Ameer H. Khan
(+852) 65985117 | ahakhan@polyu.edu.hk | Google Scholar (Citations: 1193, h-index: 13) | Scopus (Citations: 999, h-index: 12) | ahk
Jan. 2022 ‑ Present
• Pioneered interdisciplinary research at the intersection of robotics and geo‑informatics, contributing to Smart City Research Institute (SCRI)
initiatives.
• Designed robotics‑driven solutions addressing urban science and smart city challenges, emphasizing geo‑informatics integration.
• Key contributions to the robotic platform include:
Implemented a robust 2D and 3D LiDAR‑based Simultaneous Localization and Mapping (SLAM) system to enable accurate environmental mapping.
Utilized the developed SLAM framework to generate an interconnected 3D digital twin of the university campus, integrating spatial and geo‑informatics data.
Built a comprehensive ROS‑based autonomous navigation stack, leveraging the digital twin for dynamic path planning and integrating real‑time obstacle detection
using visual depth sensors.
• Advanced worker safety in high‑risk construction environments by deploying computer vision systems capable of real‑time identification of unsafe
behaviors.
• Key enhancements to safety systems include:
Integrated traditional computer vision models with advanced multimodal AI techniques to enhance detection accuracy.
Developed deep learning‑based hazard detection models capable of identifying unsafe behaviors in real‑time.
Incorporated real‑time alerting mechanisms to alert the monitoring authority about the hazardous behavior.
The project aims to ensure compliance with government‑mandated construction safety regulations, addressing both legal and operational safety requirements.
• Mentored 8 Masters and 1 Bachelors student, with ongoing supervision of a Masters student.
• Delivered impactful courses including ’Geomatics Algorithms and Programming’, ’Smart Cities: Technologies and Solutions’, and ’Urban Science and
Systems’.
June 2021 ‑ Dec. 2021
• Innovated dialogue intent classification algorithms, emphasizing few‑shot learning for NLP applications, resulting in improved classification
accuracy and enabling practical deployment in multilingual conversational systems.
• Integrated cutting‑edge medical image classification techniques with NLP to develop Medical Visual Question Answering (Med‑VQA) systems.
May 2021
Worked on a research framework for a multilingual conversational analytics engine using deep‑learning‑based NLP techniques.
March 2021 ‑ April 2021
Utilized graph theory to analyze virus transmission patterns, considering social and environmental constraints.
Sep. 2015 ‑ May 2016
• Collaborated in the Cyber‑physical systems lab to enhance indoor localization, mapping, and drone path planning.
• Engineered a camera‑based 3D localization system to guide drone movements in indoor settings.
• Explored deep learning applications for 3D object localization using multiple video streams, advancing indoor positioning solutions.
Graduated
Aug. 2016 ‑ Jan. 2021
My research is primarily focused on developing an artificial learning‑based control framework for hybrid robotic agents, a novel combination of
traditional articulated robots with the emerging field of so robotics. I developed algorithms for the motion control of articulated robots while
consideringcritical real‑world constraintssuchas; obstacleavoidance, RCM constraintsfor surgical robots, and nonholonomic constraintsofthe mobile
platforms. I also explored the prospects of integrating so actuators with articulated robots and carried out several experimental studies to bridge the
gap between classical control and so robotic control paradigm.
My Ph.D. thesis presented a recurrent neural network (RNN)‑based generalized optimal‑control framework for hybrid robotic agents and applied it to
solve real‑world control problems. The thesis demonstrates the superiority of the proposed control framework compared to the traditional techniques,
supporting the claim on theoretical foundations supported by numerical and experimental evaluations.
CGPA: 3.94/4
Sep. 2011 ‑ June 2015
I got my Bachelor’s degree in electrical engineering with a major in electronics and embedded systems while securing the second‑highest GPA in the
class. My final year project was the implementation of the Kalman‑filter on FPGA to analyze the fNIRS signal for real‑time detection of brain activity. I
was awarded scholarships and awards based on academic excellence.
