Hi there! My name is Zihao GUO, or you can call me Eric. I'm currently a PhD student at SAMOVAR research lab of Institut Polytechnique de Paris(IPP) 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.