Abirami Karthikeyan | Engineering | Young Scientist Award

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Dr. Abirami Karthikeyan | Engineering | Young Scientist Award

Assistant Professor | SASTRA Deemed University | India.

Dr. Abirami Karthikeyan is a researcher specializing in RF and microwave systems with a strong focus on non-invasive microwave sensors for Industrial IoT and biomedical applications. Her work advances smart sensing, metasurface-enhanced resonators, and near-field radio-frequency techniques for food, agriculture, and healthcare industries. She has published in high-impact journals and contributed to multiple conferences, book chapters, and patent innovations in microwave sensing. Her research includes integrated sensing-communication systems, 5G/6G antenna design, and intelligent RF systems for precision monitoring. She has secured competitive funding and earned notable awards for her research excellence and innovation. Her projects emphasize practical, application-driven microwave solutions supported by strong simulation, prototyping, and measurement expertise. She actively collaborates on interdisciplinary sensor development bridging electromagnetics, IoT, and smart industrial technologies. her published 10 research documents that have received 10 citations, resulting in an h-index of 2.

Citation Metrics (Scopus)

20

15

10

5

0

Citations
10
Documents
10

h-index
2


View Scopus  Profile
 View Google Scholar Profile

Featured Publications

 

Heba Afify | Engineering | Editorial Board Member

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Dr. Heba Afify | Engineering | Editorial Board Member

Cairo | Egypt

Dr. Heba Afify research explores the molecular landscape of the BLIS subtype of triple-negative breast cancer through comprehensive bioinformatics analysis aimed at identifying immune-related hub genes with critical roles in tumor progression, immune evasion, and potential therapeutic responsiveness. Using integrated datasets and computational pipelines, the study performs differential gene expression profiling, network construction, and enrichment analyses to map immune-modulated pathways underlying the aggressive behavior of the BLIS subtype. Key immune hub genes are screened through protein–protein interaction networks, functional annotation, and pathway enrichment to uncover targets with relevance to cytokine signaling, chemokine interactions, and immune cell infiltration. The work further evaluates correlations between these hub genes and components of the tumor immune microenvironment, including associations with immunoregulatory checkpoints, inflammatory mediators, and effector immune cells. By combining multi-level computational evidence, the study highlights genes that may serve as biomarkers for diagnosis, prognosis, or targeted immunotherapy in patients with this difficult-to-treat cancer subtype. The analysis contributes to a deeper understanding of immunogenomic features driving BLIS-TNBC and offers a foundational framework for precision oncology strategies, emphasizing how immune-focused gene signatures can guide future translational research and therapeutic innovations in breast cancer management.

Featured Publications

Adel, H., Abdel Wahed, M., & Afify, H. M. (2025). Bioinformatics analysis for immune hub genes in BLIS subtype of triple-negative breast cancer. Egyptian Journal of Medical Human Genetics. https://doi.org/10.1186/s43042-025-00745-0

Afify, H. M., Mohammed, K. K., & Hassanien, A. E. (2025). Stress detection based EEG under varying cognitive tasks using convolution neural network. Neural Computing and Applications, Advance online publication. https://doi.org/10.1007/s00521-024-10737-7

Afify, H. M., Mohammed, K. K., & Hassanien, A. E. (2024). Insight into automatic image diagnosis of ear conditions based on optimized deep learning approach. Annals of Biomedical Engineering. https://doi.org/10.1007/s10439-023-03422-8

Waleed Algriree | Engineering | Editorial Board Member

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Dr. Waleed Algriree | Engineering | Editorial Board Member

Putra university malaysia | Malaysia

Dr. Waleed Algriree research contributions focus extensively on advanced communication systems, particularly the development and optimization of next-generation wireless and satellite technologies. Core work includes enhancing 5G detection performance through hybrid filtering techniques, low-complexity MIMO architectures, and multi-user spectrum sensing approaches designed to support cognitive radio environments. Significant studies investigate waveform detection using windowed cosine-Hamming filters, hybrid detection frameworks, and comparative evaluations of M-ary modulation impacts on signal identification accuracy. Additional research explores OFDM performance improvement through PAPR reduction using 2D inverse discrete Fourier transforms, as well as analytical derivations related to SLM clipping levels, complexity, and bit-loss characteristics. Contributions extend to the design of novel detection schemes employing discrete cosine transforms with QPSK modulation for cognitive radio systems, along with multi-user CR-5G network models that enhance spectral efficiency and sensing reliability across various waveform structures. Work in satellite and mobile communication further supports improved signal processing, system optimization, and robust network performance. Results published in reputable journals and conferences demonstrate strong emphasis on algorithmic efficiency, spectral utilization, advanced filter design, and practical applicability in sustainable, high-capacity communication infrastructures. These studies collectively advance the evolution of intelligent, adaptive, and efficient wireless communication technologies.

