AIMLSystems is a brand new conference targeting research in the intersection of AI/ML techniques and systems engineering. Through this conference we plan to bring out and highlight the natural connections with these two fields. Specifically we explore how immense strides in AI/ML techniques are made possible through computational systems research (e.g., improvements in CPU/GPU architectures, data-intensive infrastructure, communications etc.), how the use of AI/ML can help in the continuous and workload-driven design space exploration of computational systems (e.g., self-tuning databases, learning compiler optimizers, learnable network systems etc.) and, the use of AI/ML in the design of socio-economic systems such as public healthcare, and security. The goal is to bring together these diverse communities and elicit connections between them.

Topics of Interest

The areas of interest are broadly categorized into the following three streams:

    Systems for AI/ML, including but not limited to:
        CPU/GPU architectures for AI/ML
        Embedded hardware for AI/ML workloads
        Data intensive systems for efficient and distributed training
        Challenges in production deployment of ML systems
        Efficient model training, optimization and inference
        Hardware efficient ML methods
        Resource-constrained ML
    AI/ML for Systems, including but not limited to:
        AI/ML for VLSI and architecture design
        AI/ML in compiler optimization
        AI/ML in data management - including database optimizations, virtualization, etc.
        AI/ML for networks - design of networks, load modeling, etc.
        AI/ML for power management - green computing, power models, etc.
    Applications of AI/ML in Socio-Economic Systems Design, which includes, but not limited to:
        Computational design and analysis of socio-economic systems
        Fair and bias-free systems for social welfare, business platforms
        Applications of AI/ML in the design, short-/long-term analysis of cyber-physical systems
        Mechanism design for socio-economic systems
        Applications of AI/ML in financial systems