Welcome to IDEAS Lab

Welcome to the interdisciplinary research lab, IDEAS (Intelligent Design for Empathetic and Augmented Systems) at Purdue Computer Science. Our research includes the design and implementation of scientific algorithms leveraging the “human in the loop” and their applications to robotics, computer graphics, AI, virtual environments, augmented intelligence, pedestrian and crowd dynamics, and medical / healthcare research.

Our research also focuses on building embodied computational models of human behaviors, and developing component algorithms of an intelligent agent (from sensing, to decision-making, to actuating). Our long-term research goal is to create engaging, socially intelligent agents that can interact with humans in innovative ways through expressive multi-modal interaction.

Some recent work includes combining these methods with machine learning, computer vision, and physically-based modeling for Multi-Agent Dynamics, Heterogenous Robotics, Autonomous Driving, Affective Computing and Virtual Reality. In addition to publishing papers at the leading venues, we have a long history of developing software packages and transitioning our technology into industrial products.

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21 Jun 2023
Three IDEAS papers were accepted at IROS 2023! With this, in 2023, IDEAS published a total of five papers in the top robotics venues (ICRA+IROS)!
30 May 2023
Prof. Bera awarded the Ross-Lynn Research Scholar Grant
13 Feb 2023
IDEAS research was covered in Purdue news
19 Jan 2023
IDEAS research was covered in NPR news
06 Jan 2023
Paper accepted at ICRA 2023 for EWareNet: Emotion Aware Human Intent Prediction and Adaptive Spatial Profile Fusion for Social Robot Navigation
06 Jan 2023
Paper accepted at ICRA 2023 for AZTR: Aerial Video Action Recognition with Auto Zoom and Temporal Reasoning
05 Nov 2022
Best Paper Award in ACM SIGGRAPH MIG 2022 for Learning Gait Emotions Using Affective and Deep Features
15 Sep 2022
Paper accepted at MIG 2022 (Learning Gait Emotions Using Affective and Deep Features)
20 Aug 2022
Paper accepted at WACV 2023 (Placing Human Animations into 3D Scenes by Learning Interaction- and Geometry-Driven Keyframes)
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