Meet ApplyKite Twin, the application assistant that learns with you

Meet your Twin, it learns with you

Your Twin learns with you

Launch week codes:30% off annual Pro20% off monthly Pro

Ends in00h00m00s

Yin Li

Associate Professor

University of Wisconsin-Madison

United States

Research Interests

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Explore related searches

Professors in United States Professors in Medical Imaging Medical Imaging professors in United States

About

Yin Li is an Assistant Professor at the University of Wisconsin-Madison, USA. His research primarily focuses on deep learning applications in medical imaging, computer vision, and high-speed imaging technologies. Recent articles highlight his work in deep non-line-of-sight reconstruction, neonatal intubation techniques, and energy-efficient video streaming solutions.

Articles (15)

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Collaborators (5)

Andreas Velten

Associate Proffessor

University of Wisconsin-Madison

UNITED STATES

View details

Tomy Varghese

Professor

University of Wisconsin-Madison

UNITED STATES

View details

Ji Hyun Nam

Assistant Professor

Inha University

SOUTH KOREA

View details

Robert Radwin

University of Wisconsin-Madison

UNITED STATES

View details

Miao Liu

Assistant Professor

Tsinghua University

CHINA

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Yin Li

Research Interests

Make your next move.

Explore related searches

About

Articles (15)

Geometry aware neural radiance fields for freehand ultrasound reconstruction

ApproxBit: Efficient Video Analytics through Latency-Aware Offloading with Learned Binary Codes

Deep learning to assess laryngoscope insertion depth during neonatal intubation with video laryngoscopy

Look Less, Think Faster: Joint Token-Compute Adaptation for Multimodal LLMs

Glottic opening detection using deep learning for neonatal intubation with video laryngoscopy

A Single-Camera Method for Estimating Lift Asymmetry Angles Using Deep Learning Computer Vision Algorithms

Agile3D: Adaptive Contention- and Content-Aware 3D Object Detection for Embedded GPUs

RICA$$^2$$: Rubric-Informed, Calibrated Assessment of Actions

Physics to the Rescue: Deep Non-Line-of-Sight Reconstruction for High-Speed Imaging

Sensorless End-to-End Freehand Three-dimensional Ultrasound Reconstruction with Physics Guided Deep Learning

Deep learning to quantify care manipulation activities in neonatal intensive care units

Physics to the Rescue: Deep Non-Line-of-Sight Reconstruction for High-Speed Imaging

In the Eye of the Beholder: Gaze and Actions in First Person Video

Virtuoso : Energy- and Latency-aware Streamlining of Streaming Videos on Systems-on-Chips

Weakly supervised foreground learning for weakly supervised localization and detection

Collaborators (5)

Andreas Velten

Tomy Varghese

Ji Hyun Nam

Robert Radwin

Miao Liu

Make your next move.