Profile

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Prof. Dr. Ahmar Rashid

Prof. Dr. Ahmar Rashid is a senior academic and researcher with over 20 years of experience in Computer Science and Engineering, specializing in Artificial Intelligence, Computer Vision, Generative AI, and Autonomous Systems. He holds a PhD from Jeju National University (South Korea), a master’s degree from NUST College of E&ME, and a BS in Computer Systems Engineering from GIK Institute. He has served at GIK Institute for over 13 years, including four years as Dean of the Faculty of Computer Science and Engineering (FCSE).

His research focuses on AI-driven optimization, image reconstruction, evolutionary and meta-heuristic algorithms, machine learning, and UAV navigation in GPS-denied and adversarial environments. He also has deep expertise in Large Language Models and Generative AI, regularly delivering advanced lectures on GANs, Diffusion Models, Transformers, GPTs, and Explainable AI.

As an educator, Dr. Rashid has taught a wide range of undergraduate and graduate courses and supervised numerous MS and PhD students in computer vision, aerial robotics, and machine learning. As Dean, he spearheaded the launch of four accredited BS programs — AI, Data Science, Cyber Security, and Software Engineering — and contributed to national curriculum reforms with the HEC and PEC.

He has delivered invited talks at major international conferences, including organizing ICET 2022, the highest-profile IEEE event hosted by GIK Institute. His work in building international collaborations spans partners in the USA, South Korea, and Turkey. Dr. Rashid is currently serving as an AI Master Trainer under a national initiative by Meta, atomcamp, MoITT, HEC, and NCEAC.

Incharge Aerial Robotics & Vision Lab

Dr. Ahmar Rashid leads the Aerial Robotics and Vision (ARV) Lab — a dynamic research group at FCSE — where he develops AI-based vision, aerial imaging, and target-tracking systems. Several of these efforts have been validated in collaboration with ZATNav.

The ARVLab is a multidisciplinary research facility dedicated to advancing drone technology and intelligent vision systems. Equipped with state-of-the-art platforms such as Crazyflie, AR Drone 2.0, DJI Mavic Air Mini, DJI Mavic Zoom 2, and DJI Matrice, the lab provides a robust environment for cutting-edge research and experimentation.

The ARV team brings together expertise from Computer Science, Computer Engineering, Electronics, Mechanical Engineering, and Engineering Sciences, fostering innovation across diverse domains. The lab supports Bachelor’s, Master’s, and PhD students in conducting research on aerial robotics, autonomous systems, computer vision, and related fields.

With modern tools and collaborative opportunities, the Aerial Robotics & Vision Lab serves as a hub for pioneering solutions in robotics, AI, and sustainable technologies.

Founding Member: Dr. Asif Khan (2016-2018)

Selected List Of Publications

Journal Publications

2025

• S. Akhtar, M. Hanif, A. Rashid, A. Khalil, E. A. Khan, and H. M. Saraoglu 2025  YOLOv8–YOLOv11 Ensemble with Box Fusion for Enhanced Detection of Underrepresented Urine Sediment Particles, IEEE Access,  doi: 10.1109/ACCESS.2025.3634240, (in process).
• F. Khalid, U. Haider, M. Hanif, A. Rashid, and A. Khalil2025  Sparse Prototype-Based Framework for Deepfake Detection Using Class-Specific Dictionary Learning, IEEE Access, doi:10.1109/ACCESS.2025.3636276, (in process).

