Teaching & Mentorship
I am deeply passionate about advancing knowledge in Artificial Intelligence (AI), deep learning, computer vision, and machine learning. My teaching philosophy centers on fostering an engaging, inclusive, and dynamic learning environment where students can connect theoretical concepts with real-world applications.
Courses Taught
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Applied AI for Intelligent Robotic Systems (IE803, Spring 2024)
- This course provided a comprehensive exploration of Applied Artificial Intelligence (AI) in the context of intelligent robotic systems. Topics included machine learning, computer vision, and AI techniques for robotics, with hands-on projects and real-world applications.
- Course Material | Codes | Course Evaluation
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Intelligent Robots (IE916, Spring 2025, planned)
- This course will focus on intelligent robotics, integrating AI concepts with the Robot Operating System (ROS). Students will learn kinematics, dynamics, control, and advanced topics like motion planning and machine learning for robotics.
Student Supervision
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Graduate Research:
- Guided Master’s and Ph.D. students in advanced topics such as semantic segmentation and robustness in AI models. Students achieved recognition in challenges like the STIR-MICCAI Challenge (2024) and MICCAI-SegStrong Challenge (2024).
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Undergraduate Projects:
- Supervised final-year projects and internships focused on computer vision and deep learning.
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Undergraduate Research Program (UGRP):
- Supervised students in developing a robust deep learning approach for surgical tool segmentation in videos, leading to a publication in the 2018 Robotic Scene Segmentation Challenge.
Teaching Assistantship
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Deep Learning (2020 Fall):
- Facilitated lab sessions, graded assignments, and guided students on projects in image segmentation, detection, and classification.
- Course Info
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Machine Learning (2019 Spring):
- Assisted students with concepts such as SVM, HMM, and KNN through lab experiments and feedback on coursework.
- Course Info