Syaheerah Lebai Lutfi, Ph.D

Ryyan Rashid is a committed undergraduate student majoring in computer science with a specialization in intelligent computing at the University of Sains Malaysia. Possessing a robust background in computer science, Ryyan has demonstrated proficiency in developing fully functional web applications and a successful history of constructing various neural networks, including RNN, LSTM, and Transformers, for Natural Language Processing projects. Fueled by a passion for innovation and technology, Ryyan is motivated to contribute to the future of the field. During a six-month tenure as a researcher at Zhang Lab – Harvard Medical School, he actively applied his expertise in Machine Learning, Artificial Intelligence, Image Processing, and Neural Networks, resulting in meaningful…

Eugene is working on a project for International Mobility & Collaboration Centre (IMCC), USM. His project consists of developing a dashboard for the mobility department by using the inbound mobility data and outbound mobility data. Besides that, he has to make enrollment predictions for the enhance resource planning for the IMCC. The first benefit for his client is that visualization of data allows management to make informed decision and secondly, it enhance resource planning.

Muhamad Aizat has developed a machine learning project that will detect a pin failure from testing product data that focused on enhancing current processes which is manual effort of debugging why the pin was fail and replace the pin. The process is lengthy where during the events of products fail in testing, a technician who is debugging the TIU will first address the issue by manually locate the failure pins. The criteria of the pin failure will be determined by test program, and it’s embedded into software that the machine runs. While testing, if the scenario happens, the software will notify user to check the pin of TIU if there…

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Samira Elsamad is now pursuing her PhD under the supervision of Dr. Syaheerah. Her work as a research assistant will focus on developing a machine learning model to analyze fMRI and EEG images to detect neural patterns linked to bribery tendencies. She will use deep learning techniques to train the model to automatically recognize distinct brain activity patterns when participants are exposed to bribery-related stimuli. By combining EEG’s fast electrical signals with the spatial detail from fMRI, she aims to create a predictive model that identifies neural markers associated with pro-bribery attitudes, providing insights into the neural basis of corrupt behaviors. During her Masters’ degree, she was part of the…

IMCC Bantu aims to revolutionize the support system for full-time international students by leveraging machine learning techniques to match them with the perfect helper. Zita’s innovation addresses the critical need for personalized assistance during the challenging transition to a new educational environment. Machine learning algorithms analyze various parameters, including cultural background, language proficiency, to identify the most suitable mentors or guides for incoming international students. This tailored matching process ensures that newcomers receive guidance and support from someone who understands their unique circumstances and can provide relevant assistance. This initiative is crucial as it fosters a smoother integration process, easing the students’ adaptation to a new country. By utilizing machine…

Under the guidance of Dr. Syaheerah, Nahvin Muthusamy leads a pioneering speech analysis research endeavor. Beyond conventional transcription, Nahvin explores linguistic nuances, cultural elements, emotions, personal traits, cognition, and speaker reliability. Employing a diverse dataset and a survey-based approach, Nahvin annotates and timestamps speech data. His research questions the effectiveness of an AI system in analyzing multiple factors, addressing challenges in dataset collection, and benchmarking against existing techniques, utilizing a CNN-based approach on spectrogram representations. Nahvin’s project contributes significantly to advancing speech analysis techniques, fostering natural human-machine interaction, and enabling innovative applications in various domains. The project’s vision is to revolutionize technology, communication, and our understanding of human behavior through…

Aisyahtul was a graduated Master student under the supervision of Dr. Syaheerah and is continuing with her PhD. Her Masters project focuses on data visualization embedded with time series prediction regarding the attrition and promotion issues among the permanent USM staff. The dashboard that describes the attrition pattern and promotion structure that happened in USM has been developed successfully using PowerBI. In order to touch the prediction element of data science, the attrition trend using the time series prediction models has been built using Python and embedded into PowerBI for the best visual. For her PhD, she is exploring multimodal bribery tendency prediction using eye-tracking and survey questions.