Simon Lacasse

About

Simon Lacasse is a researcher at the intersection of human-computer interaction, robotics, and applied machine learning, with a focus on automating user experience (UX) evaluation and touchscreen interaction. His most cited work introduces a scalable automated system for measuring UX on smart devices—including TVs, tablets, and phones—by combining a robotic arm with onboard sensors to simulate human touches and clicks. This contribution addresses a critical bottleneck in UX testing, enabling repeatable, high-throughput assessments without human intervention. Lacasse also advances the field of robotic vision with a deep neural network designed to detect keyboard regions and recognize isolated characters from camera images, a key enabler for robots that need to auto-type on touchscreens. Though his citation counts are early-stage (4 and 2 respectively), these papers signal foundational work in automating device interaction. His research holds promise for streamlining quality assurance in consumer electronics and enhancing robotic autonomy in real-world interfaces, making him a notable emerging voice in automated UX and robotic perception.

Research Focus

Key Achievements

Top Papers

1. 1
   A Scalable Automated System to Measure User Experience on Smart Devices

   4 citations · 2019
2. 2
   A Deep Neural Network to Detect Keyboard Regions and Recognize Isolated Characters

   2 citations · 2019

Key Collaborators

Contact & Links