NJIT Computing Professor Zhi Wei Named Fellow of AAAS, Follows IEEE Honor

Zhi Wei, a bioinformaticist, was elected to the 2024 Fellows class of the prestigious American Association for the Advancement of Science.

Wei, who joined NJIT’s Ying Wu College of Computing in 2008 and now holds the role of distinguished professor, also became an IEEE Fellow in 2024.

“Being elected as an AAAS Fellow is a deeply meaningful recognition for me. While the IEEE Fellowship primarily acknowledges technical and engineering contributions, the AAAS Fellowship reflects broader impact in advancing science and its applications to benefit society,” Wei said.

Wei’s major career accomplishments relate to artificial intelligence and machine learning, with a focus on applications in biomedical fields. He cited three papers that best represent his work: Clustering single-cell RNA-sequencing data with a model-based deep learning approach, which introduced a deep learning framework for clustering single-cell RNA-sequencing data; From disease association to risk assessment: an optimistic view from genome-wide association studies on type 1 diabetes, focusing on disease risk prediction based on individual genetic profiles and machine learning methods; and Dependency-aware deep generative models for multitasking analysis of spatial omics data, presenting a deep generative model that integrates spatial and molecular dependencies in tissue profiling.

He’s also graduated 13 Ph.D. students and said his favorite course to teach is CS-732, Advanced Machine Learning. “It covers advanced machine learning and deep learning methods, and uses many real-world domain sciences as application examples. I enjoy helping them bridge those worlds. Seeing students grasp complex algorithms and then apply them to real application problems is incredibly rewarding and inspiring,” Wei noted.

Looking forward, “I plan to be more involved with AAAS,” Wei added. “I’m particularly interested in engaging with initiatives that promote data science and AI in life sciences, as well as efforts that enhance public understanding of science. I also hope to contribute to mentoring programs and participate in future AAAS meetings and symposia to help shape policy discussions at the intersection of science, ethics and society.”

“The next decade will see AI models becoming essential for understanding biological systems, especially through integration of multi-modal, high-dimensional data. For my own work in this area, I have a multimillion-dollar NIH grant pending for approval, in which I will develop large-scale foundation models for single-cell omics data” — which in simple terms means he'll use AI to figure out how individual genes react to treatments, he explained.

“For AI in the biomedical science field, I anticipate a strong shift toward explainable AI in health applications, and new frameworks that unify learning from biology, clinical/medical records, and environmental/social behavior data to drive truly personalized medicine. Ethical AI, fairness in health outcomes and cross-disciplinary collaboration will also be major pillars of future research.”