Robotics · Feedback control · Mechatronics
M.S. Student and Graduate Researcher in Mechanical and Robotics Engineering at the Gwangju Institute of Science and Technology (GIST)
I develop feedback-controlled mechatronic systems that sense, process information and act in real time.
My current research at GIST focuses on system identification and embedded feedback control for contact-mode atomic force microscopy, with the aim of improving imaging speed and tracking performance. My broader interests include robotics and learning-based control of physical systems.
Dynamics & Control Lab, advised by Prof. Kyi Hwan Park
This portfolio is under development. Further project details and research updates will be added.
Selected work
Up to what scan frequency do the forward and backward topographies of a contact-mode AFM remain consistent under digital PI control of the Z-axis?
ContributionSystem identification, controller design, STM32 implementation, analog front-end revision and imaging experiments within the laboratory project.
EvidenceTrace–retrace r ≥ 0.977 through 5 Hz; agreement degrades at higher scan rates.
A single-axis voice-coil stage has no restoring spring, so the plant integrates twice and supplies no phase lead of its own.
My roleBench designed in SolidWorks and built, current drive, identification and six analog compensators.
EvidenceSix compensators built and tested; lead compensation retained after bench evaluation.
Eight channels of forearm sEMG have to become an estimate of intended hand state fast enough for a person to steer an interactive task.
My roleAcquisition and feature pipeline, classifier comparison and deployment, three task interfaces, and the evaluation protocol.
Evidence150 ms classification window, online interfaces at one to three degrees of freedom, and the MUSED-I dataset.
A wearable rehabilitation glove needs actuators that bend where a finger bends, built from material and constraint rather than joints.
My roleThree actuator geometries, ANSYS analysis, soft-lithography fabrication and the pneumatic drive.
EvidenceBench-measured 120–180° flexion per actuator segment at 100 kPa. Functional hand performance was not assessed.
Research interests
Identifying a physical plant from measurement, shaping a loop against its real resonances, and implementing that loop where saturation, quantisation and finite sample rates apply.
Current focus — AFM Z-axis, voice-coil stage
Acquisition, feature extraction and online inference on biosignals, evaluated as interfaces a person actually steers rather than as offline classification scores.
Established through prior research — sEMG interfaces, soft glove
Unsupervised models built on measured machine and human signals, and where that leads: control that improves from physical interaction rather than from a model alone.
Developing direction — not yet a research contribution
Research outputs
Poster presentation · 2026
23rd IFAC World Congress, Busan, Republic of Korea, 23–28 August 2026. Presented by M. M. Khan.
Dataset · 2023
IEEE DataPort, August 2023 · doi:10.21227/04zq-yz45
About
Before joining GIST, I studied mechanical engineering at NUST, where my research included real-time surface electromyography (sEMG) interfaces and fibre-reinforced pneumatic actuators for rehabilitation. I now conduct research in the Dynamics & Control Lab under Prof. Kyi Hwan Park.
My research approach combines experimental system identification, controller design and embedded implementation. I evaluate models and controllers through hardware experiments, with particular attention to sensing, signal conditioning and real-time operation.
Education
M.S., Mechanical and Robotics Engineering — GIST, 2025–2027 (expected)
B.E., Mechanical Engineering — NUST, 2019–2023
Methods
System identification and loop shaping · real-time embedded control · instrumentation and analog signal conditioning · feature extraction and applied machine learning
