I am passionate about AI, NLP, and computer vision, aiming to apply my skills in deep learning and full-stack development to create impactful, real-world technological solutions.<\/p>\n
ahad2ali3@gmail.com
\nhttps:\/\/www.linkedin.com\/in\/ahad-ali-01085a22a\/<\/p>\n
+92 334 343 3587<\/p>\n
Dhanani School of Science and Engineering
\nBS Computer Science<\/p>\n
2025
\nLead a workshop on electrical safety by Zindagi Trust, MERN Stack, POSTMAN (APIs), Python, SQL
\nN\/A
\nAIESEC in Karachi (2023-2024), Freshmen Council 2021, Multiverse Treasure 2022-2023, Lead a workshop on electrical safety by Zindagi Trust, Lead Organizer in HUCon 4 (2023)
\nComputer Vision Solution Architect, Dawlance (September 2024\u00a0 May 2025)
\nhttps:\/\/habib.edu.pk\/tezhib\/assets\/pdf\/full-journal_final_v.3.pdf (pg141)
\nIntenseEye: Real-Time Safety Monitoring System
\nPakistan’s industrial sector faces significant safety challenges, with 1.9 million workplace injuries reported in 2020-2021. To address this, our project develops an AI-driven real-time monitoring system for Dawlance’s sheet metal plant. Utilizing computer vision and deep learning, the system analyzes CCTV footage to detect unsafe behaviors such as missing protective gear, improper machinery use, and pathway obstructions. By providing real-time alerts, the system enhances worker safety, reduces accidents, and ensures compliance with safety protocols. Additionally, it generates analytics to help Dawlance improve safety measures proactively. Unlike manual inspections, this automated solution offers continuous, scalable monitoring adaptable to various industrial environments. Our system integrates advanced deep learning, computer vision, and embedded technologies, making workplace safety proactive rather than reactive. By minimizing injuries, financial burdens on workers, and operational disruptions, this project presents a transformative solution for industrial safety, with potential scalability across multiple sectors.<\/p>\n","protected":false},"excerpt":{"rendered":"
I am passionate about AI, NLP, and computer vision, aiming to apply my skills in deep learning and full-stack development to create impactful, real-world technological solutions. ahad2ali3@gmail.com https:\/\/www.linkedin.com\/in\/ahad-ali-01085a22a\/ +92 334 343 3587 Dhanani School of Science and Engineering BS Computer Science 2025 Lead a workshop on electrical safety by Zindagi Trust, MERN Stack, POSTMAN (APIs), […]<\/p>\n","protected":false},"author":9,"featured_media":6391,"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-6305","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":"I am passionate about AI, NLP, and computer vision, aiming to apply my skills in deep learning and full-stack development to create impactful, real-world technological solutions. ","video_profile_link":"","habib_email":"","email":"ahad2ali3@gmail.com","linkedin_link":"https:\/\/www.linkedin.com\/in\/ahad-ali-01085a22a\/","portfolio_Title":"","portfolio_link":"","personal_cell_1":"+92 334 343 3587","personal_cell_2":"","core_skills":[{"skill":"Lead a workshop on electrical safety by Zindagi Trust, MERN Stack, POSTMAN (APIs), Python, SQL"}],"academic_awards":[{"academic_record":"N\/A"}],"leadership-experiences":[{"leadership":"AIESEC in Karachi (2023-2024), Freshmen Council 2021, Multiverse Treasure 2022-2023, Lead a workshop on electrical safety by Zindagi Trust, Lead Organizer in HUCon 4 (2023)"}],"work-experience":[{"experience":"Computer Vision Solution Architect, Dawlance (September 2024 May 2025)"}],"publications-projects":[{"publications_title":"","publications":"https:\/\/habib.edu.pk\/tezhib\/assets\/pdf\/full-journal_final_v.3.pdf (pg141)"}],"project_title":"IntenseEye: Real-Time Safety Monitoring System","fyp_desc":"Pakistan's industrial sector faces significant safety challenges, with 1.9 million workplace injuries reported in 2020-2021. To address this, our project develops an AI-driven real-time monitoring system for Dawlance's sheet metal plant. Utilizing computer vision and deep learning, the system analyzes CCTV footage to detect unsafe behaviors such as missing protective gear, improper machinery use, and pathway obstructions. By providing real-time alerts, the system enhances worker safety, reduces accidents, and ensures compliance with safety protocols. Additionally, it generates analytics to help Dawlance improve safety measures proactively. Unlike manual inspections, this automated solution offers continuous, scalable monitoring adaptable to various industrial environments. Our system integrates advanced deep learning, computer vision, and embedded technologies, making workplace safety proactive rather than reactive. By minimizing injuries, financial burdens on workers, and operational disruptions, this project presents a transformative solution for industrial safety, with potential scalability across multiple sectors.","project_pictures":null,"project-video":""},"yoast_head":"\n