Featured Publication

Algriree, W. K. H. (Year). Advancing healthcare through piezoresistive pressure sensors: A comprehensive review of biomedical applications and performance metrics.

Sheharyar Khan | Engineering | Young Scientist Award

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Dr. Sheharyar Khan l Engineering
| Young Scientist Award

Shandong University | Pakistan

Dr. Sheharyar Khan is a distinguished computer scientist and software engineer with extensive expertise in software engineering, artificial intelligence, and cybersecurity, specializing in IoMT edge-cloud frameworks and network intrusion detection systems. Currently a Postdoctoral Research Fellow at Shandong University, he leads independent and collaborative research initiatives, designing experiments, analyzing data, and publishing findings in high-impact journals. His doctoral research at Northwestern Polytechnical University focused on optimization-based hybrid offloading frameworks for IoMT in edge-cloud healthcare systems, demonstrating the integration of advanced computing techniques with practical healthcare applications. Dr. Khan has made significant contributions to explainable AI and hybrid ensemble machine learning, as seen in publications such as “HCIVAD: Explainable hybrid voting classifier for network intrusion detection systems” and “Consensus hybrid ensemble machine learning for intrusion detection with explainable AI”. With prior experience as a lecturer and IT specialist, he combines academic rigor with practical software development expertise. Dr. Khan has 104 citations across 10 documents, an h-index of 6, an i10-index of 5, is indexed under Scopus Author ID 57221647889, and holds ORCID 0000-0002-0089-0168, reflecting his impact on the field. Recognized for his analytical skills, innovation, and interdisciplinary research, he continues to advance secure, intelligent, and explainable computing systems for both academic and real-world applications.

Profile: Scopus | Google Scholar | Orcid | Researchgate 

Featured Publications

Khan, S., Liu, S., Pan, L., & Mei, G. (2025). Optimization-based hybrid offloading framework for IoMT in edge-cloud healthcare systems. Future Generation Computer Systems, 108163. https://doi.org/

Ahmed, S. K. M. T. S., Jiangbin, Z., & Khan, S. (2025). HCIVAD: Explainable hybrid voting classifier for network intrusion detection systems. Cluster Computing, 28(343). https://doi.org/

Ahmed, M. T. S., Jiangbin, Z., & Khan, S. (2024). Consensus hybrid ensemble machine learning for intrusion detection with explainable AI. Journal of Network and Computer Applications, 5*. https://doi.org/

Khan, S., Jiangbin, Z., & Ali, H. (2024). Soft computing approaches for dynamic multi-objective evaluation of computational offloading: A literature review. Cluster Computing, 27(9), 12459–12481. https://doi.org/

Heyu Peng | Engineering | Best Researcher Award

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Mr. Heyu Peng | Engineering | Best Researcher Award

Xi’an Jiaotong University | China

Heyu Peng is an emerging researcher in the field of nuclear science and technology, currently pursuing his doctoral studies at the School of Nuclear Science and Technology, Xi’an Jiaotong University, China, since March . His research primarily focuses on the development and application of advanced computational methods in nuclear engineering, particularly Monte Carlo particle-transport simulations and coupled deterministic–stochastic modeling approaches. He has contributed to significant advancements in the refinement of nuclear simulation tools, demonstrating his expertise in improving accuracy, efficiency, and applicability for nuclear reactor analysis and radiation transport problems. he co-authored a paper published in IEEE Transactions on Nuclear Science that presented a coupled deterministic and Monte Carlo method for modeling and simulating self-powered neutron detectors, a study that addressed critical aspects of detector response modeling and its implications for nuclear instrumentation and monitoring. More recently, a cutting-edge computational tool designed to enhance nuclear reactor physics simulations and broaden its utility in research and practical applications. Through these publications, Peng has established himself as a promising researcher contributing to the advancement of computational nuclear science. His work reflects a strong commitment to bridging theoretical development with real-world applications, offering tools and methodologies that can improve safety, efficiency, and innovation in nuclear energy systems. As a doctoral candidate, Peng continues to expand his research profile, collaborating with experts in the field and contributing to interdisciplinary efforts in nuclear engineering. His growing academic contributions highlight his potential to become a leading researcher in nuclear science, with a focus on computational methods that can shape the future of nuclear technology and its safe, sustainable applications.