2024

• M. Arsalan, A. Rashid, K. Khan, A. Imran, F. Khan, M. A. Akbar, H. M. Cheema 2024 Real-time precision spraying application for tobacco plants, Smart Agricultural Technology 8 100497 [ISSN: 2772-3755] (Impact Factor 3).
• Haider, M. Hanif, A. Rashid, S. M. Qaisar, A. Subasi 2024 EEG-based schizophrenia classification using penalized sequential dictionary learning in the context of mobile healthcare Biomedical Signal Processing and Control 90, 105856 [ISSN 1746-8094] (Impact Factor 4.9).
• Haider, M. Hanif, A. Rashid, K. Aurangzeb, A. Khalil and M. Alhussein 2024 Discriminative Dictionary Learning Using Penalized Rank-1 Approximation for Breast Cancer Classification with Imbalanced Dataset IEEE Access, 12, 5837 – 5850 [ISSN 2169-3536] (Impact Factor 3.4).
• Akhtar, M. Hanif, A. Rashid, K. Aurangzeb, E. A. Khan, H. M. Saraoglu, K. Javed 2024 An Optimized Data and Model Centric Approach for Multi-Class Automated Urine Sediment Classification IEEE Access, Accepted for Publication/available online [ISSN 2169-3536] (Impact Factor 3.4).
• Y. Wang, X. Sun, G. Zheng, A. Rashid, S. Ullah, H., M. Waqas 2024 Enhancing Energy Efficiency with a Dynamic Trust Measurement Scheme in Power Distribution Network Computers, Materials & Continua, 78, 3909-3927 [ISSN 1546-2218] (Impact Factor 2.0).

2023

• Haider, M. Hanif, A. Rashid, S. F. Hussain 2023 Dictionary-enabled efficient training of ConvNets for image classification Image and Vision Computing, 135, 104718, [ISSN 0262-8856, Impact factor 4.2]

2021

• Z. Liu, M. Waqas, J. Yang, A. Rashid, A Multi-task CNN for Maritime Target Detection 2021 IEEE Signal Processing Letters 28 434-438, [Thomson Reuters JCR 2019, Impact factor 3.2].

2020 and Before

• Rashid, M.A. Zeb, S. Anwar, F. Joaquim, and Z. Halim 2020 Conceptualization of smartphone usage and feature preferences among various demographics Cluster Computing, 23, 1855–1873. [ISSN: 1386-7857, Springer] (Impact Factor 3.6).
• Rashid, M. Kamran, and Z. Halim 2019 A top down approach to enumerate α-maximal cliques in uncertain graphs Journal of Intelligent and Fuzzy Systems, 36, 3129 – 3141. [ISSN: 1064-1246, IOS] (Impact Factor 1.7).
• Halim, M. Atif, A. Rashid,and C. A. Edwin 2019 Profiling Players Using Real-World Datasets: Clustering the Data and Correlating the Results with the Big-Five Personality Traits IEEE Transactions on Affective Computing, 10, 568 – 584. [ISSN: 1949-3045] (Impact Factor 9.6).
• Khan, M. Imran, A, Rashid2018 Aerial Camera Network for Observing Moving Targets IEEE Sensors Journal, 18 6847-6856, [ISSN: 1558-1748] (Impact Factor 4.3).
• U. Ansari, M. Hussain, A. Rashid,  S. Mazhar, S. M. Ahmad 2018 Numerical Solution and Analysis of Three-Dimensional Transient Darcy Flow Transport in Porous Media123 289-305 [ISSN 0169-3913] (Impact Factor 2.7).
• U. Ansari, M. Hussain, A. Rashid, S. M. Ahmad, S. Mazhar, and K. J. Siddiqui 2018 Validating Numerical Solution of Transient Darcy Flow using Stabilized Mixed Finite Element Method Simulation: Transactions of the Society for Modeling and Simulation International,94 55- 65 [ISSN: 00375497] (Impact Factor 1.3).
• Halim, M. Waqas, A.R. Baig and A. Rashid2018 Efficient Clustering of Large Uncertain Graphs Using Neighborhood Information International Journal of Approximate Reasoning, 90 274-291 [ISSN: 0888-613X] (Impact Factor 3.2).
• U. Ansari, M. Hussain, S. M. Ahmed, A. Rashid, S. Mazhar 2017 Stabilized Mixed Finite Element Method for Transient Darcy Flow Transactions of the Canadian Society for Mechanical Engineering41 85–97 [ISSN 03158977] (Impact Factor 0.8).
• Rashid, S. Kim, D. Liu, K. Y. Kim 2016, A dynamic oppositional biogeography-based optimization approach for time varying electrical impedance tomography physiological measurement 37 820–842 [ISSN: 1361-6579] (Impact Factor 2.3).
• Rashid, B. S. Kim, A. K. Khambampati, S. Kim, K. Y. Kim 2011 An oppositional biogeography-based optimization technique to reconstruct organ boundaries in human thorax using electrical impedance tomography physiological measurement 32 767–796 [ISSN: 1361-6579] (Impact Factor 2.3).
• K. Khambampati, A. Rashid, J. S. Lee, B. S. Kim, L. Dong, S. Kim, K. Y. Kim 2011 Estimation of void boundaries in flow field using expectation maximization algorithm. Chemical Engineering Science 66 355-374. [SSN: 0009-2509] (Impact Factor 4.1).
• Rashid, A. K. Khambampati, B. S. Kim, S. Kim, M. J. Kang, K. Y. Kim 2010 An EKF based estimation scheme for sedimentation processes in process vessels using EIT-type measurement data. Flow Measurement and Instrumentation 21 521-530 [ISSN: 0955-5986]( Impact Factor 2.3).
• K. Khambampati, A. Rashid, U. Z. Ijaz, S. Kim, M. Soleimani, K. Y. Kim 2009 Unscented Kalman filter approach to track moving interfacial boundary in sedimentation process using three-dimensional electrical impedance tomography. Phil. Trans. R. Soc. A. 367 3095-3120 [ISSN 1364-503X].(Impact Factor 4.3]

