Grace Hopper AI Research Institute Fellowship in Biomedicine

Discover hands-on undergraduate research opportunities in AI-driven biomedical innovation across NJIT labs. Projects span exoskeleton control, brain imaging, epidemic forecasting, and more—ideal for students with programming and STEM backgrounds.

Research

Participating Labs:

Vivek Kumar Lab:

Inventing novel biomaterials that signal different cell receptors to regenerate tissue.

Project: AI/ML guided peptide drug design platform to minimize the molecular space for lead generation. We are looking for UG students who are interested in learning AI/ML models for computational peptide design, docking to different receptors and their molecular dynamic interactions. These algorithms will then be used to optimize cell binding and biomaterial strength without the need to delve into the entire (biological) design space through bespoke machine learning algorithms.

Requirements: Some background in computational programming. Pre-med, computational bioinformatics, pharmacology, computational biology, and related.

Website: kumarlab.njit.edu

PI Contact info: vak@NJIT.edu

 

Lijing Wang Lab:

Project: AI for Reliable Epidemic Forecasting. We are seeking motivated undergraduate (UG) students with a strong interest in machine learning, data science, and public health to contribute to our epidemic forecasting research project.

Requirements: Basic knowledge of Python, machine learning, and deep learning frameworks (e.g., PyTorch, TensorFlow). Prior experience with time-series forecasting, LSTMs, or GNNs is a plus but not required. Students in Computer Science, Data Science, Biomedical Engineering, Public Health, or related fields. Basic understanding of statistics and machine learning concepts.

Website: https://christa60.github.io

PI Contact info: lijing.wang@njit.edu

 

Zhifeng Kou Lab:

Translational Medical Imaging

Project: Development of next generation surgical planning and surgical navigation platform. We are leveraging the cutting edge AI and medical image processing to develop next generation technologies for brain surgery.

Requirements: Related background in image processing, machine learning and/or large language model will be preferred.

Website: https://people.njit.edu/profile/zk94

PI Contact info: Zhifeng.kou@njit.edu 

 

Bryan Pfister Lab:

CIBM3 Center

Project: automated cell tracking of histology data. We expect students to work on the development and implementation of AI/ML approaches to automate and improve the analysis of cell morphology in brain histological images.

Requirements: image processing background and basic machine learning knowledge

Website: https://people.njit.edu/profile/pfister

PI Contact info: bryan.j.pfister@njit.edu

 

Jongsang Son Lab:

Clinical Neuromuscular Adaptation Laboratory (CNAlab)


Project: Artificial Intelligence (AI)-driven outdoor activity monitoring. This project is to collect human movement data during various activities and to develop AI-based activity monitoring framework. You will be expected to collect high-quality human movement data during various activities and to develop an AI model that identifies these activities. You will be expected to continue your involvement in the CNAlab for the next academic year.

Requirements: Signal processing, microcontroller, computer programming, and related.

Website: https://people.njit.edu/profile/js439

PI Contact info: jongsang.son@njit.edu

 

Xin Di lab:

Functional brain imaging

Project: Understanding video contents using machine learning models and link them with brain activity. We are seeking undergraduate students interested in exploring the intersection of artificial intelligence and neuroscience. This project involves implementing advanced computer vision and audition models to analyze video data, extracting meaningful features, and comparing them to brain activity measured via functional Magnetic Resonance Imaging (fMRI). Our goal is to better understand how the human brain processes video content.

Requirements: Some experience in programming. Students from pre-med, biomedical engineering, electrical and computer engineering, computer science, or related fields are encouraged to apply

Website: https://people.njit.edu/profile/dixin

PI Contact info: xin.di@njit.edu;

 

Elisa Kallioniemi Lab:

Project: Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation method that can be used to study and modulate the brain. In this project, we investigate how AI can be utilized to optimize the location of TMS coils with respect to the participant's head.

Requirements: A basic understanding of computational coding is expected, along with an interest in neuroscience or neural engineering. The internship will be in person.

Website: https://people.njit.edu/profile/eak42

PI Contact info: elisa.kallioniemi@njit.edu

 

Alex Zhou Lab:

Biodynamics Lab

Project: AI-Powered Exoskeleton Control with Deep Learning for Personalized Mobility Assistance

Requirements: This project focuses on developing an innovative reinforcement learning-based approach to train neural network (NN) controllers for lower-limb exoskeletons, enabling personalized mobility assistance. Ideal candidates should have a background in deep learning and practical experience with Python, NumPy, and PyTorch/TensorFlow.

Website: https://people.njit.edu/profile/alexzhou

PI Contact info: alexzhou@njit.edu