Hi, I'm Khizar Ali
AI Student & Engineer passionate about building smart systems that solve real-world problems
About Me
AI undergraduate specializing in Computer Vision and Deep Learning. Experienced in building end-to-end ML systems including model training, optimization, deployment, and web/GUI integration. Strong foundation in neural networks, data processing, and scalable AI development.
Education: B.S. Artificial Intelligence — FAST-NUCES, Peshawar (Aug 2022 – Jun 2026), GPA: 3.5/4.0.
Technical Expertise
Work Experience
My journey in AI and technology, building innovative solutions and contributing to cutting-edge research
- Built a computer vision module for a multimodal psychology bot
- Integrated OpenCV and Google ML Kit in Flutter for real-time processing
- Contributed to system-level AI architecture and model optimization
- Assisted in AI course delivery, labs, and model debugging
- Prepared and graded assignments and supported student projects
- Developed AI models for Plant Disease Detection and Digit Recognition using CNNs (VGG19, MNIST)
- Preprocessed image data and evaluated models using standard metrics
- Deployed models using Python (TensorFlow, Keras, OpenCV)
- Collaborated via GitHub and delivered complete documentation and reports
- Met all deadlines with strong performance and technical accuracy
Education
Key Subjects
- Programming (Python, C++), Data Structures, Algorithms
- Artificial Intelligence, Machine Learning, Neural Networks, Reinforcement Learning
- Database Systems, Software Engineering
- Linear Algebra, Calculus, Probability & Statistics
- Big Data Analytics, Knowledge Representation
Core Technical Skills
- Python, C++, SQL, TensorFlow, Keras, OpenCV, DeepFace
- ML model development, training, and evaluation
- Real-time CV applications and agent-based AI systems
- Data preprocessing, analysis, and visualization
Featured Projects
Innovative AI solutions and applications that demonstrate my expertise in machine learning and computer vision
AI-based system for automated fetal biometry estimation from ultrasound images. U-Net segmentation to detect fetal structures (head, abdomen, femur) and measurement extraction for HC, AC, and FL. Integrated Grad-CAM for interpretability and an end-to-end pipeline for image/video analysis.
Developed a deep learning model using VGG19 to classify images of plant leaves as healthy or diseased. The system includes a Tkinter-based GUI for easy user interaction.
Built a Convolutional Neural Network to recognize hand-written digits using the MNIST dataset. The model is capable of real-time digit prediction through webcam feed.
Created an RDF ontology in Turtle format to represent the Solar System, integrating data about planets, moons, and orbits. Designed for linked data applications with interactive graphs.
A web-based system for managing school operations—student and teacher profiles, class scheduling, attendance tracking, and grade management. Features secure login for different user roles.
A real-time facial emotion recognition system that detects human emotions (such as happy, sad, angry, neutral, surprise, disgust, fear) from webcam input. Utilizes a CNN trained on standard datasets.
Honors & Awards
Recognition for academic excellence and outstanding performance
Awarded the prestigious Brown's Medal for securing the highest GPA in the department during Spring 2023 and Fall 2023 semesters. This medal recognizes academic excellence, consistency, and exceptional performance across all registered courses, distinguishing the recipient as a top scholar among peers.
Recognized on the Dean's List of Honor for two semesters (Fall 2022 and Fall 2023) for achieving top academic standing. This distinction is awarded to high-performing students who consistently demonstrate academic excellence and rank among the top percentile of their class.
Let's Build Something Amazing Together
I'm always interested in discussing AI projects, research opportunities, or potential collaborations. Let's connect and explore how we can create innovative solutions together!
p229269@pwr.nu.edu.pk
Phone
+92-317-7941300
Location
Peshawar, Pakistan