Cyber-Physical Intelligence (CyPhy) Lab
The Cyber Physical Intelligence Lab aims to enable sensemaking through novel sensing applications that enhance the interpretation and understanding of complex, multi-source data. We use and develop state-of-the-art machine learning techniques to a wide range of real-world applications, including instrumented, smart environments, advanced driver assistance systems, collaborative robotics, and smart healthcare. We specialize in machine learning for sensory systems, with a strong focus on 1) Multimodal learning, 2) Generative models, and 3) Large language models, particularly LLM-based systems. Fundamentally, our lab aims to drive the convergence of the digital and physical worlds.
Current Research Projects
We are currently working on the most cutting edge tools in Machine Learning and IoT.
Self-Correcting LLMs
Having LLMs properly reason about images with minimal adjustments to the VLM.
NIH CAMERA Project
Creating a multimodal system for measuring brain-behavior relationships.
Smart Streetscapes
Using IoT alongside AI/Machine Learning to measure quality of life in cities across the nation.
Current Members
The CyPhy lab consists of PhD students, Masters students, and Undergraduates advised by Dr. Jorge Ortiz
Lab Director
Jorge Ortiz
Lab Director
Jorge received his BS in computer science from MIT in 2003 and MS, PhD in computer science from UC Berkeley in 2010 and 2013, respectively. Prior to joining Rutgers University, he was at IBM Research working on applications of machine learning to the internet of things. He also spent some time in startups, including a smart-buildings startup named Pangia and a local services startup named VRLocal. He was also an early employee and kernel contributor to Spire Global.
PhD Students
Sonya (Yuan) Sun
Research Interests: Computational Sensing, Smartspace IoT, Multimodality, Generative AI, Edge Computing , Smart City AGI
Research Interests: Deep Learning, Multimodal Learning, Computer Vision, Multimodal Large Language Models, Smart Cities
Research Interests: ML, HCI, Computational Sensing, Sensor Systems, Large Language Models, Socially Cognizant Robotics
Research Interests: Machine Learning, Computer Vision, Multimodal Learning
Research Interests: Multimodal Learning, Causal Inference, Computer Vision
Research Interests: Building's Digital Twin, Sensors, Large Language Models.
Undergraduate Students
Research Interests: Machine Learning, Internet-of-Things, Generative AI
Research Interests: Computer Science, Smartspace LLM, and LLM-VLM correction
Research Interests: AI, Multimodal Sensors, LLM Architecture, Cryptography
Research Interests: Machine Learning, IoT Applications, Robotics, Sensors, Data Manipulation/Analysis
Research Interests: AGI Development, LLMs, Optimization Methods in Deep Learning
Research Interests: Machine Learning, IoT, Multimodal Learning, Sensors, Signal Processing, LLMs
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