• A.H. Khan, X. Cao and S. Li, “Management and Intelligent Decision‑Making in Complex Systems: An Optimization‑Driven Approach,”
Springer Nature, 2020. doi: 10.1007/978‑981‑15‑9392‑5
• A.H. Khan, H. Su, X. Cao, D.T. Pham, Z. Ji, M. Packianather, and S. Li, “BOMO‑RNN: A Novel Neural Model for Manipulability Optimization of Industrial
Robots with Experimental Validation,” International Journal of Systems Science, 2025. Impact Factor: 4.9
• A.H. Khan and S. Li, “Discrete‑Time Impedance Control for Dynamic Response Regulation of Parallel So Robots,” Biomimetics vol. 9, no. 6, pp. 323,
2024. doi: 10.3390/biomimetics9060323 Impact Factor: 3.4
• A.H. Khan, S. Li, and X. Luo, “Obstacle avoidance and tracking control of redundant robotic manipulator: An RNN based metaheuristic approach,”
IEEE Transactions on Industrial Informatics, 2019. doi: 10.1109/TII.2019.2941916 Impact Factor: 11.7
• A.H. Khan, Z. Shao, S. Li, Q. Wang, and N. Guan, “Which is the best PID variant for pneumatic so robots? An experimental study,” IEEE/CAA Journal
of Automatica Sinica, vol. 7, no. 2, pp. 451‑460, 2020. doi: 10.1109/JAS.2020.1003045 Impact Factor: 15.3
• A.H. Khan, S. Li, Dechao Chen, and Liefa Liao,“Tracking control of redundant mobile manipulator: An RNN based Metaheuristic Approach,”
Neurocomputing, 2020. doi: 10.1016/j.neucom.2020.02.109 Impact Factor: 5.5
• A.H. Khan, X. Cao, S. Li, V.N. Katsikis, and L. Liao, “BAS‑ADAM: An ADAM based approach to improve the performance of beetle antennae search
optimizer,” IEEE/CAA Journal of Automatica Sinica, vol. 7, no. 2, pp. 461‑471, 2020. doi: 10.1109/JAS.2020.1003048 Impact Factor: 15.3
• A.H. Khan, X. Cao, B. Xu, and S. Li, “Beetle Antennae Search: Using Biomimetic Foraging Behaviour of Beetles to Fool a Well‑Trained Neuro‑Intelligent
System,” Biomimetics vol. 7, no. 3, pp. 84, 2022. doi: 10.3390/biomimetics7030084 Impact Factor: 3.4
• A.H. Khan and S. Li, “Sliding Mode Control With PID Sliding Surface for Active VibrationDamping of Pneumatically Actuated So Robots,” IEEE Access,
pp. 88793‑88800, 2020. doi: 10.1109/ACCESS.2020.2992997 Impact Factor: 3.47
• A.H. Khan, X. Cao, V.N. Katsikis, P. Stanimirović, I. Brajević, S. Li, S. Kadry and Y. Nam, “Optimal Portfolio Management for Engineering Problems Using
Nonconvex Cardinality Constraint: A Computing Perspective,” IEEE Access, 2020. doi: 10.1109/ACCESS.2020.2982195 Impact Factor: 3.47
• A.H. Khan, S. Li, and X. Cao, “Tracking control of redundant manipulator under active remote center of motion constraints: An RNN‑based
metaheuristic approach,” SCIENCE CHINA Information Sciences, 2020. doi: 10.1007/s11432‑019‑2735‑6 Impact Factor: 7.27
• A.H. Khan, X. Cao, S. Li, and C. Luo, “Using social behavior of beetles to establish a computational model for operational management,” IEEE
Transactions on Computational Social Systems, 2020. doi: 10.1109/TCSS.2019.2958522 Impact Factor: 4.74
• A.H. Khan and S. Li, “Dynamic manipulation of pneumatically controlled so finger for home automation,” Measurement, 108680, 2020. doi:
10.1016/j.measurement.2020.108680 Impact Factor: 5.13
• A.H. Khan, S. Li, X. Zhou, Y. Li, M.U. Khan, X. Luo, and H. Wang, “Neural & bio‑inspired processing and robot control,” Frontiers in neurorobotics, 2018.
doi: 10.3389/fnbot.2018.00072 Impact Factor: 3.493
• A.H. Khan, S. Li, B. Xu, and X. Cao, “A Model‑Free Approach for Online Optimization of Nonlinear Systems,” IEEE Transactions on Circuits and Systems
II: Express Briefs, 2021. doi: 10.1109/TCSII.2021.3079125 Impact Factor: 3.69
• L. Xiao, S. Li, F.J. Lin, Z. Tan, and A.H. Khan, “Zeroing neural dynamics for control design: comprehensive analysis on stability, robustness, and
convergence speed,” IEEE Transactions on Industrial Informatics, 15, no. 5, 2018. doi: 10.1109/TII.2018.2867169 Impact Factor: 11.64
• Y. Zhang, S. Li, J. Zou, and A.H. Khan, “A passivity‑based approach for kinematic control of manipulators with constraints,” IEEE Transactions on
Industrial Informatics, 2019. doi: 10.1109/TII.2019.2908442 Impact Factor: 11.64
• D. Guo, Z. Li, A.H. Khan, Q. Feng, and J. Cai, “Repetitive motion planning of robotic manipulators with guaranteed precision,” IEEE Transactions on
Industrial Informatics, 2020. doi: 10.1109/TII.2020.2970172 Impact Factor: 11.64
• Q. Wu, X. Shen, Y. Jin, Z. Chen, S. Li, A.H. Khan, and D. Chen, “Intelligent beetle antennae search for UAV sensing and avoidance of obstacles,” Sensors,
19, no. 8, 2019. doi: 10.3390/s19081758 Impact Factor: 3.58
• X. Cao, X. Pu, C. Hua, B. Liao, and A.H. Khan, “Neural Dynamics for Constrained Bi‑Objective Quadratic Programming with Applications to Scientific
Computing,” Tsinghua Science and Technology, 2024. Impact Factor: 5.2
• A.H. Khan, X. Cao, and S. Li, “Recurrent Neural Network based Nonlinear Orientation Control of Redundant Stewart Platform,” Expert Systems With
Applications, Under Revision.
