Good planning and organizing skill • Determined and motivated towards my goals • Self-motivated, Self-disciplined, Positive attitude • High Degree of Adaptability • Team worker Good interpersonal relation Professional and awarded national cyclist and mountain climber Interested in pursuing the prestigious joint M.Sc. SSIs Program About Me!
Engineering, specializing in Electronics 1. University of Zanjan, Zanjan, 2015-2019 2. 2nd rank among 120 university classmates from University of Zanjan, 2019 3. B.Sc. Project: Design of an Earthquake Detection System Using Arduino Boards • Electrical Power Distributor (Internship) • Tehran Power Transmission Maintenance Engineering Company (METANIR Co.), Tehran, Summer 2018. • Master of Science degree in Electrical Engineering, specializing in Microelectronics Circuit Designing 1. Sharif University of Technology, Tehran, 2019-2021 2. Honor talented student Certificate from Sharif University of Technology, 2021 3. Entering graduate program with an exemption from university entrance exam (konkoor) 4. M.Sc. Project: Design and Implementation of a low phase noise CMOS integrated frequency synthesizer • Superconductive Electronics Research Laboratory (SERL) 1. Sharif University of Technology, Tehran, July 2021-Feb 2022 2. Lab Manager and Fabrication process control systems Administrator. • Electronic Engineer (Part-time Employment) Academic Centre for Education, Culture & Research (ACECR)_ Sharif University Branch, Tehran, Sep-Dec 2021. • “Amrrieh” Program (Military Service Obligation) Assembling a 20kW On-grid Solar Power Plant at Sharif University of Technology, Tehran, Feb 2022-Feb 2024. • Language Proficiency: 1. English, Persian, Turkish: Fluent, Deutsch: Intermediate
of a 20kW on-grid solar power plant on the roof of EE Department. • Management of human resources and financial office • Responsibility of the directive office of the electrical engineering department • Responsibility of managing the department's assets 20kW On-Grid Solar Power Plant
Low Phase Noise CMOS Integrated Phase Locked Loop (Frequency Synthesizer) By Using Saw Resonator for a HTS SQUID based Magnetocardiography(MCG) subject under the supervision of Dr. Mehdi Fardmanesh, 2019-2021. • In this thesis, we seek to design and build an oscillator at 1GHz with low phase noise (-160 dBc/Hz) and lock this oscillator to another oscillation at a lower frequency that has more thermal and temporal stability for the detection of heart signal(Sub-100Hz) in a Magnetocardiography(MCG) device which uses a RF-SQUID sensor in the superconductive state.
Detection System 8 This experience made me to gain skills including: PCB Designing using Altium Designer software. Becoming familiarize with Etching process. Skill to enhance coding ability of various ICs, e.g., Atmega64 and Sim900 Module.
Circuits Design, including Respectively: • RF LNA, Mixer and Power Amplifier, Frequency Synthesizer, On- Chip DC-DC Power Converters • Micro-architecture and Circuit Design, VLSI Design, VCO, Los • Phased Arrays • Solid State Physics and Quantum Transport including: • FinFET Transistors Technology , SoC, and SiGe Technology, • Computation in Memory (CIM) and Memory Architecture Design: • ReRAM, SRAM, Memristors • Edge Applications, Artificial Intelligence
Society which is the Motto of the Erasmus Mundus Program ❖Open international community with multidisciplinary teamwork ❖ A safe and inclusive working environment ❖Top Facilities for research, education, and innovation ❖Room for personal growth ❖Salary and other employment conditions
years, usage of IoT has changed many sectors. • As a result generation of data at edge devices level has increased which demands: Higher Network Bandwidth and Lower Latency. • Edge Computing (EC) has solved this issues • On the other hand, Increasing demand to use AI at the edge device has led to some new challenges, e.g., in millimeter and THz applications: • Safety-Critical applications, such as in autonomous vehicles • Face recognition and speech translation applications • Speed: edge computing offers security benefits due to wider data distribution
of Deep Learning(DL), and AI in every edge device, creates an urgent need for edge-AI processing Hardware. • New edge Hardware Requirement: • High Throughput and High Bandwidth • Reliable and Fast • Secure AI Processing at Ultra-low Power (ULP) • A very short time to market Edge Processors: • 100X Energy Efficient • 10X Design Time Reduction • Powerful and Fast enough for DL applications
TOPs/sec/W • Google TPU1:2.3 TOPs/sec/W • Inference only • Not including data movement • IBM internal Analog Designs: • MNIST: 15.2 TOPs/sec/W • PTB LSTM: 14 TOPs/sec/W 14
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