Conference Series, Journal Publications

• A. Rashid, B. S. Kim, A. K. Khambampati, L. Dong, S. Kim, K. Y. Kim 2010 Dynamic boundary estimation of heart within a complete cardiac cycle using electrical impedance tomography. Journal of Physics: Conference series 224 012042.
• A. K. Khambampati, A. Rashid, B. S. Kim, L. Dong, S. Kim, K. Y. Kim 2010 EM algorithm applied for estimating non-stationary region boundaries using electrical impedance tomography. Journal of Physics: Conference series 224 012044.
• B. S. Kim, A. Rashid, A. K. Khambampati, L. Dong, S. Kim, K. Y. Kim 2010 Tracking resistivity changes using suboptimal fading extended Kalman filter in electrical impedance tomography. Journal of Physics: Conference series 224 012024.

Conference Proceedings

• Haider, M. Hanif, H. Kobayashi, L. Kumar Parajuli, D. Shimotoku, A. Rashid, Sonia Safeer 2023 Bioacoustics Signal Classification Using Hybrid Feature Space with Machine Learning, In Proceedings of 2023 15th International Conference on Computer and Automation Engineering (ICCAE), Sydney Australia.
• S. U. Ansari, M. Hussain, S. Mazhar, A. Rashid, S. M. Ahmad 2015 Parallel stabilized mixed Galerkin method for three-dimensional Darcy flow using OpenMP, National Software Engineering Conference (NSEC).
• S. U. Ansari, M. Hussain, A. Rashid, S. Mazhar, S. M. Ahmad 2015 Three-Dimensional Stabilized Mixed Galerkin Method for Darcy Flow,13th International Conference on Frontiers of Information Technology (FIT)
• S.U. Ansari, M. Hussain. S. Mazhar, A. Rashid and S.M. Ahmad 2015 Stabilized Mixed Galerkin Method for Transient Analysis of Darcy Flow, ICMSAO, Istambul, Turkey.
• A. Naushad, A. Rashid, S. Mazhar 2014 Analysing the Performance of EIT images using the point spread function, submitted to The Tenth International Conference on Emerging Technologies 2014 (ICET 2014), Islamabad. download
• A. Rashid, A. K. Khambampati, B. S. Kim, L. Dong, S. Kim, K. Y. Kim 2010 A differential evolution based approach to estimate the shape and size of complex shaped anomalies using EIT measurements, Springer CCIS 121 206-15.
• A. Rashid, A. K. Khambampati, B. S. Kim, S. Kim, K. Y. Kim. A State Evolution Model to Monitor Sedimentation Process Using Electrical Impedance Tomography. In Proceedings of the 3rd International Workshop on Process Tomography, Tokyo, Japan, April 17-19, 2009.
• A. K. Khambampati, A. Rashid, J. S. Lee, B. S. Kim, S. Kim, M. J. Kang, K. Y. Kim. Three-dimensional electrical resistance tomography applied to soil resistivity distribution for locating earth grounding system. In Proceedings of the 3rd International Workshop on Process Tomography, Tokyo, Japan, April 17-19, 2009.
• A. K. Khambampati, A. Rashid, J. S. Lee, S. Kim, K. Y. Kim. Three-dimensional boundary estimation in sedimentation process using electrical impedance tomography with the aid of unscented Kalman filter. In Proceedings of the 23rd International Technical Conference on Circuits/Systems, Computers and Communications, Kaikyo Messe Shimonoseki, Shimonoseki City, Japan, July 6-9, 2008.

