“I am passionate about creating secure, reliable, and ethical AI-driven applications, with a strong focus on cybersecurity, software engineering, and data analysis. I am particularly interested in the governance of AI systems, ensuring that emerging technologies are designed responsibly and deliver real-world impact across industries.”<\/p>\n
duaesameen@gmail.com
\nlinkedin.com\/in\/dua-e-sameen\/<\/p>\n
+92 300 827 4260<\/p>\n
Dhanani School of Science and Engineering
\nBS Computer Science<\/p>\n
2025
\nDeep learning (CNNs, RNNs, Transformers), C, C++, C#, SQL, R, Python, MATLAB, JavaScript, React, React, Flutter, REST APIs, and database management (PostgreSQL, MySQL, MongoDB)<\/p>\n
Chavez: Autism Screening & Progress Tracking Tool
\nChavez is an AI-powered, bilingual (Urdu\/English) developmental screening and tracking platform aimed at improving early Autism Spectrum Disorder (ASD) detection in low-resource settings like Pakistan. With fewer than 350 child psychiatrists serving over 247 million people, Chavez offers accessible, culturally sensitive tools for early intervention. Designed for ages 2-8, it integrates caregiver-administered questionnaires (M-CHAT-R\/F), gamified behavioral assessments, speech analysis modules, and personalized reporting. Machine learning models such as Random Forest classifiers and Convolutional Neural Networks (CNNs) enhance the platform’s screening sensitivity, trained on public datasets and fine-tuned with local data from 93 children. Pilot results demonstrated Chavez reliably flags developmental concerns without clinical labels, providing structured insights instead. As a low-cost, flexible solution for homes or clinics, it reduces barriers to early ASD detection and empowers caregivers with actionable guidance.<\/p>\n","protected":false},"excerpt":{"rendered":"
“I am passionate about creating secure, reliable, and ethical AI-driven applications, with a strong focus on cybersecurity, software engineering, and data analysis. I am particularly interested in the governance of AI systems, ensuring that emerging technologies are designed responsibly and deliver real-world impact across industries.” duaesameen@gmail.com linkedin.com\/in\/dua-e-sameen\/ +92 300 827 4260 Dhanani School of Science […]<\/p>\n","protected":false},"author":9,"featured_media":6423,"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-6243","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 creating secure, reliable, and ethical AI-driven applications, with a strong focus on cybersecurity, software engineering, and data analysis. I am particularly interested in the governance of AI systems, ensuring that emerging technologies are designed responsibly and deliver real-world impact across industries.\"","video_profile_link":"","habib_email":"","email":"duaesameen@gmail.com","linkedin_link":"https:\/\/linkedin.com\/in\/dua-e-sameen\/","portfolio_Title":"","portfolio_link":"","personal_cell_1":"+92 300 827 4260","personal_cell_2":"","core_skills":[{"skill":"Deep learning (CNNs, RNNs, Transformers), C, C++, C#, SQL, R, Python, MATLAB, JavaScript, React, React, Flutter, REST APIs, and database management (PostgreSQL, MySQL, MongoDB)"}],"academic_awards":null,"leadership-experiences":null,"work-experience":null,"publications-projects":null,"project_title":"Chavez: Autism Screening & Progress Tracking Tool","fyp_desc":"Chavez is an AI-powered, bilingual (Urdu\/English) developmental screening and tracking platform aimed at improving early Autism Spectrum Disorder (ASD) detection in low-resource settings like Pakistan. With fewer than 350 child psychiatrists serving over 247 million people, Chavez offers accessible, culturally sensitive tools for early intervention. Designed for ages 2-8, it integrates caregiver-administered questionnaires (M-CHAT-R\/F), gamified behavioral assessments, speech analysis modules, and personalized reporting. Machine learning models such as Random Forest classifiers and Convolutional Neural Networks (CNNs) enhance the platform's screening sensitivity, trained on public datasets and fine-tuned with local data from 93 children. Pilot results demonstrated Chavez reliably flags developmental concerns without clinical labels, providing structured insights instead. As a low-cost, flexible solution for homes or clinics, it reduces barriers to early ASD detection and empowers caregivers with actionable guidance.","project_pictures":null,"project-video":""},"yoast_head":"\n