• Developed machine learning algorithms, used these algorithms to prototype AI systems, andevaluated the performance of the developed systems.• Developed an intelligent personal assistant on a cloud-based robotic platform to assist older adults in performing their daily activities.• Developed natural language processing algorithms to assess and monitor the progress of dementia.• Collaborated with different research teams from multiple disciplines and organizations.• Supervised undergraduate and graduate students and guided them in their research while maintaining steady progress of the projects.

SYSC 3020: Introduction to Software Engineering • Managed students and engaged them in the learning process to achieve the course objectives.• Assessed students’ exams and provided feedback to improve the quality of learning.• Coordinated with the teaching assistants to identify the progress of the students.

• Developed optimization models, analyzed and reduced their computational complexities, and benchmarked the developed models.• Developed convex and non-convex optimization models for smart homes to evaluate the impact of energy trading on cost optimization.• Developed a novel near-optimal optimization algorithm, named ECO-Trade, to solve a large-scale resource scheduling problem in smart homes.• Reduced solution time of an NP-hard optimization problem from a couple of hours to few minutes.

• Trained the students to identify the components of embedded systems and assisted them to effectively program these components in real time OS.• Tested and debugged assembly and C programs to verify correctness and identify errors. • Managed students in the labs, engaged them in the learning process to achieve the course objectives.• Assessed student assignments, lab reports and exams and provided feedback to improve the quality of learning.• Coordinated with the instructor to identify the progress of the students.

• Identified energy efficient sensors and associated low power communication protocols to implement a network of internet of things.• Experimented with RFID receivers and tags, analyzed results to find the feasibility of solutions in practical scenarios.

• Developed machine learning algorithms to predict human activities, activity durations, and activity intervals in smart homes using the data generated by ambient IoT sensors.• Developed a novel machine learning algorithm, named SPEED, for time series prediction using a variable-order Markov model; improved 22% prediction accuracy compared to the state-of-the-artalgorithm.• Worked in a multi-organizational project involving seven Malaysian universities, a government research organization, and an electronic design company.

• Conducted requirement analysis and created software specifications for application development.• Designed and implemented database architectures for a telecom billing system.• Developed, debugged and tested web applications for data processing and management.