Dr. Seyed Reza Nabavi | Nueral Network Awards | Best Researcher Award

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Dr. Seyed Reza Nabavi | Nueral Network Awards | Best Researcher Award 

Dr. Seyed Reza Nabavi, University of Mazandaran, Iran

Dr. Seyed Reza Nabavi is an Associate Professor of Applied Chemistry in the Department of Applied Chemistry at the University of Mazandaran, Babolsar, Iran. he earned his Ph.D. in Applied Chemistry from the University of Tabriz in 2009, focusing on hybrid modeling and artificial intelligence applications for olefin process optimization. As a visiting scholar at the National University of Singapore in 2008, Dr. Nabavi further honed his expertise in chemical and biomolecular engineering. His teaching repertoire spans diverse topics, including transport phenomena, chemical reactor design, and chemical process modeling at both undergraduate and postgraduate levels. A prolific researcher, his interests lie in polymer nanotechnology, catalytic processes, machine learning in chemical process optimization, and pyrolysis. Notably, he has collaborated on significant projects, such as studying coke formation and inhibitors in naphtha thermal cracking at the bench scale, bridging academia and industry. Married and based in Iran, Dr. Nabavi has received recognition for his academic excellence, including being the top-ranked B.Sc. graduate.

Professional Profile:

ORCID

Suitability for Best Researcher Award: Seyed Reza Nabavi

Based on the provided curriculum vitae, Dr. Seyed Reza Nabavi demonstrates exceptional qualifications that make him a strong candidate for the Best Researcher Award. Below is a summary of his key accomplishments and attributes supporting his suitability for this recognition

🎓 Educational Background

  • Ph.D. in Applied Chemistry (2009), University of Tabriz 🧬
    Thesis: Application of Hybrid Modeling and Artificial Intelligence in Modeling and Optimization of Olefin Processes.

    • Visiting Scholar: National University of Singapore (Apr-Dec 2008).
  • M.Sc. in Applied Chemistry (2003), University of Tabriz 🧵
    Thesis: Preparation and Characterization of Conducting Polyaniline/Nylon-6 Composite Fibers.
  • B.Sc. in Applied Chemistry (2000), University of Sistan and Baluchestan 🏛️
    • 🎖️ First Rank among graduate students.

👨‍🏫 Teaching Experience

  • Expertise in teaching at M.Sc. and B.Sc. levels 📚, including advanced courses:
    • Transport Phenomena, Design of Experiments (DOE), Chemical Reactors, Process Control, and Petrochemical Processes.
    • Proficient in Modeling and Simulation and Unit Operation Laboratories.

🔬 Research Interests

  • Nanotechnology of Polymers: Electrospinning and Nanofiber Membranes 🧵.
  • Catalytic Processes: Ozonation, Photocatalysts, and Reaction Engineering ⚗️.
  • Modeling and Optimization: Applying Machine Learning and Evolutionary Algorithms 🤖.
  • Thermal Cracking & Pyrolysis: Exploring Coke Formation and Mitigation 🔥.

🏅 Academic Positions

  • Associate Professor: 2022 – Present, University of Mazandaran 🏫.
  • Assistant Professor: 2012 – 2022, University of Mazandaran.

🧪 Research Highlights

  • Lead researcher in projects like Coke Formation and Inhibitors in thermal cracking of naphtha (collaboration with Tabriz Petrochemical Company) 🛢️.
  • Published impactful research on polymers, reaction engineering, and optimization using cutting-edge AI techniques.

Publication top Notes:

Multi-Criteria Decision Making in Chemical and Process Engineering: Methods, Progress, and Potential

A liter scale synthesis of hierarchically mesoporous UiO-66 for removal of large antibiotics from wastewater

Data-Based Modeling, Multi-Objective Optimization and Multi-Criteria Decision Making of a Catalytic Ozonation Process for Degradation of a Colored Effluent

A bacterial cellulose-based LiSrVO4:Eu3+ nanosensor platform for smartphone sensing of levodopa and dopamine: point-of-care diagnosis of Parkinson’s disease

Parametric optimization of poly(ether sulfone) electrospun membrane for effective oil/water separation