Profile: Orcid

Featured Publications

  • He, Q., Zheng, Q., Li, J., Huang, Z., Huang, J., Qin, S., Shu, H., Peng, H., Yang, X., Shen, J., et al. (2024). Overview of the new capabilities in the Monte-Carlo particle-transport code NECP-MCX V2.0. EPJ Nuclear Sciences & Technologies.

  • Zhou, Y., Cao, L., He, Q., Feng, Z., & Peng, H. (2022). A coupled deterministic and Monte-Carlo method for modeling and simulation of self-powered neutron detector. IEEE Transactions on Nuclear Science.

 

Rafita Haque | Engineering | Best Researcher Award

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Ms. Rafita Haque | Engineering | Best Researcher Award

Florida International University | United States

A highly motivated academic and researcher, this individual is currently pursuing a Ph.D. in Computer and Electrical Engineering, specializing in artificial intelligence, biomedical sensors, signal analysis, and data security. With a foundation built on degrees in Software Engineering and Computer Science and Engineering, their expertise bridges software development, academic teaching, and advanced research. Their professional background includes university-level teaching in computer science and software engineering, where they guided undergraduate students through core computing courses and research activities. In addition to academia, they have held positions as a Software Quality Assurance Engineer, where they contributed to the development and refinement of AML solutions for banking and insurance applications. Their scholarly work includes multiple peer-reviewed journal and conference publications indexed by Scopus, Springer, and Web of Science. Recognized with awards for both academic research and practical projects, they are committed to contributing to technological advancement in healthcare, artificial intelligence, and secure information systems.

Profile

Scopus | Orcid | Google Scholar

Education 

Rafita Haque Currently enrolled in a Ph.D. program in Computer and Electrical Engineering, the individual is conducting research in artificial intelligence, biomedical devices, signal and data analysis, and cardiovascular health technologies. They previously completed a Master’s degree in Software Engineering, where the focus was on analyzing consumer information quality within social media platforms and its effect on purchase decisions. Their Master’s education emphasized management information systems and data analytics. Prior to that, they earned a Bachelor’s degree in Computer Science and Engineering, which included a final year project on developing a secure intra-university network system. Throughout their education, they have maintained strong academic performance and engaged in research aligned with cybersecurity, data analysis, and emerging digital technologies. They have also completed several professional training programs in networking, ASP.NET development, and cybersecurity, enhancing their technical proficiency and preparing them for both academic and industry challenges in the computing domain.

Experience 

Rafita Haque With diverse experience in both academia and industry, this individual has served as a lecturer in computer science and software engineering departments at two universities. Their teaching portfolio includes courses such as programming languages, operating systems design, numerical analysis, and theory of computing. In these roles, they mentored undergraduate students, supported research collaborations, and contributed to curriculum development. Prior to and alongside their academic roles, they worked as a Software Quality Assurance Engineer at prominent software firms, where they contributed to the design, testing, and enhancement of software systems used in financial and insurance institutions. Their technical expertise includes system validation, software error correction, and performance improvement using technologies such as ASP.NET, Python, MySQL, and NoSQL. These roles have provided them with a well-rounded professional profile, integrating both the theoretical rigor of academia and the applied problem-solving demands of the software industry.

Awards and Honors

This researcher has earned multiple recognitions for their academic excellence and research contributions. They received the Best Paper Award in the Internet of Things (IoT) category at an international technology and data science conference held in Malaysia. During undergraduate studies, they were awarded Best Project honors for developing a secure network management system designed for academic institutions. Their academic output has also led to invitations for presentations at notable forums, including national-level blockchain competitions. Their research has been published in several peer-reviewed journals and conference proceedings, many of which are indexed in Scopus, Web of Science, and Springer. These works address topics such as web application vulnerabilities, blockchain integration in healthcare systems, deep learning for heritage architecture, and the intersection of IoT with digital commerce. The recognition reflects not only the relevance of their work but also their ongoing commitment to advancing practical, interdisciplinary solutions in computing and health-related technologies.

Research Focus

This researcher’s work centers on the intersection of artificial intelligence, biomedical engineering, and data security. Their doctoral research explores the integration of AI with biomedical sensors and photoplethysmogram (PPG) signal analysis to develop innovative diagnostic tools for cardiovascular health monitoring. Their broader research interests also include secure data transmission in healthcare systems, especially using blockchain technology for electronic medical records. Previous contributions have investigated the role of digital consumer information, remote protocol integration, and signal processing for both medical and heritage architecture applications. By leveraging AI-driven approaches with secure data infrastructure, their research aims to enhance the reliability, accessibility, and security of digital health technologies. The interdisciplinary nature of their work allows them to address complex challenges in both technical and healthcare environments, positioning them at the forefront of intelligent systems development for improved human health and cybersecurity in medical data ecosystems.

