Taiyi Wang

Taiyi Wang

Phd Student in Computer Science, Co-Founder of Powersense.Ltd

Teaching

Artificial Intelligence-Supervision

Part IB, University of Cambridge, Computer Lab, 2023

The aim of this course is to provide an introduction to some fundamental issues and algorithms in artificial intelligence (AI). The course approaches AI from an algorithmic, computer science-centric perspective; relatively little reference is made to the complementary perspectives developed within psychology, neuroscience or elsewhere. The course aims to provide some fundamental tools and algorithms required to produce AI systems able to exhibit limited human-like abilities, particularly in the form of problem solving by search, game-playing, representing and reasoning with knowledge, planning, and learning.

R244: Large-Scale Data Processing and Optimisation-Demonstration

Part III or MPhil, University of Cambridge, Computer Lab, 2022

This module provides an introduction to large-scale data processing, optimisation, and the impact on computer system’s architecture. Large-scale distributed applications with high volume data processing such as training of machine learning will grow ever more in importance. Supporting the design and implementation of robust, secure, and heterogeneous large-scale distributed systems is essential. To deal with distributed systems with a large and complex parameter space, tuning and optimising computer systems is becoming an important and complex task, which also deals with the characteristics of input data and algorithms used in the applications. Algorithm designers are often unaware of the constraints imposed by systems and the best way to consider these when designing algorithms with massive volume of data. On the other hand, computer systems often miss advances in algorithm design that can be used to cut down processing time and scale up systems in terms of the size of the problem they can address. Integrating machine learning approaches (e.g. Bayesian Optimisation, Reinforcement Learning) for system optimisation will also be explored in this course.