VSSNVG Krishna Murthy Somanchi | Applied mathematics | Best Researcher Award

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Prof. Dr. VSSNVG Krishna Murthy Somanchi | Applied mathematics | Best Researcher Award

Professor at Defence Institute of Advanced Technology, India

Prof. Dr. VSSNVG Krishna Murthy Somanchi is an esteemed mathematician and academic leader with extensive expertise in computational and applied mathematics. He has been instrumental in advancing numerical methods and mathematical modeling techniques, particularly in fluid dynamics and computational simulations. A recipient of the Erasmus Mundus – WILLPower Fellowship (2010-11) at École Centrale Paris, he has also been honored with the Best Teacher Award from G. Narayanamma Institute of Technology & Science in 2001. Dr. Krishna Murthy has served as Vice President and Executive Council Member of ISTAM (IIT Kharagpur) and is actively involved in international research collaborations, conference organizations, and curriculum development in applied mathematics and artificial intelligence.

Publication Profile

Google Scholar

Educational Details

Prof. Dr. VSSNVG Krishna Murthy Somanchi earned his Ph.D. in Mathematics from the Indian Institute of Technology Kanpur in 2010. He completed his M.Sc. in Mathematics from Osmania University, Hyderabad, in 1995 and obtained his B.Sc. in Mathematics, Physics, and Instrumentation from Andhra University, Visakhapatnam, in 1992. His postdoctoral research was conducted at École Centrale Paris, France, where he was a Postdoctoral Fellow from October 2010 to May 2011.

Professional Experience

Dr. Krishna Murthy is currently a Professor and Head of the Department of Applied Mathematics at the Defence Institute of Advanced Technology (DIAT), Pune, where he has served since 2011. Prior to this, he was an Assistant Professor at G. Narayanamma Institute of Technology & Science, Hyderabad (1998–2010), Sri Vani Degree College, Hyderabad (1998), and Vazir Sultan College of Engineering, Khammam (1995–1998). Over his distinguished career, he has played a pivotal role in developing new academic programs, leading research initiatives, and holding various administrative positions, including membership in the Board of Management, Academic Council, and Doctoral Research Committees at DIAT.

Research Interest

Dr. Krishna Murthy’s research focuses on fluid flow through porous media, finite element analysis, computational fluid dynamics (CFD), numerical methods for partial differential equations, mathematical modeling, numerical parallel algorithms, and parallel computing. His work contributes to advancements in mathematical simulations and computational techniques with applications across engineering and applied sciences.

Author Metrics

  • Publications & Editorial Roles: He has contributed to numerous research publications and serves on the editorial boards of various international journals, including Springer Nature Applied Sciences, Journal of Thermal Engineering, and multiple SCIREA and SciencePG journals.
  • Research Contributions: Developed M.Tech. programs in Data Science and Artificial Intelligence, along with courses in Mathematical Cryptography, Computational Mechanics, and Machine Learning.
  • Funding & Grants: Successfully secured research funding for international conferences and short courses, with grants exceeding ₹25.47 lakhs from DST, CSIR, DRDO, and ISTAM.
  • Memberships: Life member of ISTAM, IAENG, and WASET, and has held key positions in various academic and research committees.

Top Noted Publication

Mathematical Modelling of Pulsatile Flow of Blood Through Catheterized Unsymmetric Stenosed Artery—Effects of Tapering Angle and Slip Velocity

  • Authors: J.V.R. Reddy, D. Srikanth, S.K. Murthy
  • Journal: European Journal of Mechanics – B/Fluids
  • Volume: 48, Pages: 236–244, Year: 2014
  • Citations: 41
  • Summary: Investigates pulsatile blood flow through a catheterized artery with asymmetrical stenosis, considering tapering angle and slip velocity effects.

Influence of MHD Forces on Bejan’s Heatlines and Masslines in a Doubly Stratified Fluid-Saturated Darcy Porous Enclosure in the Presence of Soret and Dufour Effects

  • Authors: B.V.R.K. Vinay Kumar, V.S.S.N.V.G. Krishna Murthy
  • Journal: International Journal of Heat and Mass Transfer
  • Volume: 117, Pages: 1041–1062, Year: 2018
  • Citations: 33
  • Summary: Analyzes heat and mass transport in a stratified porous enclosure under magnetic field effects, incorporating Soret and Dufour diffusion.

Soret and Dufour Effects on Double-Diffusive Free Convection from a Corrugated Vertical Surface in a Non-Darcy Porous Medium

  • Authors: B.V.R. Kumar, S.K. Murthy
  • Journal: Transport in Porous Media
  • Volume: 85, Pages: 117–130, Year: 2010
  • Citations: 28
  • Summary: Examines the impact of Soret and Dufour effects on heat and mass transfer for double-diffusive convection near a wavy vertical surface.

Neural Network Based Analysis of Lightweight Block Cipher PRESENT

  • Authors: G. Mishra, S. Krishna Murthy, S.K. Pal
  • Book Chapter: Harmony Search and Nature Inspired Optimization Algorithms: Theory and Applications
  • Year: 2019
  • Citations: 22
  • Summary: Explores neural network techniques for analyzing PRESENT, a lightweight block cipher used in IoT security.

