Lecturer
- About
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- Email Address
- yongchao.huang@abdn.ac.uk
- School/Department
- School of Natural and Computing Sciences
Biography
2013-2017, DPhil Engineering Science (Oxford)
2016-2017, MLRG (Oxford), Bayesian/Markovian
2017-2019, Senior Data Scientist in Actuarial industry (UK), machine learning/data science
2019-2022, Postdoc in CS (Oxford), machine learning/reinforcement learning/Gaussian process
2022-, Visiting lecturer in CS (Westminster), student supervision
2022-2023, Senior Research Associate in MLG/CBL (Cambridge), probabilistic machine learning
2023-2024, collaborator, MLG/CBL (Cambridge)
2024-2025, early career academics panel, CSIC Engineering department (Cambridge)
2023-, Lecturer/Assistant Professor in CS (Aberdeen), machine learning
External Memberships
Service to community:
1. PC member, ECAI 2024
2. Organisor committee, Bioinference 2024
3. Guest editor, Journal of Theoretical Biology
Others: Chartered Management Institute (Level 5, 2019), Royal Statistical Society (RSS), International Linear Algebra Society (ILAS), Sr. Scientific Advisor to UK firm, etc.
- Research
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Research Overview
Broadly classic and modern approaches, theories and applications. Typically,
- Physics-motivated machine learning, science for AI
- Bayesian, MCMC, variational inference
- Generative modelling
- DL, RL, dynamical systems (differential equations - applied maths)
- Interdisciplinary & AI for science. e.g. vision, biology, mechanics, engineering materials/structures, energy, environment, climate, finance, etc.
Empirical work involves theoretical and practical elements. Having worked in both academia and industry, and learning from great minds, I am fortunate to be able to read, write, derive, code and assess, through years of practice. For over a decade, I have been doing reading, writing and coding on a daily basis.
A large portion of my work centers around log p(x) and its gradients, i.e. how to effectively infer a density and/or efficiently sample it. These trigger some relevant topics related to maths, statistics, computation, and cross boarders.
Research Areas
Accepting PhDs
I am currently accepting PhDs in Computing Science.
Please get in touch if you would like to discuss your research ideas further.
Computing Science
Accepting PhDsKnowledge Exchange
Welcome academia/industry collaborations, knowledge exchange and public engagement.
Supervision
As of 2024, I have independently supervised 57 UK Msc students theses on ML, data science and business analytics.
- Accepting curiosity-driven PhDs for all time entries.
- Open to supervise seasonal (e.g. final year/MPhil/summer/visiting) research projects within topics of mutual interest.
- Research-focused projects may involve mathematical, statistical analysis, computational methods, and/or standard software development practice. Training and supervision can be provided within my expertise and networks.
- I hope students can enjoy maximum flexibility and freedom to explore their interests, balance work and life, and most importantly, be happy and have fun.
Interested candidates please feel free to get in touch. Please specify specific interests and potential funding sources. Apologize I am unable to answer testing, phishing, and send-to-all emails.
- Teaching
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Teaching Responsibilities
Having taught following courses in the past:
1. Lectures: <Introduction to Software Engineering>, Aberdeen, 2023 & 2024
2. Lectures: <Software Process and Management>, Aberdeen, 2024
3. Lectures: <Computational Intelligence>, Aberdeen, 2024
3. Practicals: <3f8: Inference>, Cambridge, 2023
Others: Linear Algebra, ML, Engineering Maths (summer schools)