Dr Syed Bukahri

• • Designed and developed a multimodal sensing fusion framework integrating thermal, RGB, IoT, and environmental data for reliable perception in agricultural robotic systems.

• • Implemented AI-based fusion models and physics-informed approaches to enhance robustness and accuracy of environmental

monitoring and crop stress estimation.

• • Conducted experimental validation and performance evaluation of sensor fusion algorithms in real-world vineyard/agricultural environments.

• • Lectured and mentored postgraduate students in Artificial Intelligence and Computer Science, focusing on emerging and innovative technologies such as machine learning, deep learning, natural language processing, computer vision, and IoT.

• • Guided students in applying these technologies to real-world applications including healthcare, agriculture, environmental

monitoring, and industrial systems.

• • Promoted the development of students' analytical thinking, communication, and presentation skills through structured sessions

comprising research presentations, peer reviews, and interactive discussions. Provided continuous feedback and academic

support to ensure a high-quality learning experience aligned with course outcomes.

• • Designed curriculum content, lab manuals, and project guidelines integrated with real-world datasets, contemporary research

challenges, and industrial case studies. Encouraged experiential learning by connecting theoretical foundations with practical implementations, enhancing students' problem-solving capabilities and career readiness.

• • Conducted hands-on lab sessions using industry-standard tools and programming frameworks such as Python, TensorFlow, Keras, PyTorch, OpenCV, MATLAB, Scikit-learn, RapidMiner, Jupiter Notebooks, and Google Collab.

• • Developed comprehensive lecture content, quizzes, assignments, project evaluations, and examination materials aligned with

program learning outcomes and modern pedagogical standards. In thisrole, I have delivered and contributed to the following undergraduate-level courses:

◦  AI80010 – as Lecturer.

◦  AI80007 –

◦  AI80005 –

◦  CS80012

• • Lectured and mentored undergraduate and postgraduate students in Computer Science, focusing on both core and advanced subjects such as Software Engineering, Formal Methods, Machine Learning, and Software Design & Architecture. Ensured students developed a solid theoretical understanding and practical skills in applying computational techniques to real-world challenges.

• • Facilitated the development of students' analytical, communication, and presentation abilities through structured learning activities, including classroom discussions, mini-presentations, group projects, and feedback sessions. Maintained a student-centered approach that aligned learning tasks with defined course objectives and program outcomes.

• • Designed comprehensive course materials, including lecture slides, lab manuals, assignments, quizzes, and examination papers. Incorporated industry-relevant problem statements and real-world datasets to enhance experiential learning and better prepare students for roles in the technology sector.

• • Conducted hands-on lab sessions using widely adopted programming and software tools such as Python, MATLAB, Jupyter Notebooks, Eclipse, Visual Studio Code, and software modeling platforms like UML tools to ensure the development of practical technical competencies.

• • Contributed to curriculum development and academic assessment strategies, ensuring continuous enhancement of teaching quality and alignment with institutional academic standards

• • In this role, I have delivered and contributed to the following Undergraduate-level courses:

◦  Software Engineering

◦  Formal Methods

◦  Machine Learning

◦  Software Design and Architecture