PORTFOLIO

MAYEESHA

BASHAR

INTRODUCTION

I am Mayeesha Bashar, a dedicated professional with a BSc in Mechatronics Engineering and a Master's Degree in Artificial Intelligence. As the founder of Xobotronix, I have extensive experience in providing technological and engineering solutions, particularly in automation, digital transformation, and sustainable energy systems. My work spans consultancy for major firms like Ayaat Al Baraka Project Management Services and contributions to innovative projects such as cryptographic digital signatures for CCA ICT Bangladesh. Currently, I am pursuing a Doctor of Philosophy in Engineering at Taylor's University under the Taylor's Research Excellence Scholarship 2024. This e-portfolio showcases my expertise, projects, and pedagogical insights as part of the Tutor Development Program (Cycle 1 - 2025).

Teaching-Learning Philosophy

My teaching philosophy is rooted in fostering critical thinking, practical application, and student-centered learning. Drawing from constructivist pedagogy, I believe students learn best when they actively construct knowledge through hands-on experiences and real-world problem-solving. My engineering background informs my approach, emphasizing logical reasoning, innovation, and adaptability in the classroom. I aim to create an inclusive and engaging learning environment that encourages collaboration and creativity.

Key Pedagogical Perspectives

Constructivism: Encouraging students to build knowledge through exploration and reflection, aligning with experiential learning theories.
Problem-Based Learning (PBL): Using real-world engineering challenges to develop critical thinking and problem-solving skills.
Technology-Enhanced Learning: Integrating digital tools and AI-driven solutions to enhance student engagement and personalize learning experiences.

Professional Background and Contributions

Consultancy at Ayaat Al Baraka Project Management Services (2020–Present)

As a key consultant through Xobotronix, I provided expert technological and engineering solutions for Ayaat Al Baraka, a UAE-based firm specializing in project management, infrastructure development, and hospitality. My contributions included:

Machinery Selection and Specification: Advised on selecting machinery and defining specifications for various projects, ensuring alignment with operational needs.

Inclusive Automation Project: Led initiatives for My Room Holiday Homes Rental in Dubai, focusing on automation in air-conditioning, water pre-heating, and power conservation systems. Implemented sustainable renewable energy solutions.

Digital Transformation and AI Integration: Enhanced safety, security, and engineering processes through AI-driven solutions, contributing to a business turnover increase from AED 5 million to AED 30 million and workforce expansion from 20 to 70 employees within six months.

Cryptographic Digital Signature Project (CCA ICT Bangladesh, 2022–2023)

I played a pivotal role in the thought and idea generation process for implementing cryptographic digital signatures for CCA ICT Bangladesh. This project aimed to enhance security and efficiency in digital transactions, leveraging my expertise in AI and engineering.

Multimedia Contributions

I contributed to developing commercial and informative videos to promote technological and educational initiatives. Below are some of my key works:

Introduction to Xobotronix Solutions

PUBLICATIONS

My research focuses on AI, automation, and engineering solutions. Below are my published works, reflecting my contributions to advancing technology and education:

Bashar, M. (2023).

ENHANCING ROADWAY TRAFFIC MANAGEMENT WITH UAV’SENHANCING ROADWAY TRAFFIC MANAGEMENT WITH UAV’S

International Research Journal of Modernization in Engineering Technology and Science · Sep 1, 2023

Traffic-related issues, such as poor roadway construction, traffic jams, and air pollution, have escalated due to the surge in private car usage, this study's justification lies in its potential to enhance traffic management, sustainable transportation planning, and environmental safety. In this project, we leverage quadcopter technology for cost-effective and efficient traffic monitoring. Users are provided with various options, starting from the ways of flying the quadcopter to visualizing the roadway. Additional features include GPS, telemetry, vehicle detection, a snapshot option in the live video streaming GUI and much more. This study also includes comparison of experimental results with theoretical values, demonstrating a system with a standard deviation of 38.42 for altitude, 167.98 for horizontal distance, and 2.98607 for drone speed. The flight time exceeded calculations, totaling 7.16 minutes, with a negligible 13-millisecond FPV camera latency. Vehicle detection accuracy reached 93.68%. Potential future enhancements could incorporate solar panels for UAV battery charging and signal amplification to extend the monitoring range, allowing for more advanced and autonomous capabilities.