Invited Talks and Worskshops

The International Conference on Applications of Space Science and Technology (ICAST) 2025: Keynote Speech titled “From Sky to Space: AI-Enabled Vision for Sustainable Monitoring“.

The 4th International Conference on Communication, Computing & Digital Systems (C-CODE) 2025: Keynote Speech titled “AI-Enabled UAVs: Autonomy, Navigation, and Mapping in Challenging Environments”.

AI Master Trainer Workshop 2025 Under HEC/Meta/MoIT AI-Ready  Faculty Development Program: Delivered full day workshop on “Prompt Engineering Techniques” and “Biases & Ethics in AI Systems”.

Pakistan Navy War College and Maritime Centre of Excellence 2025: Invited Talk titled “Artificial Intelligence in Modern Era”

Advanced AI Bootcamp on Deep Nueral Networks (DNN) 2024: Delivered lectures in Generative Adversarial Networks (GANs), Diffusion Models, Transfomers, Generative Pretrained Model (GPT), Explainable AI (XAI) and Ethical challenges of AI.                                                         

Imeche 2023: Invited Tallk on Disaster Management with Focus on Aerial Maps                                               

Workshop on Accelerated Chip Design 2023: Invited Talk on Machine Learning at the Edge: HLS for Machine Learning                                                     

Frontiers of Information Technology (FIT) 2021: Invited talk on Computer Vision: Trends, Challenges and Way Forward                                                                       

3rd International Workshop on Functional Reverse Engineering of Machine Tools (WRE) 2021: Keynote Talk on Visual Object Detection                                                                                                                       

Deep Intelligence Workshop 2021: Keynote Speech on Deep Learning: Object Detection and Localization 

2nd International Workshop on Functional Reverse Engineering of Machine Tools(WRE) 2020: Keynote Talk Aerial Sensor Networks                                                                                                                       

National seminar on “HR and Connectivity Development For IT Sector: Challenges and Way Forward  2020: Invited Talk on “Emerging trends in IT and Challenges to Pakistan’s HR Development (Perspective of Academia)”, at Institute for Strategic Studies Research and Analysis (ISSRA), National Defence University (NDU), Islamabad.                                                                                                                                       

Khawaja Farid University of Engineering and Information Technology 2017: Invited Talk on Outcome Based Education

Funded Projects

Autonomous drone in GPS denied Environments

Role: Consultant/FYP Supervisor
Funding Body: ZATNav
Duration: Ongoing (2024 Onwards)
Total Budget: About Rs. 20 M +

Project Summary: This final year project develops AI- and image-based navigation solutions for UAVs operating in GPS-denied or jammed environments, addressing the limitations of conventional GPS and inertial systems. By integrating real-time image processing and deep learning, the system enables accurate localization, situational awareness, and autonomous navigation under constrained computational conditions. This project is being carried out by a group final year students who have extensive knowledge and hands-on experience programming autonmous drones. This prject is fully funded by ZATNav. As an FYP supervisor and Consultant with ZATNav, I contribute to the design and implementation of AI-driven modules, advising on model selection, data preprocessing, algorithm optimization, and the integration of computer vision techniques for satellite and aerial imagery, leveraging my expertise to enhance system robustness and accuracy for space and defense applications.