Publications 

Title: Broken authentication and session management vulnerability: a case study of web application
Year: 2018
Citation Count: 48

Title: Blockchain-based information security of electronic medical records (EMR) in a healthcare communication system
Year: 2021
Citation Count: 36

Title: Integration of blockchain and remote database access protocol-based database
Year: 2020
Citation Count: 14

Title: Modeling the role of C2C information quality on purchase decision in Facebook
Year: 2018
Citation Count: 13

Title: A cloud of things (CoT) approach for monitoring product purchase and price hike
Year: 2021
Citation Count: 10

Title: Identification of construction era for Indian subcontinent ancient and heritage buildings by using deep learning
Year: 2020
Citation Count: 10

Conclusion

Rafita Haque stands out as a capable and emerging researcher whose contributions span a wide range of impactful areas at the intersection of AI and healthcare technologies. Her academic qualifications, research output, teaching roles, and industry engagement present a holistic view of a scholar committed to advancing science and technology. With her current trajectory and a strategic focus on deepening her expertise and publication impact, she is well-positioned to become a leading figure in her field. Overall, she is a deserving candidate for the Best Researcher Award, particularly within the category of early-career researchers who are demonstrating exceptional promise and innovation in multidisciplinary research.

Sujata Basyal | Control System | Best Researcher Award

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Ms. Sujata Basyal | Control System | Best Researcher Award

Research Assistant at Auburn University, United States

Sujata Basyal is a passionate mechanical engineer and researcher from Nepal, currently pursuing her Ph.D. at Auburn University. With a strong foundation in nonlinear control and robotics, she works at the CARE Lab developing robust, adaptive, and intelligent control strategies. Sujata’s journey spans from mechanical design roles in Nepal to cutting-edge research in the U.S. She has co-authored numerous journal and conference papers on exoskeletons, deep neural networks, and control systems. Beyond academia, she’s a community leader, active volunteer, and a dedicated advocate for women in engineering and STEM education. 🌍🤖📚

Publication Profile

Google Scholar

Academic Background

Sujata holds a Ph.D. (in progress) and an M.S. in Mechanical Engineering from Auburn University, where she’s a Graduate Research Assistant in the CARE Lab. She earned her Bachelor’s degree in Automobile Engineering from Tribhuvan University, Nepal. Her academic path is marked by merit scholarships, fellowships, and an impressive research portfolio. Through her studies, she has gained deep expertise in nonlinear systems, control theory, and rehabilitation robotics. Her educational journey reflects a blend of academic rigor and hands-on innovation, both in Nepal and the United States. 🎓🇳🇵

Professional Background

Sujata’s experience ranges from research-intensive roles in the U.S. to industry-level engineering in Nepal. At Auburn, she designs robust control systems for rehabilitation robotics. Before that, she worked as a Warranty Executive at Agni Group and as a Mechanical Design Engineer and Project Supervisor at multiple firms in Kathmandu. Her roles included product design, team leadership, and service engineering. She has also interned at Go Ford, gaining hands-on experience with vehicle diagnostics and maintenance. Her career blends practical skills, technical depth, and global exposure. 🔧🌐📈

Awards and Honors

Sujata has been recognized with prestigious honors like the Presidential Graduate Research Fellowship and EPSCoR Graduate Scholars Program at Auburn University. She received the 100+ Women Strong Travel Fellowship and multiple merit scholarships throughout her undergrad. In Nepal, she secured a national RDI grant and won robotics competitions, including at IIT Bombay and Robotics Association of Nepal. These awards reflect her excellence in academics, leadership, innovation, and her commitment to advancing women and technology in engineering. 🥇🎖️👩‍🏫

Research Focus

Sujata’s research focuses on developing robust and adaptive control strategies using Lyapunov theory, deep neural networks, and concurrent learning. Her work addresses challenges in uncertain, nonlinear, and switched dynamic systems with applications in rehabilitation robotics, such as exoskeleton control, and networked control systems. She integrates artificial intelligence and control theory to build systems that are intelligent, responsive, and resilient. Her innovative research aims to enhance human-robot interaction, particularly for medical and assistive technologies. 🤖📊🧠

