• Harvard AI and Robotics Lab

    Welcome to Harvard AI and Robotics Lab. We aim to transform human wellbeing through the power of artificial intelligence and robotics through our passionate research.

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Image generation and editing

Our team develops image generation models enabling higher sample efficiency and generation fidelity alongside stronger semantic encoding. Furthermore, we develop image editing models that achieve stronger background preservation and more precise editing of target regions.

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World models for robotics

We aim to develop cutting-edge world models for robotics. A powerful world model that can accurately predict future observations is essential for bringing robotic devices to their own ChatGPT moment, because humans continuously anticipate future observations when performing everyday tasks.

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Large language model agents

LLM agents have proven effective in performing complex tasks across software engineering, scientific research, healthcare, education, finance, and robotics. A representative work from our group in this research area is our automated stock-trading agent, TrustTrade.

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Large language model behaviors

As a precursor to superhuman adaptive intelligence, or AGI, LLMs exhibit behaviors resembling human intelligence. Understanding these behaviors is critically important to ensure the reliable, safe, and effective use of LLMs. Our lab is actively studying a range of LLM behaviors.

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AI for video editing and 4D scene generation

Our team focuses on advancing text-to-video editing and text-to-4D generation technologies to enable more dynamic and immersive content creation. Our core projects explore how to achieve more precise text-to-video editing and stronger consistency in 3D/4D scene generation models.

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Large language model safety

Our team aims to identify and quantify potential safety issues in large language models such as inconsistency and privacy leakage, which will be mitigated by developing novel AI techniques to finetune standard large language models.

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Error bounds for AI models

AI research is both theoretical and computational. It is important to have a deep understanding of different AI models’ error bounds and associated factors. One of our recent studies is to analyze the impact of data distribution on fairness guarantees in equitable deep learning.

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AI-powered smart devices and robotics for low vision

AI-powered smart devices such as smart glasses and robotics have emerged as a promising way to assist people with low vision. We are developing multimodal AI models that are optimized for visually impaired individuals, which will be used with smart glasses and robotics.

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AI for genomics

The human genome can be viewed as the biological code that governs the development, organization, and function of the complex human body. Our lab is developing AI models that effectively leverage latent genomic features derived from genome foundation models to enhance genomic prediction, functional interpretation, biological discovery, and downstream clinical applications.

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AI for assessing 3D medical structures

Three-dimensional representation of anatomical and pathological structures is central to clinical practice, such as clinical diagnosis and treatment planning in CT and MRI. Recent image-to-3D foundation models offer brand new opportunities to enable fast and cost-effective 3D anatomical and pathological structure assessment.

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Equitable AI for disease screening

Our team is dedicated to developing equitable AI models for disease screening with a special focus on ocular diseases. Recently, we have developed a fair identity normalization technique to improve model performance equity.

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AI for medical data cleaning

Our team is dedicated to developing AI-based data cleaning technologies, aiming to provide cleaner data and enhance diagnostic outcomes for eye diseases.

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What We Do

Harvard AI and Robotics Lab strives to transform human wellbeing through the power of artificial intelligence and robotics with our passionate research. Our lab has broad interests spanning generative AI for computer vision, multimodal large language model behaviors and agents, AI for robotics, AI for genomics, and various other AI applications in medicine. We publish our research in leading AI conferences (CVPR, NeurIPS, and ICLR) and scientific journals. We are dedicated to promoting knowledge sharing and research collaborations.

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Media Report: AI Equity

In this video interview, Dr. Mengyu Wang discussed AI equity issues.

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MORE THAN 150
PUBLICATIONS
MORE THAN 5.5
MILLION USD GRANTS RECEIVED
MORE THAN 50
RESEARCH MEMBERS