Artificial Intelligence Based Portable Microscopic Urine Sediment Analysis System

Role: Co-PI
Funding Body: PSF-TUBITAK
Duration: Three Years (2022 – 2025)
Total Budget: About Rs. 50 M

Project Summary: Urine sediment analysis is a critical diagnostic tool for patients with renal illnesses, providing insights into various kidney-related conditions. The microscopic examination of urine particles, including crystals, epithelial cells, red blood cells (RBC), bacteria, and white blood cells (WBC), plays a significant role in identifying renal abnormalities. This research project focuses on enhancing automated urine sediment analysis by using state-of-the-art deep learning based classification and detection algorithms, capable of detecting non-rectangular or non-circular shapes commonly found in microscopic urine sediments.

Target Tracking From Up Above the Sky

Role: PI
Funding Body: HEC NRPU
Duration: Two Years (2019 – 2020)
Total Budget : About Rs. 2.6 M
Project Summary : The use of surveillance cameras to monitor and track target(s) is currently an active area of research, with civil as well as in military applications. The conventional surveillance mechanisms, such as, pre-installed CCTV cameras, are static in nature and lack the capability to robustly monitor and track dynamic target(s) in a timely manner. This project develops cooperative UAV algorithms for multiscale tracking of multiple moving targets, overcoming the limitations of static CCTV systems. Using a quad-tree framework, the novel MTMUT algorithm optimizes UAV placement to maximize coverage and tracking accuracy, outperforming prior approaches in simulations. The work also introduces the multi-FOV QOMDT dataset and YOLO-TLP, a lightweight detector for small aerial objects, validated for real-time performance on both public and custom datasets.

 

Teaching @GIKI

2025
Graduate: CSE501 Advanced Algorithms and Computational Techniques
Undergrad: CS455 NLP Using Deep Learning, DS462 Generative AI with LLMs, CS221 Data Structures and Algorithms

2024
Graduate: CSE511 Theory of Automata II
Undergrad: CS352 Soft Computing

2023 and Before
Graduate: CSE661 Machine Learning and Computer Vision, CSE539 Robotic Vision , SE672 Analysis of Stochastic Processes, CSE535 Advanced Image Processing,  CSE506 Advanced Algorithms and Computational Techniques (CSE Core), CSE639 Advanced BioInformatics, CSE511 Theory of Automata II

Undergrad: Robotic Vision, Data Structures and Algorithms, Conputing and AI, Introduction to Computing and Programming, Logic Design, Theory of Automata, Wireless and Mobile Networks

Teaching (Ex. GIK)
Fundamentals of Data communications, Computer Networks, Computer Programming, Data Structures, Operating Systems, Theory of Automata and Engineering Ethics.
MS/PhD Students (Supervised/Co-supervised)

Graduate Thesis Supervision

MS Students:

Alamgir Noushad: ANALYSING THE PERFORMANCE FIGURES OF MERIT FOR THE ELECTRICAL IMPEDANCE TOMOGRAPHY USING THE POINT SPREAD FUNCTION
Graduated in 2014

Muhammad Atif  (As Co-Supervisor):  DATA MINING-BASED PROFILING PLAYERS USING STARCRAFT DATA FOR VERIFYING DISPOSITIONAL THEORY
Graduated in 2016

Aamir Zeb: MOBILE PHONE USAGE, FEATURE PREFERENCES AND CONCEPTUALIZATION AMONG VARIOUS DEMOGRAPHICS
Graduated in Fall 2016

Muhammad Kamran: A TOP DOWN APPROACH TO ENUMERATE α-MAXIMAL CLIQUES IN UNCERTAIN GRAPHS
Graduated in Spring 2017

Muhammad Imran (As Co-Supervisor): AERIAL CAMERA NETWORK FOR MULTI-SCALE OBSERVATION OF MOVING TARGETS, JANUARY 2018
In Co- Supervision with Dr. Muhammad Asif
Graduate January 2018

Salmab Mehboob: MULTI TARGET TRACKING USING A TEAM OF COOPERATIVE UAVs
Graduated in Spring 2018