Publication Top Notes

📘 Robust Control of a Nonsmooth or Switched Control Affine Uncertain Nonlinear System Using a Novel RISE-Inspired Approach
 Year: 2023 | Cited by: 4

🦿 Deep Neural Network Based Saturated Adaptive Control of Muscles in a Lower-Limb Hybrid Exoskeleton
 Year: 2023 | Cited by: 2

🧠 Neuromuscular Model-free Epistemic Risk Guided Exploration (NeuroMERGE) for Safe Autonomy in Human-Robot Interaction
 Year: 2024 | Cited by: 1

⚙️ RISE-Like Saturated Control for Non-Smooth and Switched Non-Linear Systems
 Year: 2023 | Cited by: 1

Conclusion

Sujata Basyal is an outstanding emerging researcher whose academic journey, innovative contributions, and community engagement collectively mark her as a highly deserving candidate for the Best Researcher Award. With a strong academic foundation through her ongoing Ph.D. and prior M.S. in Mechanical Engineering from Auburn University, her work focuses on nonlinear control, rehabilitation robotics, and neural networks—fields at the forefront of engineering innovation. She has authored 3 journal papers and 18+ conference publications in top-tier venues like ACC, CDC, ICORR, and IMECE, showcasing both depth and breadth of research. Her work on adaptive and Lyapunov-based control strategies not only advances theory but also translates into impactful real-world applications such as hybrid exoskeleton systems. Recognized through prestigious fellowships like the Presidential Graduate Research Fellowship and the EPSCoR GRSP, Sujata has also demonstrated excellence through national and international robotics awards. Her leadership roles, mentoring, and active membership in organizations like ASME and SWE underscore a commitment to academic, professional, and community development. In every dimension—scholarship, innovation, leadership, and impact—Sujata Basyal exemplifies the caliber of a Best Researcher Award recipient.

Lei Ren | Electronic Devices | Best Researcher Award

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Dr. Lei Ren | Electronic Devices | Best Researcher Award

Lecturer at Nantong university, China

Lei Ren  was born in Jiangsu Province, China, in 1991. He earned his B.S. and Ph.D. in Electrical Engineering from Nanjing University of Aeronautics and Astronautics (NUAA) in 2013 and 2019. Currently, he serves as a Lecturer at the School of Electrical and Automation, Nantong University . His research focuses on static inverters  and condition monitoring of power electronic converters . With multiple publications in top IEEE journals , his work contributes to advancements in power electronics and energy efficiency. His expertise in converter design and health monitoring continues to impact the field of electrical engineering. 🚀

Publication Profile

Orcid

Academic Background

Lei Ren embarked on his academic journey in Electrical Engineering  at Nanjing University of Aeronautics and Astronautics (NUAA) 🏫, Nanjing, China. He earned his Bachelor of Science (B.S.) degree in 2013 , laying a strong foundation in the field. Driven by a passion for innovation and research, he pursued a Ph.D. at the same university, successfully completing it in 2019 . His academic achievements reflect his dedication to advancing power electronics  and electrical engineering. Through rigorous studies and research, he continues to contribute to technological advancements in the field. 🚀

Professional Background

Lei Ren is a dedicated Lecturer at the School of Electrical and Automation, Nantong University , where he imparts knowledge and inspires future engineers. His research focuses on static inverters  and the condition monitoring of power electronic converters , aiming to enhance efficiency and reliability in power systems. Passionate about innovation, he explores advanced techniques to improve energy conversion and system diagnostics . Through his academic and research contributions , he plays a vital role in shaping the future of electrical engineering, fostering technological advancements, and mentoring the next generation of engineers. 🚀

Research Focus

Lei Ren is actively engaged in research on static inverters  and condition monitoring of power electronic converters . His work focuses on improving energy efficiency and system reliability. He has published several high-impact papers in prestigious journals, including the IEEE Transactions on Power Electronics and IET Power Electronics 📖. His studies cover topics such as transformerless high-gain converters, capacitor voltage regulation, and health monitoring of power transistors. Through his innovative research, Lei Ren contributes to advancements in power electronics, enhancing the performance and sustainability of modern electrical systems. 🚀

Publication Top Notes

 

1️⃣ Capacitor Voltage Regulation Strategy for 7-Level Single DC Source Hybrid Cascaded Inverter ⚡📖
Year: 2022 | IEEE Journal of Emerging and Selected Topics in Power Electronics

