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Kumar Akash

7 accepted papers

2026

Strategic Shaping of Human Prosociality: A Latent-State POMDP Framework

RA-L 2026

We propose a decision-theoretic framework in which a robot strategically can shape inferred human's prosocial state during repeated interactions. Modeling the human's prosociality as a latent state that evolves over time, the robot learns to infer and influence this state through its own actions, in

Cited by 0SourceScholar
2025

Self-Supervised Learning-Based Multimodal Prediction on Prosocial Behavior Intentions

ICASSP 2025accepted

Human state detection and behavior prediction have seen significant advancements with the rise of machine learning and multimodal sensing technologies. However, predicting prosocial behavior intentions in mobility scenarios, such as helping others on the road, is an underexplored area. Current resea…

Cited by 0SourceScholar
2025

Toward Informed AV Decision-Making: Computational Model of Well-being and Trust in Mobility

IJCAI 2025

For future human-autonomous vehicle (AV) interactions to be effective and smooth, human-aware systems that analyze and align human needs with automation decisions are essential. Achieving this requires systems that account for human cognitive states. We present a novel computational model in the for

2024

Beyond Empirical Windowing: An Attention-Based Approach for Trust Prediction In Autonomous Vehicles

ICASSP 2024accepted

Humans’ internal states play a key role in human-machine interaction, leading to the rise of human state estimation as a prominent field. Compared to swift state changes such as surprise and irritation, modeling gradual states like trust and satisfaction are further challenged by label sparsity: lon…

Cited by 0SourceScholar
2022

Incorporating Gaze Behavior Using Joint Embedding With Scene Context for Driver Takeover Detection

ICASSP 2022accepted

Despite the recent advancement in driver assistance systems, most existing solutions and partial automation systems such as SAE Level 2 driving automation systems assume that the driver is in the loop; the human driver must continuously monitor the driving environment. Frequent transition of maneuve…

Cited by 0SourceScholar
2022

Learning Temporally and Semantically Consistent Unpaired Video-to-Video Translation through Pseudo-Supervision from Synthetic Optical Flow

AAAI 2022technical

Unpaired video-to-video translation aims to translate videos between a source and a target domain without the need of paired training data, making it more feasible for real applications. Unfortunately, the translated videos generally suffer from temporal and semantic inconsistency. To address this,…

2021

Improving Driver Situation Awareness Prediction using Human Visual Sensory and Memory Mechanism

IROS 2021poster

Situation awareness (SA) is generally considered as the perception, understanding, and projection of objects’ properties and positions. We believe if the system can sense drivers’ SA, it can appropriately provide warnings for objects that drivers are not aware of. To investigate drivers’ awareness,…

Cited by 27SourceScholar