Muhammad Nafay: FRUIT-FLY DETECTION USING DEEP LEARNING
Graduated in Spring 2022

Adnan Haider: MULTILEVEL HIERARCHICAL CLASSIFICATION APPROACH FOR DEEPFAKE DETECTION
Graduated in Summer 2024

Muhammad Haroon: MULTI-MODAL BRAIN TUMOR SEGMENTATION USING UNET TRANSFORMER
Graduated in Fall 2024

Muhammad Atif: UAV NAVIGATION IN GPS-DENIED ENVIORONMENT
Graduating in Fall 2025  

PhD Students:

Usman Haider (As Co-Supervisor): SPARSE ENCODING IN DEEP NEURAL NETWORKS
Graduated in 2024

Sania Akhtar (As Co-Supervisor): MICROSCOPIC URINE SEDIMENT ANALYSIS

Fatima Shahzadi (As Co-Supervisor):DEEP FAKE DETECTION TECHNIQUES

Administrative Duties and Committee Work

Dean Faculty of Computer Sciences and Engineering (September 2019 to Date)
HoD Comuter Engineering Program (September 2019 to Date)
Sereved as a member of GIKI Academic council for about seven years
Serverd as a member Undergraduate Admissions Committee for about eight years
Team Lead for Islamabad Admission Centre for GIKI Undergrad Admissions, Fall 2015
Team Lead for Quetta Admission Centre for GIKI Undergrad Admissions, Fall 2017
Served as a meber of Anti-Rigging Committee for about five years
Served as a member SAR committee for BSCE program
Served as a lead member of the Comittee to benchmark BSCE program wtih the ACM curriculum

International Collaborations and MOUs

Active Collaboration with Huawei for the curriclum development of BS in Aritfical Intelligence. As Dean FCSE, lead the initiative for the GIK-Huawei Partnership for BS –AI program.
Focal Person for the MOU with Kumnoh Institue of Technology (KIT), Korea for student and faculty exchange between KIT and GIK Institute.
Focal Person for MOU between GIK Institute and Sawayra Inc., a US-based humanitarian organization working in the areas of renewable energy, water, waste disposal and recycling, etc.
Prominent role in drafting and signing an MOU with University of Missouri, Kansas City (UMKC), USA for student and faculty exchange between UMKC and GIK Institute.

National/External Commitments

Working as Program Evaluator (PEV) with Pakistan Engineering Council (PEC)
Member of 2019 PEC Curriculum Review Committee for Software Engineering Program
Have been a member of 2015 HEC National Curriculum Review Committee for Computer Engineering Program.
Have been Member of NUST SEECS, Industry Advisory Board (IAB).
Currently, member of Study Board, KFUIT
Member Selection board for PAF-IAST

Naitonal Meetings
2014
First Meeting of the HEC National Curriculum Review Committee (NCRC) Computer (Systems) Engineering held on November 10-12, 2014, at HEC Regional Headquarters, Lahore.

2015
Final Meeting of the HEC National Curriculum Review Committee (NCRC) Computer (Systems) Engineering held on April 10-12, 2015, at HEC Regional Headquarter, Peshawar.
2016
Meeting of the NUST-SEECS Industry Advisory Board (IAB). The meeting focused on enhancing the academia-industry linkage and its impact through industrial feedback on the design, delivery and evaluation of the curriculum for BESE degree programs.
2017
Study Board Meeting of BS Computer Engineering Program at Khwaja Fareed University of Engineering & Information Technology (KFUEIT), Rahim Yar Khan.
2018
Represented GIK Institute in “CPEC: Think and Grow Summit”, on 31 March2018, at PITAC, Lahore
2019
6th Meeting of the PEC Sub-Group Software Engineering-ECRDC for Electrical and Allied Engineering (ECRDC) held on February, 7th, at PEC Headquarters, Islamabad.

National Competitions

Ask Leprechaun, an FYP supervised by Dr. Ahmar Rashid, was the 2nd Runner-up at National Championship of NGIRI (Ignite). The team comprised of Dr. Ahmar Rashid, Dr. Sajid Anwar, Engr. Badre Munir, Bilal Aamir, Abdul Rehman and Ahsan Abrar.