Deep Learning Aided Multi-Objective Optimization and Multi-Criteria Decision Making in Thermal Cracking Process for Olefines Production

Assist Prof Dr. Yishu Zhang | Artificial Neuron Awards | Best Researcher Award

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Assist Prof Dr. Yishu Zhang | Artificial Neuron Awards | Best Researcher Award 

Assist Prof Dr. Yishu Zhang, Zhejiang University, China

Yishu Zhang is a 32-year-old researcher currently serving as a Hundred Talents Researcher at the School of Micro-nano Electronics, Zhejiang University. He holds a Ph.D. in Electronic Engineering from the Singapore University of Technology and Design, where he achieved a GPA of 4.4/5 under the supervision of Zhao Rong. Zhang also earned his B.Sc. in Microelectronics from Jilin University, China, with a GPA of 3.61/4. He has over five years of professional experience, including roles as the Director of the Reliability Department at the Zhejiang CMOS Innovation Platform and as an Assistant Professor at Zhejiang University. His research focuses on emerging memristive devices, neuromorphic computing, and the 55nm CMOS manufacturing process. Zhang has supervised several doctoral and master’s students, contributing to advancements in high-reliability RRAM devices and neuromorphic computing based on 2D materials. He has been recognized for his work with various awards and honors, including the Zhejiang Province Thousand Talents Project and a Silver Medal in the 2023 China Postdoctoral Innovation and Entrepreneurship Competition. Zhang has also contributed to the academic community as a guest editor and reviewer for several prestigious journals. His skills encompass micro-nanofabrication, electrical characterization, semiconductor processes, and data processing using Python.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award: Yishu Zhang

Research Expertise & Direction: Yishu Zhang is an exceptional candidate for the Best Researcher Award due to his extensive contributions to emerging technologies such as memristive devices (RRAM, CBRAM, and 2D ferroelectronics), neuromorphic computing, and in-memory computing. His specialization in cutting-edge technologies that directly impact fields like AI hardware and bio-medical applications demonstrates his forward-thinking approach and relevance in today’s research landscape.

Education:

  • Ph.D. in Electronic Engineering (2015.1 – 2019.10):
    Singapore University of Technology and Design (SUTD)
    GPA: 4.4/5
    Supervisor: Zhao Rong
  • B.Sc. in Microelectronics (2010.9 – 2014.7):
    Jilin University, China
    GPA: 3.61/4

Work Experience:

  • Director of Reliability Department (2022.3 – Present):
    Zhejiang CMOS Innovation Platform

    • Supervises 2 doctoral and 2 master’s students working on high-reliability RRAM devices compatible with 55nm standard logic back-end processes.
    • Responsible for R&D of 55nm device reliability and embedded eFlash.
  • Assistant Professor (2021.11 – Present):
    School of Micro-nano Electronics, Zhejiang University

    • Supervises 4 doctoral and 1 master’s student, focusing on neuromorphic computing devices based on 2D materials.
  • Research Fellow (2019.12 – 2021.10):
    National University of Singapore
    Supervisor: Loh Kian Ping

    • Investigated two-dimensional ferroelectric materials for neuromorphic devices and designed biocompatible neuromorphic devices for biomedical applications.
  • Intern, PhD Researcher (2018.10 – 2019.9):
    Institute for Infocomm Research (I2R), A*STAR
    Supervisor: Jiang Wenyu

    • Worked on Spiking Neural Networks (SNN) and their applications in image classification using emerging memory devices.
  • Intern, PhD Researcher (2018.5 – 2018.9):
    Sungkyunkwan University, N Center
    Supervisor: Yang Heejun

    • Explored 2D materials like hBN and Graphene for large-scale memory applications, designing a self-selective Van Der Waals Heterostructure.

Teaching Experience:

  • Artificial Intelligence Hardware Design (Graduate Course), Co-Lecturer at Zhejiang University (2022.10 – 2022.12)
  • Fabrication of Microelectromechanical Systems (Undergraduate Course), Teaching Assistant at SUTD (2017.1 – 2017.5)
  • Engineering in the Physical World and Design (Undergraduate Course), Teaching Assistant at SUTD (2016.1 – 2016.5)

Publication top Notes:

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