Research Fellow, School of Computing

Imagine a situated AI assistant residing in smart glasses worn by the human and collaborating on a maker project, e.g., building an Arduino smart lamp. It communicates with the human through natural language to understand human goals and preferences. It collaborates with the human to develop and execute the solution. It sees what the human sees from a first-person view to understand human actions and offer useful tips. It connects with other AI assistants to scale up to complex tasks requiring a team solution. The AI assistant becomes the “other me”, an external, but situated extension of our individual mind and senses. In future, every human will have AI assistance for daily life and work. 

We propose an integrative program of fundamental research towards this vision. Our overall aim is to build conceptual understanding of human-AI collaboration, algorithmic foundations and tools for situated assistance, and an experimental device platform for integration and evaluation. The research program consists of five thrusts, one of which is on human collaboration models 

This thrust studies the essential elements that sustain human collaboration with AI assistants: intent, goal alignment, transactive memory, action plans, task coordination, trust, affect, and conflict resolution. We will build models that support effective collaboration between humans and AI assistants: specifically, (i) representations of intent, goals, tasks, and the transactive memory for members in a team or dyad to collectively encode, store, and retrieve task knowledge; (ii) model-driven communication protocols that enable the AI assistant to infer human intent and goals and to build shared representation of action plans, for task coordination and execution; and (iii) human emotions/affect sensing for conflict resolution, trust building, and cooperation. 

The Research Fellow will be a part of the above thrust. He/she will be responsible for undertaking in-depth research and innovation in human-AI collaboration that lead to real-world applications as well as publishing the work in top-tier international conferences and journals. He/she will be working closely with the Principal Investigator and with collaborators on interesting and challenging problems in this focal area. 

• PhD degree in a relevant discipline 
• Research areas related to AI, collaboration in domains such as customer service, healthcare 
• Machine learning 
• Econometric analyses – desirable, but not essential 
• Writing research papers in English 
• Good communication and teamwork skills 

Location: Kent Ridge Campus

Organization: School of Computing

Department : Department of Information Systems And Analytics

Employee Referral Eligible: No

Job requisition ID : 24626