as08155@st.habib.edu.pk
\nInterested in Machine Learning, AI, and Computer Vision. I aim to begin my career as an Associate ML Engineer\/MLOps and plan to pursue a Master\u2019s specializing in Computer Vision.<\/p>\n
as08155@st.habib.edu.pk
\nahsan.sidd2003@gmail.com
\nhttps:\/\/www.linkedin.com\/in\/ahsansidd\/
\nPortfolio<\/p>\n
+923178417095<\/p>\n
Dhanani School of Science and Engineering
\nBS Computer Science<\/p>\n
2026
\nDeep Learning|
\nLLMs|
\nMachine Learning|
\nPython|
\nVision Transformers|
\nAdaptability; Agility; Strategic Thinking
\nMachine Learning\/AI Engineer; Software Engineer; Data Scientist;
\nN\/A
\nVolleyball Lead,Sports & Recreational Club|Security Team Lead and Volunteer,Multiverse Club|Volleyball Team Captain,Sports & Recreational Club|Table Tennis Lead,Sports & Recreational Club|
\nHabib University,
\nResearcher – Summer Tehqiq Research Program
\n(June \u2013 August 2025)
\n|
\nResearch Paper \u2013 Research Paper on Automating ROP Diagnosis and Severity with Deep Learning published in IEEE(HONET) in December 2025|
\nResearch Paper \u2013 Participation in SemEval-2026 Task 5: Rating Plausibility of Word Senses in Ambiguous Sentences through Narrative Understanding – Manuscript ready and sent for Acceptance|
\nResearch Paper \u2013 Participation in CLEF 2026 Touche LAB – Currently in progress|
\nPredictive Fault Management in Power Distribution Networks
\nThis research addresses the energy security challenges of Karachi, a metropolis of 20 million, by transitioning utility operations from a reactive to a proactive model. Utilizing three years of K-Electric historical data, live sensor readings, and localized variables like weather and traffic, the project develops a context-aware predictive system.<\/p>\n
The primary aim is to accurately identify fault locations, classify failure types, and estimate “Time to Repair” (TTR). By integrating “Just-in-Time” maintenance and risk mapping, the system reduces operational costs, minimizing the 70 PKR cost per manual complaint, and enhances customer trust through transparent communication. Validated against actual Outage Management System (OMS) data, this model leverages unutilized logs to create a robust, localized solution for Karachi\u2019s unique socio-economic and climatic landscape.<\/p>\n","protected":false},"excerpt":{"rendered":"
as08155@st.habib.edu.pk Interested in Machine Learning, AI, and Computer Vision. I aim to begin my career as an Associate ML Engineer\/MLOps and plan to pursue a Master\u2019s specializing in Computer Vision. as08155@st.habib.edu.pk ahsan.sidd2003@gmail.com https:\/\/www.linkedin.com\/in\/ahsansidd\/ Portfolio +923178417095 Dhanani School of Science and Engineering BS Computer Science 2026 Deep Learning| LLMs| Machine Learning| Python| Vision Transformers| Adaptability; Agility; […]<\/p>\n","protected":false},"author":9,"featured_media":8480,"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":[44],"minor":[],"competencies":[60,62,63],"class_list":["post-8073","graduate","type-graduate","status-publish","format-standard","has-post-thumbnail","hentry","program-bscs","school-dhanani-school-of-science-and-engineering","class-class-of-2026","competencies-adaptability","competencies-agility","competencies-strategic-thinking"],"acf":{"scholarship":"","aspiration_statement":"Interested in Machine Learning, AI, and Computer Vision. I aim to begin my career as an Associate ML Engineer\/MLOps and plan to pursue a Master\u2019s specializing in Computer Vision.","video_profile_link":"","habib_email":"as08155@st.habib.edu.pk","email":"ahsan.sidd2003@gmail.com","linkedin_link":"https:\/\/www.linkedin.com\/in\/ahsansidd\/","portfolio_Title":"Portfolio","portfolio_link":"","personal_cell_1":"+923178417095","personal_cell_2":"","core_skills":[{"skill":"Deep Learning"},{"skill":"LLMs"},{"skill":"Machine Learning"},{"skill":"Python"},{"skill":"Vision Transformers"}],"academic_awards":[{"academic_record":"N\/A"}],"leadership-experiences":[{"leadership":"Volleyball Lead, Sports & Recreational Club"},{"leadership":"Security Team Lead and Volunteer, Multiverse Club"},{"leadership":"Volleyball Team Captain, Sports & Recreational Club"},{"leadership":"Table Tennis Lead, Sports & Recreational Club"}],"work-experience":[{"experience":"Habib University, Researcher - Summer Tehqiq Research Program (June \u2013 August 2025)"}],"publications-projects":[{"publications_title":"","publications":"Research Paper \u2013 Research Paper on Automating ROP Diagnosis and Severity with Deep Learning published in IEEE(HONET) in December 2025"},{"publications_title":"","publications":"Research Paper \u2013 Participation in SemEval-2026 Task 5: Rating Plausibility of Word Senses in Ambiguous Sentences through Narrative Understanding - Manuscript ready and sent for Acceptance"},{"publications_title":"","publications":"Research Paper \u2013 Participation in CLEF 2026 Touche LAB - Currently in progress"}],"project_title":"Predictive Fault Management in Power Distribution Networks","fyp_desc":"This research addresses the energy security challenges of Karachi, a metropolis of 20 million, by transitioning utility operations from a reactive to a proactive model. Utilizing three years of K-Electric historical data, live sensor readings, and localized variables like weather and traffic, the project develops a context-aware predictive system.\r\n\r\nThe primary aim is to accurately identify fault locations, classify failure types, and estimate \"Time to Repair\" (TTR). By integrating \"Just-in-Time\" maintenance and risk mapping, the system reduces operational costs, minimizing the 70 PKR cost per manual complaint, and enhances customer trust through transparent communication. Validated against actual Outage Management System (OMS) data, this model leverages unutilized logs to create a robust, localized solution for Karachi\u2019s unique socio-economic and climatic landscape.","project_pictures":[{"project_pic":8752}],"project-video":""},"yoast_head":"\n