Kevin Lin

About

Kevin Lin is a faculty member in the Program in Applied Mathematics at the University of Arizona. His research interests include applied mathematics, specifically nonlinear dynamics, computational methods, nonequilibrium statistical physics, and mathematical biology. He is involved in various research groups related to applied mathematics, biomathematics, computational neuroscience, data assimilation, nonlinear dynamics, physics, statistical physics, and uncertainty quantification. His work focuses on advancing understanding and computational techniques within these areas, contributing to the broader field of applied mathematics and its interdisciplinary applications.

Research topics

• Biology
• Genetics
• Internal medicine
• Chemistry
• Medicine
• Cancer research
• Computer Science
• Artificial Intelligence
• Endocrinology
• Biochemistry

Selected publications

• PI3K/AKT/mTOR signaling transduction pathway and targeted therapies in cancer

  Molecular Cancer · 2023-08-18 · 1868 citations

  reviewOpen access

  The PI3K/AKT/mTOR (PAM) signaling pathway is a highly conserved signal transduction network in eukaryotic cells that promotes cell survival, cell growth, and cell cycle progression. Growth factor signalling to transcription factors in the PAM axis is highly regulated by multiple cross-interactions with several other signaling pathways, and dysregulation of signal transduction can predispose to cancer development. The PAM axis is the most frequently activated signaling pathway in human cancer and…

  PublisherOA PDFDOI

• End-to-End Human Pose and Mesh Reconstruction with Transformers

  2021-06-01 · 671 citations

  article1st author

  We present a new method, called MEsh TRansfOrmer (METRO), to reconstruct 3D human pose and mesh vertices from a single image. Our method uses a transformer encoder to jointly model vertex-vertex and vertex-joint interactions, and outputs 3D joint coordinates and mesh vertices simultaneously. Compared to existing techniques that regress pose and shape parameters, METRO does not rely on any parametric mesh models like SMPL, thus it can be easily extended to other objects such as hands. We further…

  PublisherDOI

• The Transformative Journey to Becoming a High-Reliability Organization (HRO)

  Physician leadership journal · 2025-08-26 · 1 citations

  article1st authorCorresponding

  Healthcare organizations increasingly aim to become high-reliability organizations (HROs) to ensure patient safety and enhance care quality. Becoming an HRO requires more than operational changes; it necessitates a cultural transformation prioritizing safety and continuous improvement. This review outlines the tactics our organization employed to achieve HRO status, focusing on leadership engagement, safety culture, process improvement strategies, and measurement of progress using a newly create…

  PublisherDOI

• Cardiorenal Syndrome Type 1 Complicated by Uremic Pericarditis and a Small Pericardial Effusion Causing Cardiac Tamponade

  Cureus · 2026-04-23

  articleOpen access

  Cardiac tamponade is typically associated with large pericardial effusions; however, even small effusions can result in significant hemodynamic compromise, particularly in the setting of rapid fluid accumulation and underlying cardiac pathology. This case highlights the diagnostic challenge of identifying low-volume tamponade in a patient with elevated baseline intracardiac pressures. An elderly man was admitted for acute heart failure complicated by cardiorenal syndrome. Following initial diure…

  PublisherOA PDFDOI

• TechImage-Bench: Rubric-Based Evaluation for Technical Image Generation

  ArXiv.org · 2025-12-13

  preprintOpen access

  We study technical image generation, where a model must synthesize information-dense, scientifically precise illustrations from detailed descriptions rather than merely produce visually plausible pictures. To quantify the progress, we introduce TechImage-Bench, a rubric-based benchmark that targets biology schematics, engineering/patent drawings, and general technical illustrations. For 654 figures collected from real textbooks and technical reports, we construct detailed image instructions and…

  PublisherOA PDFDOI

Recent grants

• Computational Nonlinear Dynamics: Variance Reduction Methods and Numerical Studies of Large, Chaotic, and Noisy Systems

  NSF · $220k · 2014–2018

• CDS&E-MSS: Predictive Modeling and Data-Driven Closure of Chaotic and Noisy Dynamics in Discrete Time

  NSF · $200k · 2018–2023

• Computational Analysis of Large Dynamical Systems

  NSF · $249k · 2009–2013

Frequent coauthors

• K. Leigh Greathouse

  Baylor University

  92 shared

• Tia Berry

  92 shared

• Tiffany Bredfeldt

  92 shared

• Kurunthachalam Kannan

  91 shared

• Megan L. Mittelstadt

  91 shared

• Jeffrey I. Everitt

  Duke University

  91 shared

• Shuk‐Mei Ho

  University of Arkansas for Medical Sciences

  91 shared

• Thomas C. Harding

  88 shared

Labs

• Program in Applied MathematicsPI

Similar researchers at University of Arizona

• Kristopher Kleinh-40
• Joanna Maselh-35
• Laura Condonh-35