“Next Gen” Spotlight: Seyed Amir Sheikh Ahmadi
I’m Seyed Amir Sheikh Ahmadi, a PhD student in Mathematical Science at RMIT University. My academic background is in Computer Engineering, and I have extensive experience in teaching data analysis, data mining, machine learning, and data science courses. Over the past nine years, I’ve published more than 50 journal papers and presented numerous conference papers. I was recognized as the most outstanding researcher among all academics in Kurdistan province, earning the University Dean award for Islamic Azad University of Kurdistan from 2016 to 2023.
I’m pursuing my PhD under the supervision of Dr. Laleh Tafakori and Prof. Mahdi Jalili, focusing on using Graph Neural Networks to identify influential nodes in complex networks. I chose this project due to my previous background and its diverse applications, such as viral marketing, information dissemination, controlling the spread of epidemic diseases, enhancing network stability, and minimizing rumour spread. The prospect of uncovering key regulatory mechanisms within these networks excites me, as it promises to contribute valuable insights to the field of network science and advance the application of data science in various research domains.
One of the most pleasant surprises has been the collaborative nature of the research. I have had the opportunity to work with brilliant minds from various disciplines, enriching my research and broadening my perspective. Additionally, the rapid advances in Graph Neural Networks have been both challenging and exciting, constantly pushing me to stay updated and innovate.
My interest in data science stemmed from my fascination with the patterns and insights hidden in large datasets. During my master’s degree in computer engineering and my experience as a university lecturer, I discovered the power of data in solving real-world problems. This led me to pursue further studies and eventually specialise in data analysis and machine learning. The ability to derive actionable knowledge from data continues to inspire and motivate my research.
One of the significant challenges facing the data science community is the ethical use of data and ensuring privacy. With the exponential growth of data collection, it’s crucial to develop methods that protect individual privacy while still enabling valuable insights. Additionally, ensuring the interpretability and transparency of machine learning models is essential for building trust and facilitating fair decision-making processes. A pressing research question we should be addressing is how to create robust, interpretable models that can be transparently applied across various fields without compromising ethical standards. This involves developing algorithms that not only perform well but also provide understandable and justifiable results.
Outside of my academic pursuits, I enjoy gymnastics and spending time with my family. Family time helps me recharge and often sparks new ideas for my research. Additionally, I have a passion for watching movies, which provides a creative outlet and a perfect balance to my analytical work.