Maha Baig
NUST
· 2022
Email
mahabaig7@gmail.com
Phone
923328639350
GitHub
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Academic
Program
BSCS
CGPA
3.33
Year
2022
Education
SEECS
Address
Sialkot, Pakistan
DOB
—
Career
Current role
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Target role
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Skills
Artificial Intelligence, Vision-Language Models, Explainable AI, Agentic AI Systems, Retrieval-Augmented Generation, Machine Learning, Software Engineering, Product Design, Post-Quantum Cryptography, IoT, React, Figma, Adobe XD, UI/UX, Knowledge Graphs, Medical AI
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Maha Baig Cell: 923328639350 | Email: mahabaig7@gmail.com LinkedIn: https://www.linkedin.com/in/maha-baig-95649b148/ Address: NISHAT PARK, OPPOSITE TO CBCS, DR. ANJUM SOHAILKHAN, HOUSE NO. 1, PARIS ROAD, SIALKOT. , Sialkot , Pakistan PROFESSIONAL PROFILE Computer Science undergraduate at NUST with strong research and applied experience in Artificial Intelligence, Vision-Language Models, and explainable AI. Experienced in building agentic AI systems, Retrieval-Augmented Generation pipelines, and ML-driven healthcare and education applications. Adept at translating complex AI outputs into interpretable, user-centered systems through interdisciplinary work spanning machine learning, software engineering, and product design. Seeking research or industry roles where rigorous AI development, interpretability, and real-world impact intersect. EDUCATION Bachelor of Science in Computer Science School Of Electrical Engineering And Computer Science , Islamabad , 3.33/4.0 (2022) INTERNSHIP EXPERIENCE Deep Learning Lab, NUST 08-Mar-2025 - 09-May-2025 Designed a secure smart-attendance system integrating post-quantum cryptographic schemes for IoT-enabled classrooms. Analyzed performance trade-offs and security resilience against classical and quantum adversaries. Demonstrated applicability to healthcare and education environments requiring tamper-proof monitoring. SMART Labs, NUST 03-Sep-2025 - 01-Nov-2025 Conducted research on interpretability and grounding in Retrieval-Augmented Generation systems. Co-authored a survey on explainability, attribution, and verification in generative AI. Contributed across the full research pipeline, including literature review, experimentation, analysis, and manuscript preparation. Machine Vision & Intelligent Systems Lab, NUST 14-Nov-2025 - 22-Jan-2026 Developed an agentic medical AI pipeline using Vision-Language Models to generate interpretable, evidence-grounded diagnostic reports from medical images. Designed a clinical Knowledge Graph to encode hierarchical and spatial findings for traceable reasoning. Introduced an Evidence Gate to verify diagnostic claims against image-derived evidence, reducing hallucinations. Evaluated the system on public X-ray and CT datasets, improving factual consistency and interpretability. Carbonteq, Lahore 22-Jun-2025 - 08-Aug-2026 Worked in a cross-functional software engineering team on production-grade applications. Designed high-fidelity UI/UX assets using Figma and Adobe XD. Contributed reusable frontend components in React while maintaining design system consistency. FINAL YEAR PROJECT XMedAgent: An Agentic AI Framework for Knowledge-Guided Radiology Report Generation Developed an agentic radiology reporting system using Vision Agents, Retrieval Agents, and multi-LLM orchestration. Integrated a clinical Knowledge Graph and an Evidence Gate to ensure image-grounded, verifiable diagnostic statements. Focused on interpretability, factual consistency, and safety-critical deployment in medical AI settings. TECHNICAL EXPERTISE
AI enrichment
Maha Baig is a Computer Science undergraduate with a focus on AI, specifically Vision-Language Models and Retrieval-Augmented Generation. She has practical experience in building agentic AI systems and healthcare applications through internships at NUST labs and Carbonteq.
Skills (AI)
["Artificial Intelligence", "Machine Learning", "Vision-Language Models", "Retrieval-Augmented Generation", "Explainable AI", "React", "UI/UX Design", "Python", "Deep Learning"]
Status: ai_done