2024, Table Tennis Lead, SNRC, 2023-2024, GDG, Tech Team Member, 2024-2025

Internship / Volunteer Work

  • Intern, CHKK (Feb 2025 April 2025), Data Science Intern, 10Pearls (June 2024 Aug2024), OBE Student Employee, Habib University (Dec 2023 Jan 2025), TAships, Habib University (TAships)

Publications / Creative Projects

  • Research paper and simulation on indoor navigation for the visually impaired using smart mobile robots (no publication), Research paper on poet attribution using deep learning techniques (in process of publication soon), Research paper on evolving L systems using evolutionary algorithms (no publication), Developing a large language model (LLM) for the Urdu language (once completed will result in multiple publications)

Final Year Project

Project Title

Alif - Developing A Pre-Trained Generative Large Language Model for the Urdu Language

Description

The project is basically to develop a large language model specifically curated for the Urdu language. It is the first language model to be developed for Urdu from scratch, with performance comparable to the current state-of-the-art models such as ChatGPT etc. Since its going to be much smaller than those state-of-the-art models, it will be a low-cost solution for NGOs, banks, and organizations in Pakistan to develop AI solutions for their businesses for the local community as it would adhere to the local context.