Home · Projects · Publications · Contact

---

Curriculum Vitae

Last updated: April 2026 — Download PDF Version

---

Education

M.Sc. Computer Engineering Oct 2022 – Apr 2026
Università degli Studi di Padova, Italy

• GPA: 103/110
• Thesis: Graph-meta: Improving Metagenomic Classification with Graph-based Learning
• Advisor: Dr. Matteo Comin

B.Sc. Computer Engineering Oct 2018 – Sep 2022
Imam Khomeini International University, Iran

• GPA: 18.45/20 (3.9/4.0)
• Final Project: Stock Market Prediction
• Advisor: Dr. Nastooh Taheri Javan
• Ranked 1st in the Class of 2018 · Awarded Exceptional Talent

---

Research Experience

Graduate Researcher (Master’s Thesis) Mar 2025 – Apr 2026
Università degli Studi di Padova, Italy
Supervisor: Dr. Matteo Comin

• Developed a hybrid Deep Learning + GNN architecture for metagenomic sequence classification.
• Built an end-to-end bioinformatics pipeline: genome curation, read simulation, and graph dataset generation.
• Optimized GNN hyperparameters for large-scale biological graphs.
• Validated on real-world multi-omic benchmarks.

---

Teaching Experience

Junior Tutor — Foundation of Computer Science Oct 2024 - Feb 2025
Università degli Studi di Padova, Italy

Course instructor: Dr. Adriano Luchetta

• Led weekly lab sessions with programming exercises related to course material.
• Prepared lecture materials, such as slides and sample code.
• Provided troubleshooting support and feedback on students’ code.

Teaching Assistant — Advanced Programming Feb 2021 – Jun 2021
Imam Khomeini International University, Iran

Course instructor: Dr. Hamidreza Hamidi

• Led weekly lab sessions with programming exercises related to course material.
• Prepared lecture materials, such as slides and sample code.
• Provided troubleshooting support and feedback on students’ code.

---

Industry Experience

Computer Engineering Intern Jul 2023 – Dec 2023
Consat Engineering AB, Gothenburg, Sweden

• Developed an MVP for an edge management system for IoT devices.
• Deployed a computer vision model for product classification.
• Presented the computer vision model to customers.

---

Technical Skills

• Graph Learning: GNNs, spectral clustering, link prediction, network analysis.
• Deep Learning: CNNs, autoencoders, transformers, explainable AI.
• NLP: RAG, fine-tuning, sequence labeling, dependency parsing.
• Programming: Python (PyTorch, PyG, NetworkX, Scikit-learn, HuggingFace), R, Git, Docker, Linux, HPC.

---

Languages

Language	Level
English	C2 Proficient (IELTS Academic: 8.5)
Persian	Native
French	A2
Italian	A2

---

Certificates

IELTS (Academic) 27 March 2026

Listening: 9 - Reading: 9 - Writing: 8 - Speaking: 8

---