2️⃣ Self-Adaption Dead-Time Setting for the SiC MOSFET Boost Circuit in the Synchronous Working Mode 🔧🔋
Year: 2022 | IEEE Access

3️⃣ Transformer-Less High Gain Three-Port Converter With Low Voltage Stress and Reduced Switches for Standalone PV Systems ☀️⚙️
Year: 2022 |  IEEE Transactions on Power Electronics

4️⃣ A Series Incremental Inductance Detection Based Sensorless Startup Method for DSEM ⚙️🔍
Year: 2021 |  IEEE Transactions on Industrial Electronics

5️⃣ Parameter Identification Based on Linear Model for Buck Converters ⚡📊
Year: 2021 |  Electrical Engineering

Conclusion

Lei Ren is a highly qualified researcher in power electronics with strong technical expertise and impactful publications. His work on inverters and power monitoring systems is significant for modern energy applications. To further strengthen his eligibility for the Best Researcher Award, he could expand collaborations, increase research citations, and take on leadership roles in funded projects. Given his current contributions, he is a strong candidate for the award.

 

 

 

Santos Kumar Das | Engineering | Best Researcher Award

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Dr. Santos Kumar Das | Engineering | Best Researcher Award

Associate Professor at National Institute of Technology Rourkela, India

Dr. Santos Kumar Das, an Associate Professor at the Department of Electronics and Communication Engineering, National Institute of Technology (NIT) Rourkela, is an accomplished researcher with expertise in AI, IoT, Sensor Networking, and Optical Networking, including LiFi, FSO, and SDN. With a Ph.D. in Communication Networks from NIT Rourkela and an M.S. in Electrical Communication Engineering from IISc Bangalore, Dr. Das has an extensive academic and professional background. He has supervised 12 Ph.D., 53 M.Tech., and 54 B.Tech. theses and managed numerous government-funded research projects totaling over ₹671 lakh. A recipient of multiple awards, including the Best Research Paper Award at IoTCloud’21 and INDICON 2023, he has over 50 journal publications. Dr. Das is actively involved in academia as a reviewer, technical committee member, and conference session chair. His innovative contributions in 6G communication and IoT for societal applications make him a strong contender for the Best Researcher Award.

Professional Profile

Education

Dr. Santos Kumar Das has an impressive educational background, marked by a strong foundation in electronics and communication engineering. He completed his Ph.D. in Communication Networks from the National Institute of Technology (NIT), Rourkela, in 2014. Prior to that, he earned a Master of Science (M.S.) in Electrical Communication Engineering from the prestigious Indian Institute of Science (IISc), Bangalore, in 2002, graduating with first-class honors. Dr. Das also holds a Bachelor of Engineering (B.E.) degree in Electronics and Communication from VSSUT (formerly UCE), Burla, Odisha, completed in 1998, where he again achieved first-class honors. His academic journey began with a strong foundation in science during his higher secondary education at D.D. College, Keonjhar, Odisha, where he secured first-class marks. With this comprehensive educational background, Dr. Das has built a distinguished career in research and teaching, focusing on cutting-edge technologies in communications and networking.

Professional Experience

Dr. Santos Kumar Das has a diverse and extensive professional experience spanning academia, industry, and research. Currently serving as an Associate Professor at the Department of Electronics and Communication Engineering at NIT Rourkela since 2009, he has significantly contributed to the institution’s academic and research initiatives. Prior to his academic career, Dr. Das gained substantial industry experience as a Senior Software Engineer at Palvision and ITXpress in Singapore, where he worked on cutting-edge network systems and software development. He also held roles as a Software Engineer at Actatek and Network Engineer at Netmarks, contributing to advanced technological solutions in various sectors. In addition, Dr. Das worked as a Research Associate at CEMNet Lab, NTU Singapore, and as a Research Engineer at A-Star Singapore, where he was involved in high-impact research in communication networks and sensor technologies. His broad range of roles has enriched his expertise and research focus, particularly in IoT, AI, and Optical Networking.

Research Interest

Dr. Santos Kumar Das has a broad and innovative research focus, primarily centered around emerging technologies in communications and networking. His key research interests include Artificial Intelligence (AI), the Internet of Things (IoT), Sensor Networking, and Optical Networking, particularly focusing on cutting-edge technologies like LiFi, Free-Space Optics (FSO), and Software-Defined Networking (SDN). Dr. Das explores the integration of AI in IoT applications, aiming to enhance the intelligence and efficiency of network systems. His work in optical networking focuses on leveraging advanced communication techniques for high-speed data transmission and next-generation wireless systems, with a special emphasis on 6G communication technologies. He also investigates IoT-based smart city applications, environmental monitoring systems, and industrial IoT for better security, safety, and resource management. By combining AI with sensor networks and optical technologies, Dr. Das contributes to the development of sustainable, intelligent, and high-performance communication systems for both industrial and societal applications.

