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  • Tehran

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alirezanmotiei/README.md

Alireza Najafi Motiei

Electrical Engineer & Researcher @ University of Tehran
Focusing on Bioelectronics, Biomedical Systems, and Deep Generative Learning

Email Institution GitHub

🧬 About & Research Statement

I am an Electrical Engineering graduate and researcher from the University of Tehran, ranked 11th out of 120 in my cohort with a 3.89 / 4.00 (18.32 / 20) GPA.

My research lies at the intersection of hardware bioelectronics and computational intelligence:

  1. Bio-Signal Instrumentation & Microfluidics: Designing high-frequency analog/digital circuitry (100 kHz – 500 kHz) and microfluidic devices to administer alternating electric fields (Tumor Treating Fields - TTFields) for targeted cancer cell therapeutics.
  2. Deep Generative Modeling & Representation Learning: Developing and benchmarking mathematically grounded neural architectures—including Denoising Diffusion Probabilistic Models (DDPM/DDIM), Score-Based SDEs, Normalizing Flows, and Variational Autoencoders (VAEs)—for high-dimensional scientific data synthesis and medical representation learning.

🔬 Active Research Appointments

  • Researcher, Nano Bioelectronics Laboratory (NBEL), University of Tehran
    Supervisor: Dr. Mohammad Abdolahad · (June 2024 – Present)

    • Investigating electroporation and Tumor Treating Fields (TTFields) modalities for microfluidic cancer cell therapeutics.
    • Designing precision high-frequency signal generator hardware (STM32 + AD9833 + high-speed/high-current analog driving stages) for microfluidic PDMS chips with gold interdigitated electrode (IDE) arrays.
    • Conducting multiphysics modeling of electric field distributions and thermal dissipation in biological tissue via COMSOL Multiphysics 6.2.
    • Co-authoring a research manuscript on non-cytotoxic electrochemotherapy (currently in preparation).

  • Teaching Assistant, Faculty of Electrical and Computer Engineering, University of Tehran
    (Fall 2023 – Present)

    • Electronics I & II (6 Semesters, Fall 2023 – Present) · Dr. Zeinab Sanaee, Dr. Ali Afzali-Kusha, Dr. Reihane Mahdavi
    • Engineering Mathematics (Fall 2024 – Present)
    • Probability and Statistics (Spring 2024, Fall 2025) · Dr. Behnam Bahrak, Dr. Abdol-Hossein Vahabie, Dr. Ali Haghi
    • Linear Control Systems (Fall 2025) · Dr. Mohammad Reza Nayeri, Dr. Abolfazl Yaghmaei
    • Electrical Circuits I (Fall 2023, Spring 2025) · Dr. Moein Abedini, Dr. Shaghayegh Vahdat

🚀 Featured Codebases & Technical Benchmarks

Project Description Primary Stack Technical Reports
Digital-Integrated-Circuits-VLSI-HSPICE Multi-node CMOS VLSI design across 180nm, 90nm, 32nm, and 0.5µm nodes: VTC noise margins, thermal/leakage sweeps (0°C to 100°C), Static CMOS vs DCVSL vs Dynamic NAND3, pipelined memory datapaths, and Tanner L-Edit mask layouts. HSPICE Tanner L-Edit PTM / TSMC 90nm LaTeX 46-Page Portfolio & IEEE Report
Introduction-to-Biomedical-Engineering-IBME Analog front-end (AFE) biopotential circuits in NI Multisim (ECG/EEG amplifiers, 50 Hz active Twin-T notch filter), AD8232 + Arduino real-time biopotential acquisition, and biopotential telemetry. MATLAB NI Multisim Arduino C++ AD8232 4 Reports & IEEE LaTeX
Pipelined-ARM-Processor-Verilog Synthesizable 32-bit 5-stage pipelined ARM processor (ARMv4T subset) in Verilog HDL featuring dynamic operand forwarding, load-use hazard detection, and multi-cycle SRAM controller (Zynq-7000 FPGA @ 125 MHz). Verilog HDL Xilinx Vivado ModelSim IEEE Report & Persian Report
Deep-Generative-Models Complete graduate-level theoretical formulation, implementations, and empirical benchmarks for modern generative architectures: VAEs ($\beta$-VAE, VampPrior), Masked Autoregressive Flows, CycleGAN with PatchGAN, Energy-Based Models, Score-Based Generative Models (SDEs), DDPM/DDIM, and DreamBooth. PyTorch Diffusers Torchvision Reports & Figures Included
Neural-Networks-and-Deep-Learning Comprehensive graduate coursework repository covering Vision Transformers (ViT) on agricultural pathology, CamVid semantic segmentation (100 epochs, $8.2\times$ MAC reduction), Domain-Adversarial Neural Networks (DANN), medical polyp EndoVAE, ICU telemetry forecasting, and adversarial ML. PyTorch TensorFlow Transformers 7 IEEEtran LaTeX Reports
profdash-ece OpenAlex-based ECE/BME faculty importer & venue preset extending profdash (upstream: sahroush/profdash) — faculty research tracking, AI-assisted scoring outreach, and literature profiling. Python OpenAlex API SQLite HTMX Source Code

🎓 Education & Academic Honors

  • University of Tehran, Tehran, Iran
    Bachelor of Science in Electrical Engineering · (September 2026)
    • Cumulative GPA: 18.32 / 20.00 (3.89 / 4.00, converted per official institutional non-linear scale)
    • Cohort Standing: Ranked 11th out of 120 students in the Electrical Engineering department
    • National University Entrance Exam (Konkur): Ranked 293rd out of ~165,000 candidates (Top 0.18%) nationwide in Mathematics & Physics (June 2021).

🛠️ Technical Competencies

Domain Tools & Technologies
Machine Learning & Deep Learning PyTorch, TensorFlow / Keras, HuggingFace Transformers, Diffusers, Torchattacks, Scikit-Learn
Hardware & Embedded Systems STM32 (ARM Cortex-M4/M7), Altium Designer (PCB Layout & High-Speed Routing), Verilog HDL, Xilinx Vivado
Circuit Simulation & EDA LTspice, HSPICE, Cadence Virtuoso, NI Multisim, L-Edit (Tanner EDA)
Multiphysics & Scientific Computing COMSOL Multiphysics 6.2 (AC/DC & Thermal Modules), MATLAB & Simulink, ModelSim
Programming Languages Python, C / C++, Verilog, R, SQL, \LaTeX

🇮🇷 معرفی و مشخصات آکادمیک

علیرضا نجفی مطیعی، دانش‌آموخته و پژوهشگر مهندسی برق از دانشگاه تهران (رتبه ۲۹۳ کنکور سراسری، معدل ۱۸.۳۲، رتبه ۱۱ دانشکده). زمینه پژوهشی و تخصصی من در مرز مشترک طراحی سیستم‌های سخت‌افزاری بیوالکترونیک (ژنراتورهای فرکانس بالا، چیپ‌های میکروفلوئیدیک و اعمال میدان‌های الکتریکی نابودکننده تومور در آزمایشگاه NBEL) و مدل‌های هوش مصنوعی زایشی و یادگیری عمیق (مدل‌های دیفیوژن، ترنسفورمرهای بینایی و بازنمایی داده‌های پزشکی) متمرکز است.

Maintained by Alireza Najafi Motiei · Last updated: 2026

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