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AI Research

To seed high quality research efforts aimed at developing fundamental AI novel techniques, algorithms and adjacent technologies that will eventually significantly contribute to the other pillars of AI Singapore. Additionally, the AI Singapore Research Programme encourage national research collaborations and nurture local AI talents.

Important Questions

What are the gaps in current AI technology?

What are the new AI advances with positive economic and societal impacts?

How can we use AI safely and securely?

How do we design AI to align to ethical, legal and societal principles?

Targeted Capability Building in AI Research

Third Call for AI Research Proposal

The AI Research Grant Call 2020 will comprise two application stages:

Stage One - Whitepaper Stage

Whitepapers, also known as Letter-of-Intent (LOI), are submitted for potential development into Full Proposals (FP).

Stage Two – Full Proposal Stage

Shortlisted whitepapers will be informed by the AI research team to develop into a FP. Selected FP are required to present their ideas to AISG’s appointed International Evaluation Panel for a thorough assessment before awarding..

AI Singapore invites proposals in advanced fundamental AI research for the following themes:

1.1 Theme One: AI for Collaborative Decision Making

This theme centres on advancing the state of the art in collaborative AI and the following are the three areas of interest:

  1. Human Modelling for Collaboration – Intentions; Goals; and Behaviours
  2. Complex Decision Making Under Uncertainty
  3. Communications and Interaction – Collaboration with Sparse Information/Communication; Group Decision Making with Self Interested Agents or by Aggregated Opinions

1.2 Theme Two: Trustworthy and Explainable AI

This theme centres on advancing the state of the art in trustworthy or explainable AI and the following are the three areas of interest:

  1. Safe, Fair and Robust AI System Development
  2. Transparent or Explainable AI System Development
  3. Explainability and Trust (Safe, Fair, Robust) Assessment

1.3 Theme Three: AI for Design and Discovery

This theme centres on advancing the state of the art in resource efficient AI and the following are the four areas of interest:

  1. AI Understanding of Design and Creation
  2. Human AI Co-Design
  3. Knowledge Representation with Complex Priors or Measurements
  4. Science-Inspired or Physics-Based AI Systems and Models

The proposals may include, but not limited to, the proposed sub-topics areas.

Each proposal should address one of the three themes listed above. Alternative themes and proposals with multiple themes will not be considered for evaluation. Hence, we highly encourage proposals to have a clear research focus of a single theme.

AI Kickstarter Grant Call 2019

Deep Generative Modelling of Epigenomics Data

MILE SIKIC (A*STAR)

ESCAI: Efficient and Secure Collaborative AI

REZA SHOKRI (NUS)

InnoBrain for Artificial Creativity

JIANXI LUO (SUTD)

Reflective Intelligence Amplification: Tackling Wicked Problems Through Dynamic Search Space Exploration

PATRICK JANSSEN (NUS)

Grant Call 2019

Assistive AI with Artificial Theories of Mind and Body

Harold Soh Soon Hong (NUS)

Explaining AI with the Right Level of Abstraction

Jun Sun (SMU)

Learning To Anticipate Human Actions That Happen In The Next One To Five Seconds Using Self-Regularised Future Content Generation For Human-Robotic Engagement

Basura Fernando (A*STAR)

New Directions in Adversarial Machine Learning: From Theory to Applications

Bo An (NTU)

Noisy distributed learning on noisy data: A unified mathematical framework for dealing with arbitrary noise

Ernest Chong Kai Fong (SUTD)

Towards Improved Grammatical Error Correction

Ng Hwee Tou (NUS)

Grant Call 2018

Advancing Dense Prediction Methods for Visual Scene Understanding

Lin Guosheng (NTU)

Conversational Question Answering

Ng Hwee Tou (NUS)

Embedding Knowledge into Learning

Lee Wee Sun (NUS)

Targeting High Productivity Workforces via Data-Centric Transfer Optimization in the Internet Era

Ong Yew-Soon (NTU)

Enabling Spiking Neuromorphic Computation with On‐Board Learning Through Algorithm and Hardware Co‐design

Shaowei Lin (SUTD)

Rationalizing Deep Learning Model Decisions

Wynne Hsu (NUS)

PAT-AI: Privacy-Aware Transparency for AI in Singapore

Yair Zick (NUS)

One-Shot Learning: A Crucial Learning Paradigm Towards Human-like Learning

Fang Yuan (SMU)

Scaling Discrete Integration via SAT and CSP

Kuldeep S. Meel (NUS)

AI Research Grant Call 2020 is now closed.

Call for AI Kickstarter Proposal

Stage One - Whitepaper Stage

Whitepapers, also known as Letter-of-Intent (LOI), are submitted for potential development into Full Proposals (FP).

Stage Two – Full Proposal Stage

Shorlisted whitepapers will be informed by the AI research team to develop into a FP. Selected FP will require to present their ideas to AISG appointed International Evaluation Panel for a thorough assessment before awarding.

The AI Kickstarter Grant Call provides a platform for AI researchers in Singapore to explore innovative ideas which have the potential to be developed into full proposals for large-quantum grant calls. It aims to fund multi-disciplinary applications, reflecting novel ideas and visions that are under explored and/or have significant social impacts.

There is no restriction on topics. However, researchers may consider these suggested areas:

  • Collaborative AI
  • Life Long Learning AI
  • Privacy-Aware AI
  • Resource Efficient AI
  • Trustworthy AI

Proposals should emphasise novel and significant contributions in methodologies and algorithms rather than domain-specific solutions.

The funding support (inclusive of 20% IRC) is up to $100,000 per proposal, for a maximum of 1-year.

Note: If your application for the grant is successful, you are expected to submit your application to the NRF Competitive Research Programme (CRP) / MOE AcRF Tier 3 and its equivalent grant calls. Otherwise, a report detailing why the initial proposed approach is not feasible, is required.

AI Kickstarter Grant Call is now closed.

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