Award and Honor

Dr. Santos Kumar Das has received numerous prestigious awards and honors throughout his career, reflecting his excellence in research, teaching, and professional contributions. He was recognized as a Senior Member of IEEE in 2019, showcasing his standing in the global engineering community. Dr. Das has received multiple Best Paper Awards, including at the International Conference on Next Generation Computing Technologies (NGCT) in 2017, Electronic Systems and Intelligent Computing (ESIC) in 2020, and IoTCloud’21, III T Kottayam in 2021. He was also honored with the Best Faculty Advisor Award at NIT Rourkela in 2022 and 2023 for his outstanding guidance to students. Dr. Das’s leadership and contributions to academic committees have earned him recognition as an editorial board member and reviewer for multiple journals. Additionally, his involvement in technical committees and chairing sessions at international conferences, such as TENCON 2023 and SGCNSP 2023, further exemplify his significant impact in the field of engineering and technology.

Conclusion

Dr. Santos Kumar Das stands out as a highly accomplished researcher with a stellar record in academia, research, and mentorship. His contributions to IoT, AI, and advanced networking, coupled with his leadership in projects and professional service, make him an outstanding candidate for the Best Researcher Award. Addressing minor areas for improvement, such as broadening his research scope and enhancing global collaboration, could further solidify his position as a leader in the field. Overall, he is highly deserving of this recognition.

Publications Top Noted

  • A comprehensive review on deep learning-based methods for video anomaly detection
    Authors: R Nayak, UC Pati, SK Das
    Journal: Image and Vision Computing
    Year: 2021
    Citations: 268
  • Time series based air pollution forecasting using SARIMA and prophet model
    Authors: KKR Samal, KS Babu, SK Das, A Acharaya
    Conference: Proceedings of the 2019 International Conference on Information Technology
    Year: 2019
    Citations: 158
  • Multi-directional temporal convolutional artificial neural network for PM2.5 forecasting with missing values: A deep learning approach
    Authors: KKR Samal, KS Babu, SK Das
    Journal: Urban Climate
    Year: 2021
    Citations: 74
  • An improved pollution forecasting model with meteorological impact using multiple imputation and fine-tuning approach
    Authors: KKR Samal, AK Panda, KS Babu, SK Das
    Journal: Sustainable Cities and Society
    Year: 2021
    Citations: 47
  • Temporal convolutional denoising autoencoder network for air pollution prediction with missing values
    Authors: KKR Samal, KS Babu, SK Das
    Journal: Urban Climate
    Year: 2021
    Citations: 44
  • Swin transformer based vehicle detection in undisciplined traffic environment
    Authors: P Deshmukh, GSR Satyanarayana, S Majhi, UK Sahoo, SK Das
    Journal: Expert Systems with Applications
    Year: 2023
    Citations: 42
  • Critical review on slope monitoring systems with a vision of unifying WSN and IoT
    Authors: DK Yadav, S Jayanthu, SK Das, S Chinara, P Mishra
    Journal: IET Wireless Sensor Systems
    Year: 2019
    Citations: 36
  • Multi-output TCN autoencoder for long-term pollution forecasting for multiple sites
    Authors: KKR Samal, AK Panda, KS Babu, SK Das
    Journal: Urban Climate
    Year: 2021
    Citations: 35
  • Video-based real-time intrusion detection system using deep-learning for smart city applications
    Authors: R Nayak, MM Behera, UC Pati, SK Das
    Conference: 2019 IEEE International Conference on Advanced Networks and
    Year: 2019
    Citations: 32
  • A vehicle detection technique using binary images for heterogeneous and lane-less traffic
    Authors: GSR Satyanarayana, S Majhi, SK Das
    Journal: IEEE Transactions on Instrumentation and Measurement
    Year: 2021
    Citations: 31
  • Design of real-time slope monitoring system using time-domain reflectometry with wireless sensor network
    Authors: DK Yadav, G Karthik, S Jayanthu, SK Das
    Journal: IEEE Sensors Letters
    Year: 2019
    Citations: 31
  • Observation of multiphonon transverse wobbling in 133Ba
    Authors: KR Devi, S Kumar, N Kumar, FS Babra, MSR Laskar, S Biswas, S Saha, …
    Journal: Physics Letters B
    Year: 2021
    Citations: 30

