To be on the forefront of advancements in Machine Learning, AGI, Embodied AI and Robotics.<\/p>\n
alimuhammad7465@gmail.com
\nhttps:\/\/www.linkedin.com\/in\/muhammad-a1i\/<\/p>\n
+92 333 391 3931<\/p>\n
Dhanani School of Science and Engineering
\nBS Computer Science<\/p>\n
2025
\nC++, CUDA, MATLAB, Python, Pytorch
\nPresident List (2022, 2023, 2024) Dean’s List (Spring 2022, Fall 2022, Spring 2023, Fall 2023, Spring 2024, Fall 2024) High Achievement Merit Scholarship (Fall 2022, Spring 2023, Fall 2023, Fall 2024)
\nWinner Faysal Bank FinTech Hackathon, 2024 Vice President, Maths Club 2023-2024 Technology Mentor\/Instructor, Wujood Adult Literacy Program, SerVe CLub, 2022-2023 SET Alumni Network – Core Team Member
\nResearch Intern, Texas A&M (May July 2024)
\nAnalysis of the Banach Tarski Paradox
\nALIF – A Pretrained Urdu Generative Model
\nAlif is a language model for Urdu which understands cultural nuances and contexts without being computationally expensive. Large Multilingual Language Models are mostly trained for languages like English, French, German. For underrepresented languages like Urdu, these models often produce ill-nuanced responses. State-of-the-art LLMs like GPT perform well to an extent in Urdu, but too computationally. Environmentally and financially, they are expensive to use. For local governments using these models could incur a huge training, and end point usage cost. Organizations like OpenAI cannot be trusted with sensitive data of banks and governments which is why using API is not a viable option. Therefore, we are working to build a Small Language Model which is significantly smaller in size than the large multilingual models but gives similar performance for Urdu language.<\/p>\n","protected":false},"excerpt":{"rendered":"
To be on the forefront of advancements in Machine Learning, AGI, Embodied AI and Robotics. alimuhammad7465@gmail.com https:\/\/www.linkedin.com\/in\/muhammad-a1i\/ +92 333 391 3931 Dhanani School of Science and Engineering BS Computer Science 2025 C++, CUDA, MATLAB, Python, Pytorch President List (2022, 2023, 2024) Dean’s List (Spring 2022, Fall 2022, Spring 2023, Fall 2023, Spring 2024, Fall 2024) […]<\/p>\n","protected":false},"author":9,"featured_media":6393,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"single-graduate-01.php","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"program":[29],"school":[42],"class":[41],"minor":[52],"class_list":["post-6254","graduate","type-graduate","status-publish","format-standard","has-post-thumbnail","hentry","program-bscs","school-dhanani-school-of-science-and-engineering","class-class-of-2025","minor-not-applicable"],"acf":{"aspiration_statement":"To be on the forefront of advancements in Machine Learning, AGI, Embodied AI and Robotics.","video_profile_link":"","habib_email":"","email":"alimuhammad7465@gmail.com","linkedin_link":"https:\/\/www.linkedin.com\/in\/muhammad-a1i\/","portfolio_Title":"","portfolio_link":"","personal_cell_1":"+92 333 391 3931","personal_cell_2":"","core_skills":[{"skill":"C++, CUDA, MATLAB, Python, Pytorch"}],"academic_awards":[{"academic_record":"President List (2022, 2023, 2024) Dean's List (Spring 2022, Fall 2022, Spring 2023, Fall 2023, Spring 2024, Fall 2024) High Achievement Merit Scholarship (Fall 2022, Spring 2023, Fall 2023, Fall 2024)"}],"leadership-experiences":[{"leadership":"Winner Faysal Bank FinTech Hackathon, 2024 Vice President, Maths Club 2023-2024 Technology Mentor\/Instructor, Wujood Adult Literacy Program, SerVe CLub, 2022-2023 SET Alumni Network - Core Team Member"}],"work-experience":[{"experience":"Research Intern, Texas A&M (May July 2024)"}],"publications-projects":[{"publications_title":"","publications":"Analysis of the Banach Tarski Paradox"}],"project_title":"ALIF - A Pretrained Urdu Generative Model","fyp_desc":"Alif is a language model for Urdu which understands cultural nuances and contexts without being computationally expensive. Large Multilingual Language Models are mostly trained for languages like English, French, German. For underrepresented languages like Urdu, these models often produce ill-nuanced responses. State-of-the-art LLMs like GPT perform well to an extent in Urdu, but too computationally. Environmentally and financially, they are expensive to use. For local governments using these models could incur a huge training, and end point usage cost. Organizations like OpenAI cannot be trusted with sensitive data of banks and governments which is why using API is not a viable option. Therefore, we are working to build a Small Language Model which is significantly smaller in size than the large multilingual models but gives similar performance for Urdu language.","project_pictures":null,"project-video":""},"yoast_head":"\n