Keywords: Traffic Monitoring, Telemetry, Vehicle Detection, GPS Integration, Real-time Video Streaming

Through GUI.

More Details

Bashar, M. (2023). MACHINE LEARNING-BASED ACUTE LIVER FAILURE (ALF) OUTCOME PREDICTION USED FOR PRIMARY CARE: A COMPREHENSIVE COMPARATIVE STUDYMACHINE LEARNING-BASED ACUTE LIVER FAILURE (ALF) OUTCOME PREDICTION USED FOR PRIMARY CARE: A COMPREHENSIVE COMPARATIVE STUDY

International Research Journal of Modernization in Engineering Technology and Science · Aug 1, 2023International Research Journal of Modernization in Engineering Technology and Science · Aug 1, 2023

Given its rapid progression and widespread impact, Acute Liver Failure (ALF) is a serious health problem. The goal of this study was to create a predictive machine learning model that can be used in primary care settings. To predict the ALF outcome, six machine learning algorithms were used: Nave Bayes, Decision Trees, Random Forests, SVM, KNN and Logistic Regression. The study used evaluation measures such as accuracy, sensitivity, specificity, AUC for ROC and model fitness score in 23 trials using various techniques such as model tuning, feature selection and sampling techniques (both under sampling and oversampling). Notably, with oversampling and tuning, Nave Bayes had the highest accuracy of 0.9377. The tuned Random Forest, using an unsampled data set without feature selection, had the lowest accuracy of 0.7697. This 16.8% improvement illustrates the success of the proposed method. Additionally, a 17.77% improvement was achieved over previous research. This study provides important insights into improving ALF predictability in primary care using machine learning methods.

Keywords: Acute Liver Failure, Machine Learning, Predictive Model, Primary Care, Evaluation Metrics, Algorithm Comparison.

More Details

✽ Teaching-Learning Materials

Summary of Key Readings

"How People Learn: Brain, Mind, Experience, and School" (National Research Council, 2000)

This seminal work emphasizes the importance of active learning and prior knowledge in shaping effective teaching strategies. It highlights the need for educators to design lessons that connect new concepts to students' existing frameworks, which I apply by integrating real-world engineering problems into my teaching.

EdTech Magazine: "What Is Ed Tech (Educational Technology)?" (2024)

This article discusses how educational technology enhances student engagement through tools like AI and interactive platforms. I incorporate AI simulations and collaborative tools like Google Classroom to create dynamic engineering education experiences. Access here.

"Problem-Based Learning: An Overview of its Process and Impact on Learning" (2019)

Published in the Journal of Problem-Based Learning in Higher Education, this article outlines how PBL fosters critical thinking and collaboration in higher education. I design project-based assignments, such as automation system design, to mirror real-world engineering challenges, encouraging practical application. Access here.

Classroom Management Strategies

Clear Objectives:

Setting transparent goals to ensure focus and accountability.

Interactive Learning:

Using group discussions, simulations, and case studies to engage students.

Continuous Feedback:

Implementing peer reviews and instructor evaluations to support student growth.

Reflections on Teaching and Learning

My consultancy experience has honed my ability to communicate complex ideas clearly, a skill I apply in the classroom to facilitate discussions. Observing teaching sessions in the Tutor Development Program, I noted the effectiveness of interactive methods like PBL, which align with my constructivist approach. Moving forward, I plan to:

Integrate AI-driven simulations to teach complex engineering concepts.

Design assessments that encourage practical application of theoretical knowledge.

Use reflective practices to refine my teaching based on student feedback.

Future Plans as an Educator

To enhance my effectiveness as a tutor, I will:

Apply Learning Sciences: Use cognitive science principles like spaced repetition to improve retention.
Leverage Technology: Develop interactive e-learning modules on platforms like Wix or WordPress.
Pursue Professional Development: Attend workshops on pedagogy and AI advancements to stay at the forefront of engineering education.