Muhammad Tayyab Iftikhar
NUST
· 2026
Email
tayyabiftikhar321@gmail.com
Phone
923067279504
GitHub
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Academic
Program
BSCS
CGPA
3.29
Year
2026
Education
SEECS
Address
P.O SAME CHAK NO.274/RB KALA CHEEMA TEHSIL SADARFAISALABAD , Faisalabad , Pakistan
DOB
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Career
Current role
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Target role
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Skills
Large Language Models, generative AI, fine-tuning LLMs, RAG pipelines, machine learning, deep learning, full-stack application design, text-to-speech synthesis, image caption generation, Ollama, Hugging Face, exploratory data analysis, UAV imagery, phenological analysis, Data Engineering, Feature Engineering
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Muhammad Tayyab Iftikhar Cell: 923067279504 | Email: tayyabiftikhar321@gmail.com LinkedIn: https://www.linkedin.com/in/muhammad-tayyab-iftikhar-99740a2a0/ Address: P.O SAME CHAK NO.274/RB KALA CHEEMA TEHSIL SADARFAISALABAD , Faisalabad , Pakistan PROFESSIONAL PROFILE Computer Science undergraduate at NUST with a focus on Large Language Models and generative AI. Experienced in fine-tuning LLMs, building RAG pipelines, and developing scalable AI applications. Skilled in machine learning, deep learning, and full-stack application design, translating technical requirements into production-ready solutions. Seeking an AI/ML role to create LLM-driven and generative AI systems with real-world impact. EDUCATION BSCS SEECS , Islamabad , 3.29 (4) INTERNSHIP EXPERIENCE ESCASA 09-Jun-2026 - 15-Aug-2026 Trained deep learning models for text-to-speech synthesis and image caption generation. Developed and evaluated model pipelines for accurate and robust outputs. HPC NUST 04-Aug-2025 - 25-Jan-2026 Developed RAG pipelines and fine-tuned large language models, exploring Ollama and Hugging Face ecosystems, and currently working on the NUST AI help bot. Built an interactive system allowing students to query and explore models in real time. Machvis NUST 04-Mar-2025 - 25-Jan-2026 Conducted exploratory data analysis on Lahore population and air pollution datasets, generating insights and visualizations. Later, worked on UAV imagery and machine learning to analyze wheat genotypes, preprocessing data and extracting structural, spectral, and texture features for phenological analysis. FINAL YEAR PROJECT Analyzing UAV based multispectral data for genotypic aware crop performance Assessment Modern agriculture increasingly uses UAV-based multispectral imagery to monitor crop performance. However, current methods often treat entire fields as homogeneous crop populations, overlooking the underlying genotypic or varietal diversity present in experimental or breeding fields. Each plot in such fields typically hosts a specific genotype or variety, often replicated across spatial and temporal dimensions. Without accounting for these varietal differences, analysis of phenological stages, biomass estimation, fractional cover, and other morphological / physiological features lack granularity and cannot inform genotypic performance comparison or variety selection. This project aims to bridge the gap identified in the above problem statement by performing a detailed, genotypic-aware analysis of UAV-collected multispectral crop data across multiple seasons and crops (Sunflower and Wheat) to identify and quantify performance variability, cluster high-performing varieties, and provide trends & insights for plant breeders and agronomists through a well-designed dashboard / interface. TECHNICAL EXPERTISE Data Engineering & Feature Engineering Processed, cleaned, and transformed datasets for machine learning and deep learning models. Worked with structured,
AI enrichment
Muhammad Tayyab Iftikhar is a Computer Science undergraduate at NUST with a 3.29 CGPA, specializing in Large Language Models, generative AI, and RAG pipelines. He has internship experience in deep learning model training and data analysis, with a final year project focused on UAV-based multispectral crop assessment.
Skills (AI)
["Large Language Models", "Generative AI", "RAG Pipelines", "Fine-tuning", "Machine Learning", "Deep Learning", "Data Engineering", "Feature Engineering", "Python", "Hugging Face", "Ollama", "UAV Imagery Analysis", "Data Visualization"]
Status: ai_done