Kevin Han

According to our database, Kevin Han authored at least 14 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

DistMLIP: A Distributed Inference Platform for Machine Learning Interatomic Potentials.

Kevin Han, Bowen Deng, Amir Barati Farimani, Gerbrand Ceder

CoRR, June, 2025

Segmenting Objectiveness and Task-awareness Unknown Region for Autonomous Driving.

Mi Zheng, Guanglei Yang, Zitong Huang, Zhenhua Guo, Kevin Han, Wangmeng Zuo

CoRR, April, 2025

A vision-based weigh-in-motion approach for vehicle load tracking and identification.

Phat Tai Lam, Jaehyuk Lee, Yunwoo Lee, Xuan Tinh Nguyen, Van Vy, Kevin Han, Hyungchul Yoon

Comput. Aided Civ. Infrastructure Eng., April, 2025

Automating Mathematical Proof Generation Using Large Language Model Agents and Knowledge Graphs.

Vincent Li, Yule Fu, Tim Knappe, Kevin Han, Kevin Zhu

CoRR, March, 2025

Pragmatic Metacognitive Prompting Improves LLM Performance on Sarcasm Detection.

Joshua Lee, Wyatt Fong, Alexander Le, Sur Shah, Kevin Han, Kevin Zhu

Proceedings of the 31st International Conference on Computational Linguistics, 2025

2024

Pegasus-v1 Technical Report.

Raehyuk Jung, Hyojun Go, Jaehyuk Yi, Jiho Jang, Daniel Kim, Jay Suh, Aiden Seung Joon Lee, Cooper Han, Jae Lee, Jeff Kim, Jin-Young Kim, Junwan Kim, Kyle Park, Lucas Lee, Mars Ha, Minjoon Seo, Abraham Jo, Ed Park, Hassan Kianinejad, Sj Kim, Tony Moon, Wade Jeong, Andrei Popescu, Esther Kim, EK Yoon, Genie Heo, Henry Choi, Jenna Kang, Kevin Han, Noah Seo, Sunny Nguyen, Ryan Won, Yeonhoo Park, Anthony Giuliani, Dave Chung, Hans Yoon, James Le, Jenny Ahn, June Lee, Maninder Saini, Meredith Sanders, Soyoung Lee, Sue Kim, Travis Couture

CoRR, 2024

2023

CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling.

Bowen Deng, Peichen Zhong, KyuJung Jun, Janosh Riebesell, Kevin Han, Christopher J. Bartel, Gerbrand Ceder

Nat. Mac. Intell., September, 2023

Algorithm and hardware co-design co-optimization framework for LSTM accelerator using quantized fully decomposed tensor train.

Mingshuo Liu, Miao Yin, Kevin Han, Ronald F. DeMara, Bo Yuan, Yu Bai

Internet Things, July, 2023

CHGNet: Pretrained universal neural network potential for charge-informed atomistic modeling.

Bowen Deng, Peichen Zhong, KyuJung Jun, Kevin Han, Christopher J. Bartel, Gerbrand Ceder

CoRR, 2023

RAVIC: Runtime Analysis Visualizer for Introductory Courses.

Georgiana Haldeman, Emma Pizer, Mathelide Hou, Matthew Rojas, Kevin Han, Ahmed Kamran

Proceedings of the 54th ACM Technical Symposium on Computer Science Education, Volume 2, 2023

Detecting Interference in Online Controlled Experiments with Increasing Allocation.

Kevin Han, Shuangning Li, Jialiang Mao, Han Wu

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022

Hardware Oriented Strip-wise Optimization (HOSO) Framework for Efficient Deep Neural Network.

Xiaotian Ma, Kevin Han, Yucheng Yang, Ronald F. DeMara, Yu Bai

Proceedings of the 35th IEEE International System-on-Chip Conference, 2022

2021

An Efficient Video Prediction Recurrent Network using Focal Loss and Decomposed Tensor Train for Imbalance Dataset.

Mingshuo Liu, Kevin Han, Shiyi Luo, Mingze Pan, Mousam Hossain, Bo Yuan, Ronald F. DeMara, Yu Bai

Proceedings of the GLSVLSI '21: Great Lakes Symposium on VLSI 2021, 2021

An Efficient Real-Time Object Detection Framework on Resource-Constricted Hardware Devices via Software and Hardware Co-design.

Mingshuo Liu, Shiyi Luo, Kevin Han, Bo Yuan, Ronald F. DeMara, Yu Bai

Proceedings of the 32nd IEEE International Conference on Application-specific Systems, 2021