Zhi Wei

Professor

New Jersey Institute of Technology

United States

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About

Dr. Zhi Wei is a Professor at the New Jersey Institute of Technology in the United States. His research focuses on deep learning frameworks for single-cell data integration, multi-omics analysis, and spatial omics data interpretation. Recent contributions include advancements in multi-omics pipelines, generative models for multitasking analysis, and applications of deep learning in cellular diversity and immune response studies.

Zhi Wei

Research Interests

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About

Articles (17)

scDILT: A Model-Based and Constrained Deep Learning Framework for Single-Cell Data Integration, Label Transferring, and Clustering

Innate and Adaptive Immune Parameters following mRNA Vaccination in Mice

Dependency-aware deep generative models for multitasking analysis of spatial omics data

Tjong: A transformer‐based Mahjong AI via hierarchical decision‐making and fan backward

Discrete latent embeddings illuminate cellular diversity in single-cell epigenomics

MultiSC: a deep learning pipeline for analyzing multiomics single-cell data

Hidden Markov random field models for cell-type assignment of spatially resolved transcriptomics

Clustering of single-cell multi-omics data with a multimodal deep learning method

A convolutional neural network model for survival prediction based on prognosis-related cascaded Wx feature selection

Fa-Mb-ResNet for Grounding Fault Identification and Line Selection in the Distribution Networks

An active learning approach for clustering single-cell RNA-seq data

MGEL: Multigrained Representation Analysis and Ensemble Learning for Text Moderation

Very low mutation burden is a feature of inflamed recurrent glioblastomas responsive to cancer immunotherapy

Model-based deep embedding for constrained clustering analysis of single cell RNA-seq data

Elucidation of DNA methylation on N6-adenine with deep learning

An Enriched Time-Series Forecasting Framework for Long-Short Portfolio Strategy

Dynamic surface control for a class of nonlinearly parameterized systems with input time delay using neural network

Collaborators (3)

Michael Brown

Matthias Gromeier

Mano Joseph MATHEW

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