AmirHossein Entezari

amir.entezari.org amir@entezari.org amirho.entezari@gmail.com GitHub: github.com/Amir-Entezari LinkedIn: Amirhossein-Entezari

Education

University of Tehran (National Rank: 1st)

B.Sc. in Computer Science Sep 2020 – Feb 2025 GPA: 17.93/20 (Overall: 3.84/4, Last Two Years: 3.90/4) Ranked among Top 10 students

National University Entrance Exam – Iran

Mathematics and Physics Track Aug 2020 Ranked 148 (Top 0.1%) among 155,000 participants

National Organization for Development of Exceptional Talents (NODET)

Diploma in Mathematics and Physics Sep 2017 – Sep 2020 GPA: 18.81/20 (4.0/4.0) Admission acceptance rate < 5%

Research Experience

Object-Centric Tokenization for Adaptive Multimodal Graph in Video Reasoning

Fall 2025 – Present Supervised by Prof. Ziaeetabar

Ongoing research — details coming soon.

Time Series Analysis for Alzheimer’s Disease Diagnosis Using Transformers

Fall 2024 Bachelor Thesis – Supervised by Prof. BabaAli

• Evaluated whether foundation models for time-series can serve as representation learners for EEG-based dementia diagnosis under limited data and high noise conditions.
• Designed a rigorous evaluation pipeline including ICA, ASR preprocessing and LOSO validation to prevent subject leakage and assess cross-subject generalization.
• Demonstrated that MOMENT-based representations improved classification specificity (75% accuracy), while revealing failure modes of end-to-end transformers on raw EEG signals.

Supervised and Unsupervised Learning with Temporal Coding in Spiking Models of the Visual Cortex

Spring 2024 Supervised by Prof. GanjTabesh

• Studied temporal spike coding and biologically inspired plasticity in spiking neural networks.
• Showed that STDP-based learning alone is insufficient for stable feature emergence.
• Demonstrated that competitive mechanisms (lateral inhibition, k-WTA, homeostasis) are necessary for robustness under pattern overlap and noise.

Selected Projects

U-Net-Based Segmentation for Gastrointestinal Images in Cancer Detection

Fall 2023 Supervised by Prof. Sajedi

• Analyzed encoder–decoder architectures for pixel-level segmentation of gastrointestinal lesions on Kvasir-SEG.
• Studied impact of data augmentation and spatial feature fusion on generalization.
• Achieved 93.39% validation accuracy.

Author Identification in Persian Literature Using Transformers and Classical Models

Fall 2023 Supervised by Prof. BabaAli

• Compared pretrained language models with TF-IDF baselines under limited data.
• Best transformer: 70% test accuracy; classical models: 98%.

Semantic Text Classification through Word Embedding and Statistical Modeling

Fall 2023

• Compared embedding-based representations (Word2Vec, GloVe, FastText-style) with classical statistical baselines (NB, SVM, LSA-style).
• Analyzed dimensionality reduction and representation impact on generalization and efficiency.

Computational Visual Analysis for Grapevine Leaf Classification

Spring 2022

• Compared pretrained CNN features, custom CNNs, and autoencoder-based dimensionality reduction.
• Achieved 92% classification accuracy.

Work Experience

Backend Developer – ZLAB Research & Development Lab

June 2023 – Nov 2023

• Developed AI-driven backend solutions using Django and Docker.
• Improved processing speed by 30%.
• Integrated Redis and scalable REST infrastructure.

Technologies: Django, REST Framework, Docker, Redis, Linux, Databases

Teaching Experience

Teaching Assistant for 8+ Courses (2020 – 2025) University of Tehran – Mentored 300+ students

• Designed theoretical and programming assignments.
• Led project-based learning sessions and support classes.
• Collaborated with faculty to organize quizzes, labs, and projects.

Including:

• Design and Analysis of Algorithms (Prof. GanjTabesh)
• Data Mining and Artificial Intelligence (Prof. Sajedi)
• Advanced Information Retrieval (Prof. BabaAli)
• Principles of Computer Systems (Prof. Nadi, Prof. BabaAli)
• Statistics, Data Structures, Operating Systems, Basic Programming, General Calculus

Relevant Coursework (Selected)

• Computational Neuroscience (19.75/20)
• Combinatorics (19.88/20)
• Design and Analysis of Algorithms (19.7/20)
• Linear Algebra (19.46/20)
• Introduction to Bioinformatics (18.75/20)
• Artificial Intelligence (18.9/20)
• Graph Theory (18.84/20)

Honors & Awards

• Top 10 Student – University of Tehran (2023)
• Rank 148 (Top 0.1%) – National University Entrance Exam (2020)
• Rank 259 (Top 0.2%) – English Language National Exam
• Member – National Organization for Development of Exceptional Talents

Technical Skills

Programming: Python, C++, JavaScript, Assembly, LaTeX ML/DL: PyTorch, TensorFlow, Keras, sklearn, PymoNNto, CoNeX Systems & Backend: Django, FastAPI, REST Framework, Docker, Kubernetes, Redis, Linux Core Areas: Computer Vision, Multimodal AI, Deep Learning, Neural Networks, Compiler, Operating Systems

Languages

English: C1 (IELTS 7.5) Persian: Native

References

Available upon request (Or list professors only if required by specific applications.)

Last updated: February 12th 2026