OUR TEAM

Lecturer, Department of Electrical Engineering, NUtech University (Feb 2024–Present)

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• Taught introductory programming courses, including Python and Java, for undergraduate students.
• Developed new course materials and assignments to better integrate industry-relevant technologies into the curriculum.

Senior Software Engineer, PoliSpace (2022–2024)

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• Led a team to develop AI-powered Mobile App for predictive analytics in satellites.
• Designed and implemented machine learning models to analyze satellite data, reducing housekeeping errors by 30%.

Instructor, MCS NUST (2019–21)

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• Teach undergraduate courses in OOP, and Data Structures.
• Serve as a faculty mentor for student clubs focused on AI and technology innovations.

Academia

• M.Sc. in Electrical Engineering, Polytechnic University of Milan, Italy (2024)
• B.Sc. in Telecommunications Engineering, NUST, Islamabad (2019)

Certifications

• Front End Development, FreeCodeCamp (2023)
• Certified Machine Learning, Stanford University (2022)
• MCS Certified Network Associate,  CCNA (2017)

I have taught a variety of undergraduate level courses in the Electrical Engineering Department. Below are the courses I have been involved in teaching:

• Introduction to Programming (CS101)
  An introductory course focusing on programming concepts using C++, covering topics such as variables, control structures, functions, and basic data structures.
• Machine Learning (EE4406)
  A course focused on the theory and application of machine learning algorithms, including supervised and unsupervised learning, neural networks, and deep learning.
• Applications of ICT (CS405)
  An advanced course that explores the practical applications of Information and Communication Technologies (ICT) and software tools in various domains.

My research focuses on the intersection of machine learning, deep learning, and computer vision. I am currently working on several projects that apply AI techniques to hardware, such as developing algorithms for accelerated object detection and classification.

Ongoing Research Projects

• AI accelerator using FPGA’s
• Predictive analytics for electrical grids using machine learning

• ML-powered Approach for Space Exploration (2023): Presented a complete app built using React and LeanSpace backend APIs at Space Tech Expo Europe (2023), awarded top position at the Space Hackathon 2023 for optimizing satellite selection through ML techniques, ensuring superior image quality and signal strength.
• Realtime Employee Location Tracking (2018): Developed a cross-platform app for real-time tracking of employee locations which was essential to dispatch orders to users.
• Smart Infant Monitoring System (2019): Created a monitoring system using Raspberry Pi and AI for audio localization, utilizing Python for both audio processing and UI.