Linlin Jia
— Ph.D. in Machine Learning
Research Scientist · Postdoc University of Bern, Switzerland
- SNSF + Innosuisse + ANR funded 8+ projects / grants delivered
- Authored graphkit-learn + LIULIAN 9 papers · 130+ citations
today's research
Learning
Learning
Learning
Science & Industry
& Agents
can graphs + LLM agents do real science or industry work?
open to opportunitiesAbout Me
Building graph representation learning across domains: open-source tools, models, and AI systems for research & industry.
graphkit-learn · liulian · redoxprediction
Selected Publications
130+ citations · Google Scholar
Bridging graph and kernel spaces: a pre-image perspective
Graph kernels, graph edit distances, and pre-image algorithms and applications. Supervised by Prof. Paul Honeine and Prof. Benoit Gaüzère.
Research Outline
Graph Machine Learning
Bridging graph kernels, edit distances, GNNs, transformers. Pre-image and generation problems.
Spatio-Temporal Learning
Time series with entity embeddings, spatial graphs for environmental forecasting.
Graph AI for science and industry
Molecular property prediction (foundations for drug discovery), computational chemistry, smart engineering, hydrology, digital humanities, finance, healthcare.
LLM Systems & Agents
RAG pipelines, fine-tuning (LoRA), agent orchestration for production AI.
Professional Experience
Postdoctoral Researcher
SNSF-funded research on spatio-temporal graph convolutional networks and LLMs for Swiss river temperature forecasting. Developing transformer architectures with entity embeddings and graph structures. Paper accepted by ICPR 2026.
AI Lead (Industry Collaboration)
Led the AI strategy and the architecture and development of an LLM-agent system (chatbot, AI Studio proof-of-concept, and a data-fusion-platform design) for the neobank research center, with The Hong Kong Polytechnic University. Demonstrated at InnoEX 2026.
Scientific Collaborator
Applied topology-aware graph and vision deep learning for symbol detection, connection prediction, and graph construction in engineering diagrams and handwritten document analysis. Contributed to SNSF-funded Virtual Bodmer project (accepted) for 3D digital reconstruction of ancient papyrus.
Research Fellow
SNSF-funded research on novel graph matching algorithms. Published at ACPR 2023 on bridging distinct spaces in graph-based machine learning.
Postdoctoral Researcher
Applied graph ML to polymer optimization (OCTOPUSSY project) and redox potential prediction. Published in Journal of Computational Chemistry (2024).
Innosuisse Entrepreneurship Training: Business Concept (Module 2)
Ten-evening programme (October to December 2025) on founding and growing a start-up: idea development, team building, financial planning and fundraising, IP protection, the start-up ecosystem, and pitching own projects.
Ph.D. in Computer Science
Thesis: "Bridging graph and kernel spaces: a pre-image perspective": Graph kernels, graph edit distances, and pre-image problems.
M.Sc. in Software Engineering
Service-oriented programmable control for Software-Defined Networks; applied extreme learning machine (ELM) to network mobility prediction. Resulted in 1 China patent (CN106376041B).
B.S. in Information Engineering
Foundations in signal processing, networks, and software engineering.
Invited Talks & Presentations
From Dialogue Box to Agent: A Researcher's Path with AI Tools
How Graphs Understand the World: Unified Modelling across Hydrology, Digital Humanities, and Chemistry
Bridging Graph Spaces: Novel Algorithms and Their Applications
Bridging Distinct Spaces in Graph-based Machine Learning
A Graph Pre-image Method Based on Graph Edit Distances
Skills & Technologies
Selected Awards & Grants
UniBE ECSC Open Round 2023/2
Early Career Scientist Cooperation. Applicant & Principal Investigator. Predicting molecular energies with multiscale graph ML built on Interacting Quantum Atoms (IQA) and GNNs.
ANR Grant (PhD project APi)
PhD thesis funding (LITIS, INSA Rouen), project Apprivoiser la Pré-image: graph kernels & ML for structured data.
Academic Services
Supervision
- 20+ students mentored
- Topics: Computer vision, Graph-based learning, Smart engineering, Deep learning, LLMs, Agent systems
- Ran the technical recruitment panel: 20+ candidates interviewed
Associations
- Member of the Swiss Association for Pattern Recognition (SAPR) (2024-)
- Member of the Marie Curie Alumni Association China Chapter (2024)
- Associated member of the LITIS lab (2022)
Reviewing
- International Conference on Pattern Recognition 2024
News & Updates
Contact
Location
🇨🇭 University of Bern · Pattern Recognition Group
Schützenmattstrasse 14, 3012 Bern, Switzerland
Phone
🇨🇭 +41 78 224 1419 (Switzerland)
🇨🇳 +86 <please-add> (China)
Visitors
— total visits — countries past 3 days via Microsoft Clarity