Project Overview

We are seeking one or more research engineers in computer science to join the “Towards an Immersive Workplace” project. This project is part of  Task “T1” of a five-year, ambitious research program on "Mens, Manus and Machina—How AI Empowers People, Institutions and Cities in Singapore (M3S)."

Successful applicants for this position will have the opportunity to work on cutting-edge research that builds new capabilities for AI-enhanced human-robot interaction, with a special focus on supporting efficient spatial/3D sensing and comprehension in industrial environments, such as airport tarmacs and logistics warehouses.  The end goal is to build exciting new capabilities that allow robots and humans to work together, interactively and in close proximity, such that the robotic actions are controlled by commands and queries that humans would issue naturally in untethered, field settings.

This research will specifically look at the integration of new sensing technologies, such as event-based vision sensors, to help augment or complement data generated by alternative sensors, such as LIDAR (3D) and RGB camera (2D) sensing.  The goal is to utilize such event-based sensors as energy-efficient, accurate indicators of key spatial changes in the environment, which in turn allows for more efficient, targeted use of additional sensing modalities (LIDAR, RGB camera) as well as optimization of the subsequent DNN-based sense-making pipeline.

Given the current state-of-the-art, the project will initially focus on tackling two novel challenges: (i) developing pre-processing techniques to integrate event-based vision sensors (aka neuromorphic sensors) into a more comprehensive spatial sensing pipeline, including LIDAR and RGD sensor streams, and (ii) developing systems-level neural network based optimization techniques that allow for efficient execution of AI-based spatial sense-making logic on edge devices. These techqniues will progressively be combined with additional research, being developed in complementary efforts within the overall T1 project, that tackles topics such as non-obtrusive human attention capture and efficient multi-modal DNN comprehension for human instructions.

The T1 team is led by distinguished scholars, including Profs. Sanjay Sarma, Daniela Rus and Jinhua Zhang from MIT; and Prof. Archan Misra from Singapore Management University. The proposed research described above will be spearheaded by Prof. Misra.

Job Description

• Conduct research and develop systems-level prototypes that focus on optimized sensing systems for spatial awareness that include emerging event-based vision platforms
• Publish research results in top-tier conferences and journals, with focus on venues associated with mobile/embedded systems, AI and multimedia.
• Collaborate with graduate and undergraduate students at MIT and in Singapore.
• Assist in grant writing, project management, and other administrative duties related to research activities.

Job Requirements

• Minimum Bachelor’s (and ideally Master’s or PhD-level Credentials) in Computer Science, including Mobile/Wearable Computing, Multimedia Systems and/or Artificial Intelligence and Machine Learning.
• Experience with edge-based optimization of DNN algorithms for RGB/video streams or SNN models for event-based sensor data streams is essential  
• Project-level experience with programming on edge platforms such as Jetson TX2/AGX is highly desired
• Strong publication record in top-tier ACM/IEEE conferences and journals.
• DESIRABLE: Demonstrated ability to conduct inter-disciplinary research with a systems focus.
• Excellent communication and collaboration skills.

This role is primarily based in Singapore and appointment is on contract, with the possibility of renewal and extension. To find out more about this role, please contact Professor Archan Misra  (archanm@smu.edu.sg). 

Interested applicants are invited to send in their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.