Open to PhD positions · Spring/Summer 2027

Hello, I’m Yang Song (宋扬).

MSc student, University of Copenhagen Copenhagen, Denmark

I develop Bayesian and agentic AI methods for scientific and biomedical problems.

I study IT and Cognition at the University of Copenhagen. My work spans Bayesian machine learning, AI agents, foundation models, and healthcare data science.

Bayesian ML AI Agents Foundation Models AI for Science Healthcare AI
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Portrait of Yang Song
Photo taken at ICML 2026.

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Research output

Featured research

Framework overview of iLoRA

ICML 2026

iLoRA: Bayesian Low-Rank Adaptation with Latent Interaction Graphs for Microbiome Diagnosis

Yang Song, Yixuan Zhang, Lingfa Meng, Tongyuan Hu, Haizhou Shi, Hao Wang, Samir Bhatt, and Hengguan Huang.

Bayesian graph-conditioned LoRA for jointly learning diagnostic predictions, latent interaction structures, and calibrated uncertainty.

arXiv:2605.30179
Method overview of Subset Lattice Distillation

Preprint · 2026

Evidence Acquisition and Stopping via Lattice Distillation

Yixuan Zhang, Yang Song, Jiayi Zhang, Jingqi Sun, Hao Wang, Samir Bhatt, and Hengguan Huang.

Subset Lattice Distillation: planning cost-aware query/stop decisions over evidence-subset lattices and distilling them into an online controller, evaluated on influenza monitoring.

arXiv:2606.09433

02

Background

Education & experience

May 2026 — Present

Data Scientist

Deep Delved · Denmark

Working with Lingfa Meng on battery energy storage system (BESS) benchmarking and automated reporting.

Jun 2026 — Aug 2026

Research Assistant

School of Data Science, The Chinese University of Hong Kong, Shenzhen · Full-time

Supervised by Asst. Prof. Zhongxiang Dai.

2024 — Present

MSc in IT and Cognition

University of Copenhagen · Denmark

Working on Phylo-anything: Universal Phylogenetic Inference with Foundation Models, co-supervised by Prof. Anders Krogh and Asst. Prof. Hengguan Huang.

2019 — 2023

BSc(Eng) in Internet of Things Engineering

Queen Mary University of London & Beijing University of Posts and Telecommunications

Joint programme. My undergraduate thesis, Real-time Behaviour Anomaly Detection for Industrial Robot Arms on Edge Computing, was supervised by Prof. Jonathan Loo.

2022 — 2023

Early industry experience

AI healthcare · Cloud infrastructure · Medical imaging

Worked across product, data, and back-end engineering roles, contributing to healthcare AI products, IoT infrastructure, and medical image annotation systems.

03

Recognition

Awards & service

2026

Danish Data Science Academy (DDSA) Travel Grants

Awarded funding to attend ICML 2026.

2026

Reviewer

ICLR 2027 · ACL Rolling Review (ARR)

Let’s connect

Research, collaboration, or PhD opportunities.

I am especially interested in PhD opportunities beginning in Spring or Summer 2027.