Summary
Dr. Hamza Wazir Khan is an experienced professional with impact factor research publications. Skilled in organizing and leading diverse training sessions and presenting at international conferences. Successfully conducted executive programs trainings and contributed to industrial projects in Enterprise Resource Planning, Augmented Reality and Business Analytics, applying theoretical knowledge to real-world scenarios for project success
Honours and Awards
Outstanding Teacher Award
In recognition of innovative Teaching & many Contributions made in students learning during the Award Year 2024-25
01-Oct-2025
Patron of the Year
In recognition of devotion, commitment and contributions for the Namal Sports and Adventure Club (NSAC)
13-Aug-2025
Courses
- Financial Accounting
- Applications of Information, Communication and Technologies
- Data Mining and Machine Learning
- Data Analysis with R
- Introduction to Data Analytics
- Data Driven Marketing
- Digital Marketing
Livestock Breed Identification using image analysis Technique
This project aims to revolutionize the livestock sector in Pakistan by utilizing the Machine Learning and AI algorithms. In the Agricultural sector in Pakistan, Livestock comprises a major part. Unfortunately, at many levels, multiple animals are considered un-identified because their breed is not recognized properly. For a long time, the animal breeds are recognized manually just by using previous knowledge. DNA imprinting methods that include studying the types of animals by studying their Genome sequence is another popular strategy but is expensive and time-consuming. Therefore, a cost-effective and easy-to-use method is required for proper breed recognition. In this project, we are proposing the recognition of the breed of livestock by developing a deep-learning model using the image data. We train our model by providing it with different biometric indicators of different animals. So, our model will be analyzing and identifying the breed of the animal by scanning different features of the animal like coat color, coat pattern, horns, size and length of animal body, etc.
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PDF Chat Bot: Document Based Conversations
This research explores the potential of pre-trained open-source Large Language Models (LLMs) for using secure and cost-effective in-house chatbot solutions within organizations. Through the utilization of the data-privacy centered PrivateGPT architecture and the capabilities of open source LLMs, we propose a solution that addresses data security and control problems that are frequently connected with commercially available chatbot solutions. The study investigates how businesses may use these open-source tools to create unique chatbots that can be deployed inside their local infrastructure and have access restricted to only authorized individuals. The research attempts to show the feasibility and affordability of this strategy by comparing the development, deployment, and maintenance expenses of this in-house solution to choices provided by third parties. This project promotes the broader use of LLMs in the workplace landscape by offering a safe and affordable substitute for current commercial solutions, hence meeting the growing demand for responsible AI adoption inside enterprises.
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Currency Detection System for Blind People
Blind or visually impaired individuals encounter challenges in daily life, including difficulty recognizing currency notes. Despite the growing popularity of electronic payments, cash remains widely used. This reliance on cash poses problems for those with visual impairments, as they struggle to identify currency values during financial transactions, making them vulnerable to exploitation. To assist blind individuals Currency Detection System can be employed. This project will include two parts, firstly training of YOLOv8 model on Pakistani currency notes and a system will be employed. The model will be given with an image of a currency note to detect the currency denomination as output. Furthermore, text-to-speech model will be used to convert text output into speech. This Project will be deployed on Google Cloud using NGROK (cross-platform application) enabling the Flask API to be accessible over the internet. Secondly, it includes research on YOLOv8 and analysis of results obtained by YOLOv8. Overall, this project aims to empower blind or visually impaired individuals by providing them with a reliable and accessible tool for recognizing currency notes. By leveraging the capabilities of YOLOv8 and text-to-speech technology, the project seeks to improve the independence and financial security of those with visual impairments.
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Aloe Solution: Aloe Vera Health Detection and Product Development in Pakistan.
Aloe Solution blends industrial innovation with consumer needs, leveraging aloe vera’s potential in Pakistan. We raised awareness about its benefits, promoting cultivation as a cash crop. The AI-powered YOLOv11 model ensures quality control, using computer vision for real-time aloe plant health detection. Our product Arogya Drink, "You Prefer, We Offer," a natural beverage meets the rising demand for healthy drinks. This project drives sustainable agriculture and agribusiness.
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LensLook: An AR Customized Solution - Bringing Beauty to Reality
This AR-based cosmetic lens try-on app offers users a personalized and interactive shopping experience, similar to leading beauty brands like L'Oréal and Sephora. Designed for mobile devices, the app allows users to virtually try on cosmetic contact lenses in real time, using augmented reality. By analyzing the user's skin tone through facial landmark detection and skin tone classification (based on 5–7 common Asian skin tones), the app recommends 3–4 lens shades that best complement their complexion. Eye region tracking ensures accurate overlay of virtual lenses on the user's eyes, creating a realistic and immersive try-on experience. The app features a friendly, easy-to-use interface where users can explore recommended lenses or manually browse the collection.
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Personality-Based Candidate Recommendation System Using MBTI for Recruitment
The Personality-Based Candidate Recommendation System leverages the Myers-Briggs Type Indicator (MBTI) to modernize recruitment by aligning candidates' personalities with job roles. Traditional hiring often overlooks personality-job fit, leading to mismatches and high turnover. This system introduces a dual-interface approach: a candidate-facing MBTI assessment platform and an HR dashboard for compatibility analysis. It replaces manual processes with a secure, scalable digital solution that reduces bias and enhances decision-making. Aimed at transforming recruitment in Pakistan, the system improves efficiency, workforce alignment, and engagement. Future enhancements may include cultural and team fit analytics for deeper organizational impact.
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Data Driven Approach to predict crop price and suitable location to sell the crops.
Agriculture plays a vital role in Pakistan’s economy, yet farmers often lack reliable data to make profitable crop-selling decisions. This project analyzes daily price and quantity data (2021–2025) for eight major crops across ten cities in Punjab, sourced from AMIS. We applied data analytics and developed a Random Forest model to predict future prices and suggest the best cities for selling crops. Despite data limitations, the project demonstrates how machine learning can empower farmers and improve decision-making in agricultural markets.
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Retail Sales Analytics and Forecasting Platform
This project develops a Power BI platform integrating Python and machine learning models (ARIMA, SARIMA, LSTM) to forecast sales, optimize inventory, and drive strategic decisions. It offers real-time dashboards, key KPIs (e.g., GMROI, sales velocity), and actionable insights, with scalability for diverse retail sectors. Stakeholder feedback has been incorporated, and the models are successfully deployed. Next steps include final integration, automation, and client delivery.
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Integration of Augmented Reality in Marketing Communication
This project introduces an AR-based marketing approach that replaces static ads with interactive, immersive experiences. Using tools like Unity and Vuforia, we developed a prototype that shows how AR boosts customer engagement and purchase intent. The goal is to launch an AR marketing agency that helps brands connect with audiences in innovative and impactful ways.
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Namal University