Prakash Kharade | Electronics Engineering | Best Faculty Award

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Dr. Prakash Kharade | Electronics Engineering | Best Faculty Award

Dr. Prakash Kharade, Bharati Vidyapeeth College of Engineering Navi Mumbai, India

Dr. Prakash Kharade has over 31 years of academic experience and is the Head of the Electronics and Telecommunication Engineering (ExTC) Department at Bharati Vidyapeeth College of Engineering, Navi Mumbai. He holds a Ph.D. in Power Electronics and has published extensively, including 10 international research papers and multiple conference papers. Dr. Kharade’s research interests include Power Electronics, Analog Electronics, and Control Systems. He is a member of ISTE and has contributed significantly to the growth of his department, overseeing major academic and administrative responsibilities, including NBA accreditation and curriculum development.

Publication Profile

Google Scholar

Professional Experience 🏫💼

Dr. Prakash Kharade brings over 31 years of professional experience at Bharati Vidyapeeth, where he has contributed significantly to the academic and research advancements in Power Electronics, Analog Electronics, and Control Systems. Throughout his career, Dr. Kharade has demonstrated excellence in teaching, mentoring students, and conducting impactful research. His long tenure at the institution reflects his dedication to fostering innovation and advancing knowledge in the field of electronics and control systems, while continually striving for excellence in both academic and professional settings. 👨‍🏫🔧🌟

 

Educational Qualifications 🎓📚

Dr. Prakash Kharade has a solid academic foundation, earning a Ph.D. in February 2022 from Shivaji University. He completed his M.E. in May 2000, also from Shivaji University, securing a 1st Class with distinction and a remarkable 71%. His B.E. degree, awarded by Pune University in December 1992, was earned with 54% and a 2nd Class distinction. Additionally, he holds a DEE degree with a 1st Class with Distinction from the Maharashtra State Board of Technical Education in May 1988, and completed his SSC in May 1984 with 72.71% from the Maharashtra State Board. 🎓🌟

 

Achievements 🏆🎯

Dr. Prakash Kharade has made remarkable contributions throughout his career. In the academic year 2012-2013, he successfully increased the intake of his department from 60 to 120 students, reflecting his commitment to expanding educational opportunities. He has also played a key role in securing NBA accreditation for the Electronics and Telecommunication Engineering Department on three separate occasions—August 2018, June 2021, and June 2022, ensuring accreditation until June 2025. Furthermore, under his leadership, the department achieved 100% admission in the academic years 2021-22, 2022-23, and 2023-24, showcasing his dedication to academic excellence. 🎓✨

 

Research Focus

Dr. Prakash Kharade specializes in Power Electronics, Analog Electronics, and Control Systems. With a profound understanding of electrical systems, he focuses on the development and optimization of power conversion techniques, circuit designs, and control algorithms. His work explores innovative solutions for enhancing energy efficiency, system reliability, and performance in various applications. Additionally, Dr. Kharade’s research contributes to advancements in analog circuit designs, power management, and automated control systems, making him a key figure in these engineering disciplines. His expertise is instrumental in shaping the future of sustainable and efficient electronic technologies. 🌍🔋

 

Publications 📚📈

  • “P F improvement in single-phase high power rectifiers with interleaved boost topology” – Cited by: 4 – Year: 2017
  • “Current Controlled Single-Phase Interleaved Boost Converter with Power Factor Correction” – Cited by: 3 – Year: 2016
  • “Yolov4-based hybrid feature enhancement network with robust object detection under adverse weather conditions” – Cited by: 2 – Year: 2024
  • “Part One: Stability Analysis of Hydrogen-CNG Powered Vehicle” – Cited by: 1 – Year: 2023
  • “Design and Control of High-Power Density Converters with Power Factor Correction Using Multilevel Rectifiers” – – Year: 2024
  • “Modelling and Comparative Analysis for Residual Heat Removal Thermosyphon Heat Transport Devices in Thorium Fuelled PWR”- Year: 2024
  • “Part Two: Neural Network Controller for Hydrogen-CNG Powered Vehicle”- Year: 2024
  • “Co-Simulation of IBC Type PFC Converter with Fuzzy Logic Controller” – Year: 2021
  • “Performance analysis of high power PF corrector by co-simulation using PSIM and Matlab/Simulink”  – Year: 2020
  • “Performance Analysis Of High Power PF Corrector By Co-Simulation Using PSIM And Matlab/Simulink”  – Year: 2020