Dr. Shivanshu Shrivastava | Deep Learning | Best Researcher Award

Dr. Shivanshu Shrivastava, Deep Learning, Best Researcher Award

Doctorate at Rajiv Gandhi Institute of Petroleum Technology, India

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๐ŸŒ Academic Background:

Dr. Shivanshu Shrivastava is an Assistant Professor in the Department of Electrical & Electronics Engineering at Rajiv Gandhi Institute of Petroleum Technology (RGIPT), Amethi, Uttar Pradesh, India. He has been contributing to the field of electrical and electronics engineering with a focus on artificial intelligence and communications since September 2021.

๐ŸŽ“ Education:

Dr. Shrivastava earned his Ph.D. from IIT Guwahati in August 2017, specializing in Wireless Communication with a thesis on “Security Issues in Cognitive Radios,” under the guidance of Prof. A. Rajesh and Prof. P. K. Bora. He completed his Postdoctoral Fellowships at Shenzhen University, China, and IIT Kanpur from August 2017 to December 2020, focusing on “Artificial Intelligence and Deep Learning Applications in 5G Communications” under Prof. Bin Chen. He holds a Bachelor of Engineering degree in Electronics and Telecommunication Engineering from CSVTU, Bhilai, with a CPI of 8.13/10.

๐Ÿ’ผ Work Experience:

Before joining RGIPT, Dr. Shrivastava worked as a Postdoctoral Fellow at Shenzhen University from January 2019 to December 2020 and as a SERB-NPDF at IIT Kanpur from August 2017 to October 2018. His current role involves advancing research in deep learning and AI applications in communications.

๐Ÿ”ฌ Research Areas:

His research interests encompass artificial intelligence and deep learning applications in communications, cognitive radio systems, wireless communications, visible light communications (VLC), and security issues in cognitive radios.

๐Ÿ“ Research Experience:

At RGIPT, Dr. Shrivastava leads research on deep learning and AI applications in wireless communication. His previous projects include optimizing achievable rates in hybrid RF/VLC systems and designing energy-efficient hybrid RF/VLC systems for 5G communications. He has supervised Ph.D. students and undergraduate project students in these areas.

๐Ÿ† Honors, Awards, and Memberships:

Dr. Shrivastava has received the International Travel Support (ITS) from SERB for attending the IEEE ICCCAS conference in Xiamen, China, and the Best Teacher Award from Union Bank of India at RGIPT. He was also honored with postdoctoral fellowships from Shenzhen University and IIT Kanpur.

๐Ÿ“– Publications:

A lightweight group-based SDN-driven encryption protocol for smart home IoT devices
  • Authors: Raza, A., Khan, S., Shrivastava, S., Wu, K., Wang, L.
  • Journal: Computer Networks
  • Year: 2024
Collision Penalty-Based Defense Against Collusion Attacks in Cognitive Radio Enabled Smart Devices
  • Authors: Shrivastava, S., John, S., Rajesh, A., Bora, P.K.
  • Journal: IEEE Transactions on Consumer Electronics
  • Year: 2024
Transfer learning for resource allotment in dynamic hybrid WiFi/LiFi communication systems
  • Authors: Verma, T., Shrivastava, S., Dwivedi, U.D., Kothari, D.P.
  • Journal: Optics Communications
  • Year: 2023
Asset Allotment in Hybrid RF/VLC Communication in the 400-700 THz Band
  • Authors: Shrivastava, S., Agarwal, S., Chen, B.
  • Journal: Terahertz Wireless Communication Components and System Technologies
  • Year: 2022
A survey on security issues in cognitive radio based cooperative sensing
  • Authors: Shrivastava, S., Rajesh, A., Bora, P.K., Lin, X., Wang, H.
  • Journal: IET Communications
  • Year: 2021

Dr. Seyed Hamed Godasiaei | Deep Learning | Best Researcher Award

Dr. Seyed Hamed Godasiaei, Deep Learning, Best Researcher Award

Doctorate at Xi’an Jiaotong University, China

Professional Profile

Summary:

Dr. Seyed Hamed Godasiaei is a versatile professional with a rich background in chemical engineering, research, and development. His career spans various disciplines, showcasing expertise in computational fluid dynamics (CFD), machine learning applications, environmental experiments, and heat transfer analysis.

๐ŸŽ“ Education:

  • Ph.D. in Chemical Engineering: Xi’an Jiaotong University
  • M.S. in Chemical Engineering: Islamic Azad University of Shahrood
  • Bachelor’s in Chemical Engineering: Islamic Azad University of Birjand

๐Ÿ’ผ Professional Experience

  • Welding and Mapping GIS: Dr. Godasiaei has applied his skills in welding techniques and Geographic Information System (GIS) mapping to various projects.
  • Lab Researcher: His research includes extensive work in environmental experiments and heat transfer studies.
  • Python for Machine Learning: He leverages Python programming for advanced applications in machine learning.
  • C++ Programming: Proficient in C++ for developing computational models and simulations.

๐Ÿ† Achievements & Awards:

  • elected as a top researcher by the Iranian National Standards Organization.
  • Recognized for environmental research contributions at KhatamToos Co, Iran.

Skills and Expertise:

Dr. Godasiaei is proficient in a wide array of software and tools essential for his research and professional endeavors, including Ansys Fluent, Ansys CFX, CFD-Post, ICEM CFD, Space Claim, Gambit, STAR-CCM+, AutoCAD, Photoshop, CorelDRAW, SolidWorks, Comsol, openLB, and Python programming.

 

Publications Top Noted:

Paper Title: Water jet angle prediction in supersonic crossflows: Eulerโ€“Lagrange and machine learning approaches
  • Authors: S.H. Godasiaei, H. Kamali
  • Journal: European Physical Journal Plus
  • Volume: 139
  • Issue: 3
  • Pages: 251
  • Year: 2024
  • Citations: 3
Paper Title: Exploring novel heat transfer correlations: Machine learning insights for molten salt heat exchangers
  • Authors: S.H. Godasiaei, A.J. Chamkha
  • Journal: Numerical Heat Transfer; Part A: Applications
  • Year: 2024
  • Citations: 2
Paper Title: Ballistic limit evolution of field-aged flexible multi-ply UHMWPE-based composite armour inserts
  • Authors: S.H. Godasiaei
  • Journal: Numerical Heat Transfer; Part A: Applications
  • Year: 2024
Paper Title: Saturated/subcooled flow boiling heat transfer inside micro/mini-channels: A new prediction correlation and experiment evaluation
  • Authors: X. Ma, X. Ji, C. Hu, J. Wei, S.H. Godasiaei
  • Journal: International Journal of Heat and Mass Transfer
  • Volume: 210
  • Pages: 124184
  • Year: 2023
  • Citations: 5
Paper Title: Advancing heat transfer modeling through machine learning: A focus on forced convection with nanoparticles
  • Authors: S.H. Godasiaei, A.J. Chamkha
  • Journal: Numerical Heat Transfer; Part A: Applications
  • Year: 2023