Postdoctoral Associate, State University of New York, United States
Dr. Nuzla Ismail is a dynamic Postdoctoral Research Fellow specializing in bioinformatics and machine learning, with a PhD in Information Science. With over a decade of experience spanning academia and industry, she has played a transformative role in over 100 global projects. Her career is driven by a passion for turning complex data into actionable insights and pioneering predictive models for real-world impact. Recognized for her innovative contributions and leadership, Dr. Ismail actively explores advanced genetic analysis, disease prediction models, and the development of scalable data systems. 🌐🧬
Publication Profile
Google Scholar
🎓 Education Background:
Dr. Ismail earned her PhD in Information Science from the University of Otago, New Zealand in 2022. She holds a dual undergraduate background with a B.Sc. from the University of Sri Jayewardenepura and a BEng (Hons) in Software Engineering from Staffordshire University, UK (2015). Her academic journey reflects a unique blend of computing, bioinformatics, and data science education. 🎓📚
💼 Professional Experience:
Currently serving as a Postdoctoral Researcher at the State University of New York, Buffalo (2025–Present), Dr. Ismail applies her bioinformatics expertise to decode complex genetic networks. She has previously held roles at the University of Otago, including Postdoctoral Fellow and Research Assistant, contributing to pioneering work in genome graphs and structural variant detection. Her industry experience includes positions such as Architect/Data Scientist at Axiata Digital Labs and Consultant at Alex Solutions. She also held technical and academic roles, showcasing her versatile skills in IT deployment, robotics education, and business intelligence systems. 💻🧑🔬
🏅 Awards and Honors:
Dr. Ismail is a recipient of prestigious awards such as the University of Otago Doctoral Scholarship (2017), Google Grace Hopper Scholar (2016), and the Google Anita Borg Memorial Scholarship (2014). She has also represented globally at events like the ACM Tapia Celebration of Diversity, CERN’s Port Hackathon, and the NYUAD Hackathon for Social Good. Her recognition spans innovation, leadership, and diversity in STEM. 🏆🌍
🔎 Research Focus:
Her research is focused on computational biology, genome graph methodologies, and predictive analytics for wildfire modeling and disease risk estimation. She explores machine learning, structural variant detection, and genomic simulations for human and agricultural health. Her contributions extend to AI applications in climate science and bioinformatics workflow development. 🔬🔥🌱
🧭 Conclusion:
Dr. Nuzla Ismail is an interdisciplinary innovator whose work intersects data science, genetics, and AI. With a strong global presence and a robust publication portfolio, she continues to inspire progress in bioinformatics and data-driven decision-making. She is open to new collaborations, mentorship opportunities, and knowledge-sharing in her research domains. 🌟📈
📚 Top Publications
Modelling Methane Emissions from Rice Paddies Using Machine Learning – 2024, IVCNZ 2024.
Cited by: 3 articles.
Pangenome graphs in infectious disease: a comprehensive genetic variation analysis of Neisseria meningitidis leveraging Oxford Nanopore long reads – 2023, Frontiers in Genetics.
Cited by: 9 articles.
A Comparison of One-Class Versus Two-Class Machine Learning Models for Wildfire Prediction in California – 2023, Australasian Conference on Data Science and Machine Learning.
Cited by: 5 articles.
One-Class Classification-Based Machine Learning Model for Estimating Wildfire Risk – 2023, Procedia Computer Science.
Cited by: 6 articles.
An assessment of existing wildfire danger indices in comparison to one-class machine learning models – 2024, Natural Hazards.
Cited by: 4 articles.
Evaluating the boundaries of Big Data environments for Machine Learning – 2019, AI 2019: Australasian Joint Conference.
Cited by: 11 articles.