Hi there! My name is Zihao GUO, or you can call me Eric. I'm currently a PhD student @ Institut Polytechnique de Paris under the supervision of Dr. Andrea ARALDO and Dr. Mounim EL YACOUBI. My research topic is preserving graph performance in an exogenously perturbed environment.
I love everything about statistics and optimization, and I’m excited to share my knowledge, passion, and tools with collaborators.
- Interdisciplinary collaborating across labs & industry
- Multilingual working across EN · FR · CN
Research
My research spans multiple threads focused on optimization under uncertainty, with an emphasis on large-scale decision-making in complex network systems.
- Formulating resilient optimization frameworks for vehicle routing and transport network design, prioritizing solution stability and service efficiency under multi-scale uncertainties.
- Advancing high-performance decomposition techniques, such as Column Generation, to tractably solve high-dimensional stochastic and combinatorial optimization problems.
- Integrating Deep Reinforcement Learning (DRL), Graph Neural Networks (GNNs), and Large Language Models (LLMs) to automate heuristic discovery and co-optimize real-time Learning-to-Optimize (L2O) pipelines for complex decision systems.
Publications
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Data Sampling-driven Adaptive Modification of Bus Routes Under Time-Varying Road Conditions [Link] Zihao Guo, Andrea Araldo, Mounîm A El Yacoubi The 19th Learning and Intelligent Optimization Conference, 2025 |
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Restoring Accessibility During Urban Rail Disruptions via Bus Network Redesign [Link] Zihao Guo, Andrea Araldo, Mounîm A El Yacoubi Transportation Research Board (TRB) 104th Annual Meeting, 2025 |
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Rate variation and recurrent sequence errors in pandemic-scale phylogenetics [Link] Nicola De Maio, Myrthe Willemsen, Zihao Guo, Abhratanu Saha, Martin Hunt, Nhan Ly-Trong, Bui Quang Minh, Zamin Iqbal, Nick Goldman Preprint |
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A Sinh–Cosh-Enhanced DBO Algorithm Applied to Global Optimization Problems [Link] Xiong Wang, Yaxin Wei, Zihao Guo, Jihong Wang, Hui Yu, Bin Hu Biomimetics |
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SA-CNN: Application to text categorization issues using simulated annealing-based convolutional neural network optimization [Link] Zihao Guo, Yueying Cao ACM EITCE 2022. |
Education
Institut Polytechnique de Paris
Pre-doc · 2023 — 2026
Research topic: Preserving graph performance in an exogenously perturbed environment.
Nantes Université
Master of Science degree · 2022 — 2023
Specialization in Mathematics and Applications.
Ecole centrale de Nantes
Engineer's degree - Generalist Engineer · 2021 — 2023
Focus on Applied Mathematics (Statistics & Data Science) and Research & Development.
Université de Picardie Jules Verne
Bachelor of Management · 2017 — 2021
Specialization in Optimization.
Industrial Experience
Algorithm Engineer 2025.8 — 2025.11
Internship
@ Huawei — Shanghai, CHINA
Data Engineer 2022.4 — 2022.9
Internship
@ IFP Energies nouvelles — Rueil-Malmaison, FRANCE
Genomics Algorithm Developer 2023.4 — 2023.9
Internship
@ European Bioinformatics Institute — Cambridge, UK
Data Analyst 2021.11 — 2022.1
Internship
@ Tencent — Beijing, China (Remote)
Teaching
MSc - Intelligence artificielle et données
Teaching Assistant @ ENSTA Paris — Palaiseau, FRANCE
Algorithm Engineer — Huawei
2025.8 — 2025.11 · Shanghai, CHINA
- Developed a point cloud-channel multimodal contrastive learning framework, aligning environment and channel modalities within a shared feature space.
- Proposed an integer-partition-based non-contiguous resource block allocation algorithm that extends the legacy RIV continuous allocation mechanism.
Data Engineer — IFP Energies nouvelles
2022.4 — 2022.9 · Rueil-Malmaison, FRANCE
- Analyzed badge validation data and built exploratory dashboards for the mobility analytics team.
- Benchmark validation counts against MATSim agent-based simulations to calibrate software accuracy and reduce discrepancies.
- Applied SARIMAX, NeuralProphet, and related time-series models to forecast corrected statistics and quantify external impacts.
Supervised by Dr. Pierre Michel.
Genomics Algorithm Developer — EMBL-EBI
2023.4 — 2023.9 · Cambridge, UK
Researched genetic evolutionary tools and simulated the evolution of genomes along large, short-branch phylogenetic trees to support pandemic-scale analyses.
Supervised by Dr. Nicola De Maio.
Data Analyst — Tencent
2021.11 — 2022.1 · Beijing, China (Remote)
Through deep mining of user churn data, built predictive models that estimated churn probability and guided recovery strategies for prioritized cohorts.
Supervised by Dr. Zhao Zhang.