Study and Analysis of eSTREAM Cipher Salsa and ChaCha

  • Authors: P. Yadav, I. Gupta, S.K. Murthy
  • Conference: 2016 IEEE International Conference on Engineering and Technology (ICETECH)
  • Year: 2016
  • Citations: 22
  • Summary: Compares the security performance of eSTREAM ciphers, Salsa and ChaCha, with an emphasis on cryptographic resilience.

Conclusion

Prof. Dr. VSSNVG Krishna Murthy Somanchi is a strong candidate for the Best Researcher Award, given his significant contributions to computational mathematics, leadership in academic research, and ability to secure research funding. His experience in research collaborations, curriculum development, and numerical methods strengthens his profile.

To further enhance his suitability, he could increase international engagement, focus on publishing more high-impact research in recent years, and explore cutting-edge applications in AI and computational sciences.

Overall, he is a highly accomplished researcher, and if the award criteria prioritize long-term impact, leadership, and academic contributions, he is a very strong contender.

 

 

Ahmed Awad | Control Engineering | Best Researcher Award

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Dr. Ahmed Awad | Control Engineering | Best Researcher Award

Senior Electrical Maintenance Engineer at SESCO TRANS Company, Egypt

Summary:

Dr. Ahmed Awad is an accomplished electrical and control systems engineer with a blend of academic achievements and practical engineering expertise. His work integrates advanced control system algorithms and IoT-driven solutions to enhance the operational efficiency of logistic equipment. Dr. Awad is committed to the seamless fusion of theoretical research and hands-on engineering practice, contributing to innovative advancements in industrial control technologies.

Professional Profile:

👩‍🎓Education:

Dr. Ahmed Awad has a robust academic foundation in Control Engineering. He completed his Bachelor’s degree at Banha University in 2013, graduating with honors and an impressive project on Building Automation Systems, where he led the team to achieve an “Excellent” grade. He proceeded to Mansoura University, obtaining a Preliminary Master’s degree with a grade of “Very Good” in 2014, followed by a Master’s degree in Computer & Automatic Control Engineering in 2018. Dr. Awad is currently registered for his Ph.D. at Mansoura University as of July 2020, continuing his pursuit of advanced research in his field.

🏢 Professional Experience:

With over eight years of extensive experience, Dr. Awad has served as a Senior Electrical Maintenance Engineer at Sesco Trans for Developed Logistics since May 2015. In this role, he has expertly managed the maintenance, troubleshooting, and repair of various logistics heavy equipment, including mobile harbor cranes, loaders, excavators, forklifts, and trucks. His work encompasses designing and maintaining control circuits, programming PLCs (Simatic S5/S7, LS Master K), and handling motor drives such as Siemens SIMOREG and Parker SSD drives. Dr. Awad’s proficiency extends to installing, commissioning, and repairing electronic circuit boards, as well as training new engineers in electrical concepts and maintaining foundational knowledge in hydraulics and mechanical systems.

Research Interests:

Dr. Awad’s research centers on enhancing automation and control systems with a focus on applying algorithms for performance optimization. He has a keen interest in integrating IoT frameworks and deep learning methodologies for monitoring and controlling industrial systems, particularly in the context of logistics and heavy equipment. His work also delves into algorithm-based motor control systems and quality control for logistics applications.

Author Metrics:

Dr. Awad’s publications have been recognized for their relevance in the engineering and computer science communities, contributing to discussions on motor control algorithms, IoT applications, and logistics automation solutions.

Top Noted Publication:

Enhancing Tracking Performance Parameters of Induction Motor Based on PI-PSO Algorithm

  • Authors: M. M. Abd-Elsalam, M. S. Elkasas, S. F. Saraya, A. H. Awad
  • Journal: International Journal of Scientific & Engineering Research
  • Year: 2017
  • Summary: This research investigates the performance improvement of induction motors using a Proportional-Integral (PI) controller optimized with a Particle Swarm Optimization (PSO) algorithm. The study addresses the limitations of conventional PI controllers and demonstrates how integrating PSO enhances the dynamic performance of induction motors, focusing on improved tracking parameters and reduced steady-state error.

IoT Based Framework for Monitoring and Controlling Movable Harbor Cranes

  • Authors: A. H. Awad, M. S. Saraya, M. S. M. Elksasy, Amr M. T. Ali-Eldin
  • Conference: 2021 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC), IEEE
  • Year: 2021
  • Summary: This paper presents an Internet of Things (IoT) framework designed for the real-time monitoring and control of movable harbor cranes. The system aims to enhance operational efficiency and reduce human intervention by utilizing IoT-based sensors and controllers. The proposed framework demonstrates improvements in data collection, crane performance, and remote control capabilities.

