zk08128@st.habib.edu.pk
I am pursuing roles at the intersection of product and technology, ideally at startups where I can grow from a technical contributor to someone shaping what gets built and why.<\/p>\n
zk08128@st.habib.edu.pk
zaidbinkhalid29@gmail.com
www.linkedin.com\/in\/zbk2001
Portfolio
https:\/\/zaidbkhalid.github.io\/
+923177129791<\/p>\n
Dhanani School of Science and Engineering
BS Electrical Engineering<\/p>\n
2026
Agentic AI & Automation|
\nArtificial Intelligence|
\nData Science|
\nMachine Learning & Deep Learning|
\nPython|
\nRobotics & Embedded Systems|
Adaptability; Collaborates Openly; Drive for Results; Effective Presentation Skills; Encourages Innovation; Planning; Problem Solving; Takes Initiative
Product Manager; AI Engineer; Software Engineer, Data Analyst, Data Engineer;
N\/A
Event Lead,Ieee (Institute of Electrical and Electronics Engineers)|Treasurer,Math Club|
Teaching Assistant For Calculus I,
\n Habib University
\n (September \u2013 December 2024)
\n|<\/p>\n
Summer Tehqeeq Student Researcher,
\n Habib University
\n (June \u2013 August 2024)
\n|<\/p>\n
Peer Tutor For Calculus Ii,
\n Habib University
\n (February \u2013 April 2024)
\n|<\/p>\n
Teaching Assistant For Calculus I,
\n Habib University
\n (August \u2013 December 2023)
\n|
Conference Presentation \u2013 Zaid Bin Khalid, Nahyan Javed, Farhan Khan. “BiLSTM-Based Sequential Acoustic Crash Detection for Urban Road Safety”. IEEE Karachi Humanitarian Technology Conference (KHI-HTC), 2026. (Conference Paper Under Review)|
\nPublication \u2013 “Acoustic Car Crash Detection Using Audio Classification”. DURS, Habib University, 2026. (Abstract Under Review)|
Real-Time Car Crash Detection Using Acoustic Signatures
Road traffic accidents claim 1.19 million lives annually, with delayed emergency response being a critical contributing factor. This project develops a passive acoustic vehicle crash detection and localization system intended for deployment on embedded hardware in low-resource urban environments. In the first phase, three audio classification approaches were evaluated \u2014 a Bidirectional LSTM, an SVM with Bag of Aural Words, and a Gaussian Naive Bayes classifier \u2014 with the BiLSTM achieving 97.14% accuracy and 98.5% crash recall.<\/p>\n
The ongoing second phase focuses on two objectives: implementing the detection pipeline on a Xilinx Zynq-7000 FPGA for real-time embedded inference and developing an acoustic localization algorithm to estimate crash coordinates for first responders, completing a fully deployable crash notification system.<\/p>\n
<\/p>\n","protected":false},"excerpt":{"rendered":"
zk08128@st.habib.edu.pkI am pursuing roles at the intersection of product and technology, ideally at startups where I can grow from a technical contributor to someone shaping what gets built and why. zk08128@st.habib.edu.pkzaidbinkhalid29@gmail.comwww.linkedin.com\/in\/zbk2001Portfoliohttps:\/\/zaidbkhalid.github.io\/+923177129791 Dhanani School of Science and EngineeringBS Electrical Engineering 2026Agentic AI & Automation| Artificial Intelligence| Data Science| Machine Learning & Deep Learning| Python| Robotics & […]<\/p>\n","protected":false},"author":9,"featured_media":7185,"menu_order":0,"comment_status":"","ping_status":"","template":"single-graduate-01.php","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"program":[30],"school":[42],"class":[44],"minor":[],"competencies":[60,56,61,53,55,58,54,59],"class_list":["post-9098","graduate","type-graduate","status-publish","format-standard","has-post-thumbnail","hentry","program-bsee","school-dhanani-school-of-science-and-engineering","class-class-of-2026","competencies-adaptability","competencies-collaborates-openly","competencies-drive-for-results","competencies-effective-presentation-skills","competencies-encourages-innovation","competencies-planning","competencies-problem-solving","competencies-takes-initiative"],"acf":{"scholarship":"","aspiration_statement":"I am pursuing roles at the intersection of product and technology, ideally at startups where I can grow from a technical contributor to someone shaping what gets built and why.","video_profile_link":"","habib_email":"zk08128@st.habib.edu.pk","email":"zaidbinkhalid29@gmail.com","linkedin_link":"www.linkedin.com\/in\/zbk2001","portfolio_Title":"Portfolio","portfolio_link":"https:\/\/zaidbkhalid.github.io\/","personal_cell_1":"+923177129791","personal_cell_2":"","core_skills":[{"skill":"Agentic AI & Automation"},{"skill":"Artificial Intelligence"},{"skill":"Data Science"},{"skill":"Machine Learning & Deep Learning"},{"skill":"Python"},{"skill":"Robotics & Embedded Systems"}],"academic_awards":[{"academic_record":"N\/A"}],"leadership-experiences":[{"leadership":"Event Lead, Ieee (Institute of Electrical and Electronics Engineers)"},{"leadership":"Treasurer, Math Club"}],"work-experience":[{"experience":"Teaching Assistant For Calculus I, Habib University (September \u2013 December 2024)"},{"experience":"Summer Tehqeeq Student Researcher, Habib University (June \u2013 August 2024)"},{"experience":"Peer Tutor For Calculus Ii, Habib University (February \u2013 April 2024)"},{"experience":"Teaching Assistant For Calculus I, Habib University (August \u2013 December 2023)"}],"publications-projects":[{"publications_title":"","publications":"Conference Presentation \u2013 Zaid Bin Khalid, Nahyan Javed, Farhan Khan. \"BiLSTM-Based Sequential Acoustic Crash Detection for Urban Road Safety\". IEEE Karachi Humanitarian Technology Conference (KHI-HTC), 2026. (Conference Paper Under Review)"},{"publications_title":"","publications":"Publication \u2013 \"Acoustic Car Crash Detection Using Audio Classification\". DURS, Habib University, 2026. (Abstract Under Review)"}],"project_title":"Real-Time Car Crash Detection Using Acoustic Signatures","fyp_desc":"Road traffic accidents claim 1.19 million lives annually, with delayed emergency response being a critical contributing factor. This project develops a passive acoustic vehicle crash detection and localization system intended for deployment on embedded hardware in low-resource urban environments. In the first phase, three audio classification approaches were evaluated \u2014 a Bidirectional LSTM, an SVM with Bag of Aural Words, and a Gaussian Naive Bayes classifier \u2014 with the BiLSTM achieving 97.14% accuracy and 98.5% crash recall.\n\nThe ongoing second phase focuses on two objectives: implementing the detection pipeline on a Xilinx Zynq-7000 FPGA for real-time embedded inference and developing an acoustic localization algorithm to estimate crash coordinates for first responders, completing a fully deployable crash notification system.","project_pictures":null,"project-video":""},"yoast_head":"\n