• D. Yang, W.Z. Shi, A.H. Khan, “Degeneracy‑Resistant LiDAR‑SLAM Algorithm based on Geometric and Visual Features Fusion,” Journal of Field
Robotics, Under Revision.
• C. Yang, Y. Zhang, and A.H. Khan, “Undetectable Attack to Deep Neural Networks Without Using Model Parameters,” In International Conference on
Intelligent Computing (pp. 46‑57), Singapore, July 2023.
• X. Li, B. Liu, A.H. Khan, F. Lu, and X.M. Wu, “Multi‑modal pre‑training for medical vision‑language understanding and generation: An empirical study
with a new benchmark,” Conference on Health, Inference, and Learning (CHIL), Proceedings of Machine Learning Research 209:117–132, 2023.
• A.H. Khan, Z. Shao and S. Li, “A Novel Active Damping Mechanism for Multi‑Chambered Parallel So Robots,” IROS Workshop on So Robotic
Modeling and Control: Bringing Together Articulated So Robots and So‑Bodied Robots, short paper poster presentation, 2018.
• M.S. Nazir, M. Aqil, A. Mustafa, A.H. Khan, and F. Shams, “Real‑time brain activation detection by FPGA implemented Kalman filter,” International
Conference on Control, Automation and Systems (ICCAS), pp. 432‑435, 2015. doi: 10.1109/ICCAS.2015.7364954
PolyU
Mathworks
PolyU
Mathworks
PolyU
PolyU
PIEAS
IEEE ISB SB
PIEAS
BISE, Gujranwala
• IEEE Transactions on Cybernetics
• Neurocomputing
• So Robotics
• IEEE Access
• Neural Processing Letter
• Applied Mathematics and Computation
• Journal of Sensors
• Mathematics
• International Journal of Systems Science
• IEEE Open Journal of Circuits and Systems
• International Journal on Artificial Intelligence Tools
• IEEE Transaction on Industrial Informatics
• So Computing
• IEEE Transactions on Circuits and Systems II: Express Briefs
• IEEE Transactions on Cognitive and Developmental Systems
• PeerJ Computer Science
• Frontiers in Neurorobotics
• Frontiers in Medical Technology
• Advanced Control for Applications
• Energy Systems
• IEEE Open Journal of Circuits and Systems
• Journal of Systems and Control Engineering
• Measurement
• IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
• IEEE Symposium on Recent Advances in Electrical Engineering (RAEE)
• IEEE Conference on Decision and Control (CDC)
PolyU
April ‑ June 2019
Gained knowledge and experience in developing a business plan and learned tools to analyze its viability. The program spanned ten weeks, with a
focus on converting our research project into a commercial business idea.
PolyU
March 2018
Participated in the entrepreneurial competition as a member of our research team. Gained experience about the development of a business plan and
pitching it to an investor.
PIEAS
April 2014 ‑ April 2015
Gained valuable experience in leadership, teamwork, and conflict management by organizing activities for the society. Worked as a member of the
organizing committee for a national level entrepreneurial competition, CREATE’15.
Online
March 2024
Enhancing Construction Site Safety through the Application of Vision AI models in Autonomous Mobile Robots.
Online
December 2022
Seminar on Design, Construction, Optimization, and Control of Robotic systems.
Online
May 2021
Delivered a research talk on the Applications of Optimization Algorithms for the Control of Robotic Systems.
PolyU
July 2019
Summarized the learning and experiences of ten weeks long entrepreneurial program. The presentation discussed important factors related to
commercializing a research project.
PolyU
May 2019
Delivered a mock presentation to angel investors. The goal was to preset the commercial viability of research projects.
PolyU
June 2018
Presented an idea to apply modern computing and robotic developments to automate the functioning of financial institutes.
PolyU
March 2018
Pitched the business idea related to our research project to an angel investor.
PolyU
April 2017
Presented our lab project about human assistive robots and presented its potential applications to aid the elderly. My team won second prize.
Oulu, Finland
October 2025
The conference will be held in Oulu, Finland, on theme of ”Autonomous Intelligent Systems” and I will be chairing a special session on ”AI for
Autonomous Navigation and Surveillance Systems: Innovations and Challenges”.
MDPI, Biomimetics
2024
This SI gathered the latest research related to nature‑inspired metaheuristic optimization algorithms and their applications in engineering, robotics,
computer science, and other fields. [Link]
MDPI, Biomimetics
2025
Aer success of 2024 version, this SI is organized to gather the latest research related in areas related to metaheuristic and its applications. [Link]
IEEE JSAS
2025
This special issue aims to provide a platform for researchers to present their latest research on data‑driven intelligent sensor calibration and its
applications. [Link]
Digital Finance
2025
This special issue aims to provide a platform for researchers to present their original research, reviews, and case studies on the use of generative AI in
financial services. [Link]