A Quality Control System for Logistic Ports Goods Movable Harbor Cranes Based on IoT and Deep Learning

  • Authors: A. H. Awad, M. S. Saraya, M. S. M. Elksasy, Amr M. T. Ali-Eldin, M. M. Abd-Elsalam
  • Journal: Indonesian Journal of Electrical Engineering and Computer Science
  • Year: 2024
  • Summary: This study develops a quality control system for logistics ports, focusing on the operation of movable harbor cranes. The system leverages IoT technology combined with deep learning algorithms to monitor and ensure the safe and efficient handling of goods. The approach enhances fault detection and predictive maintenance, contributing to a more reliable and automated port management system.

Conclusion:

Dr. Ahmed Awad’s unique combination of practical engineering expertise and applied research in control systems and IoT positions him as a strong candidate for the Best Researcher Award. His work on optimizing control algorithms and integrating deep learning for enhanced system performance demonstrates significant potential for continued contributions to the field. To maximize his impact, expanding his research collaborations and publication reach would further cement his status as a leader in control engineering. Overall, Dr. Awad exemplifies the qualities of a dedicated researcher who merges innovation with real-world engineering challenges.

 

Xiaoming Li | Systems Engineering | Best Researcher Award

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Dr. Xiaoming Li, Systems Engineering, Best Researcher Award

Doctorate at Concordia University, Canada

Summary:

Dr. Xiaoming Li is an accomplished researcher and educator with extensive experience in artificial intelligence, machine learning, and optimization models for shared mobility and smart logistics. With a Ph.D. in Information and Systems Engineering from Concordia University, his work focuses on integrating data-driven approaches to optimize urban transportation systems and enhance sustainability. He has a strong background in software engineering and has contributed significantly to both academic research and industry projects. Dr. Li has received several awards, including the IEEE Outstanding Leadership Award and the Mitacs Accelerate Program Award. As a dedicated educator, he has taught and mentored students across various institutions, shaping the next generation of computer scientists.

Professional Profile:

👩‍🎓Education:

Ph.D. in Information and Systems Engineering

  • Concordia University, Montréal, QC, Canada
  • Cumulative GPA: 4.0 / 4.3

M.Sc. in Computer Software and Theory

  • Northeastern University, China
  • Cumulative GPA: top 16.7%

B.Sc. in Computer Science and Technology

  • Shenyang Aerospace University, China

Professional Experience:

Dr. Xiaoming Li currently serves as a Research Associate at Concordia University, Montréal, where he supervises interdisciplinary research in artificial intelligence and operations research for shared mobility-on-demand applications. His role involves designing deep learning models for time-series demand forecasts, developing data-driven stochastic optimization models for renewable energy mobility management, and creating an integrated optimization framework for sustainable crowd-shipping services. Previously, Dr. Li held a Research Assistant position at Concordia, working on data analysis and machine learning model development for various projects, including forecasting commodity rates and predicting hotel booking cancellations.

Dr. Li’s industrial experience includes internships at Ericsson’s Global Artificial Intelligence Accelerator, where he developed an energy-saving framework for 5G base stations, and Medialpha, where he optimized nurse routing and medical resource allocation using meta-heuristic algorithms. Additionally, he has substantial experience as a Software Engineer at Shenyang Aerospace University, leading projects and managing teams.

In academia, Dr. Li has served as an Adjunct Faculty at Vanier College, teaching database theory and application development, and as a Full-Time Lecturer at Shenyang Aerospace University, instructing on a variety of computer science courses and supervising numerous student projects.

Research Interest:

  • Machine Learning
  • Operations Research
  • Data Science
  • Data-Driven Optimization
  • Agent-Based Simulation Modeling
  • Shared Mobility
  • Smart Logistics
  • Sustainable Intelligent Transportation Systems

Publications Top Noted: 

GREEN: A Global Energy Efficiency Maximization Strategy for Multi-UAV Enabled Communication Systems

  • N. Lin, Y. Fan, L. Zhao, X. Li, M. Guizani
  • IEEE Transactions on Mobile Computing, 14, 2022.

BM-DDPG: An Integrated Dispatching Framework for Ride-Hailing Systems

  • J. Gao, X. Li, C. Wang, X. Huang
  • IEEE Transactions on Intelligent Transportation Systems, 23(8), 11666-11676, 2021.

Driver Guidance and Rebalancing in Ride-Hailing Systems Through Mixture Density Networks and Stochastic Programming

  • X. Li, J. Gao, C. Wang, X. Huang, Y. Nie
  • 2021 IEEE International Smart Cities Conference (ISC2), 1-7, 2021.

Learning-Based Open Driver Guidance and Rebalancing for Reducing Riders’ Wait Time in Ride-Hailing Platforms

  • J. Gao, X. Li, C. Wang, X. Huang
  • 2020 IEEE International Smart Cities Conference (ISC2), 1-7, 2020.

Ride-Sharing Matching Under Travel Time Uncertainty Through Data-Driven Robust Optimization

  • X. Li, J. Gao, C. Wang, X. Huang, Y. Nie
  • IEEE Access, 10, 116931-116941, 2022.