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


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Featured Publications

 

Keabetsoe Manosa | Chemical Engineering | Young Researcher Award

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Mr. Keabetsoe Manosa | Chemical Engineering
| Young Researcher Award

Mersin University | Turkey

Mr. Keabetsoe Manosa  study investigates the hydrogen-storage potential of AB₂-type cluster systems based on Magnesium–Titanium (Mg–Ti) and Magnesium–Nickel (Mg–Ni), focusing on their economic feasibility, effectiveness, safety profile, and proximity to optimal thermodynamic and physicochemical conditions for maximum hydrogen retention. The research evaluates key material parameters including enthalpy of formation, activation energy, hydride stability, charge distribution, atomic radii compatibility, and lattice behavior under varying temperature–pressure conditions. Comparative computational analyses reveal how alloying magnesium with transition metals enhances hydrogen diffusion pathways, reduces desorption barriers, and influences reversible storage capacity. The Mg–Ti system is examined for its lightweight composition, favorable thermodynamic window, and potential cost efficiency, while the Mg–Ni system is assessed for catalytic enhancement, structural robustness, and effective hydrogen absorption–desorption kinetics. The study integrates principles of materials thermodynamics, solid-state chemistry, and cluster theory to determine which system aligns more closely with optimal storage metrics required for scalable applications in clean-energy technologies. Overall, the analysis provides insight into the tunability of Mg-based alloys, highlighting their comparative strengths and limitations in meeting industrial hydrogen-storage demands and contributing to the broader pursuit of high-performance, safe, and economically viable energy-storage materials.

Featured Publications

Manosa, K. (2025, July 30). The comparison in the degree of economic feasibility, effectiveness, safety and the proximity to the optimum conditions needed for the maximum storage of hydrogen gas in AB₂-type cluster systems of Magnesium–Titanium and Magnesium–Nickel based on the relevant physical and chemical properties: The Mpoetsi Manosa study (Version 2) [Preprint]. ChemRxiv. https://doi.org/10.26434/chemrxiv-2025-wkpn4-v2

Manosa, K. (2025, June 23). The comparison in the degree of economic feasibility, effectiveness, safety and the proximity to the optimum conditions needed for the maximum storage of hydrogen gas in AB₂-type cluster systems of Magnesium–Titanium and Magnesium–Nickel based on the relevant physical and chemical properties: The Mpoetsi Manosa study [Preprint]. ChemRxiv. https://doi.org/10.26434/chemrxiv-2025-wkpn4

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.

Yunwen Xu | Engineering | Best Researcher Award

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Dr. Yunwen Xu l Engineering
| Best Researcher Award

Shanghai Jiao Tong University | China

Dr. Yunwen Xu’s research focuses on advancing intelligent transportation systems, autonomous driving control, and predictive control for complex and embedded systems. Her innovative work integrates graph-based spatial-temporal modeling, data-driven control algorithms, and real-time optimization to enhance vehicle trajectory prediction, traffic signal management, and collaborative control in large-scale dynamic environments. Through over 50 high-impact publications, including 15 in top-tier journals and several ESI highly cited papers, Dr. Xu has significantly contributed to the theoretical and practical foundations of predictive control and intelligent mobility. Her research achievements include developing FPGA-based predictive controllers, robust model predictive frameworks, and reinforcement learning-based control systems for V2X-enabled autonomous vehicles. By leading national and provincial research projects and collaborating internationally with institutions like Purdue University and industrial partners such as Shanghai Electric Wind Power Group, she bridges the gap between academic innovation and industrial application. Her patents and successful technology transfers in microgrid energy management and advanced temperature control demonstrate the translational strength of her research. Recognized with prestigious honors, including the Best Paper Award at the Chinese Process Control Conference and championship at the Autonomous Driving Algorithm Challenge, Dr. Xu continues to pioneer next-generation control and automation technologies that drive the evolution of intelligent, efficient, and sustainable transportation ecosystems.

Profile:  Google Scholar 

Featured Publications

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/

Pedro Pitrez | Engineering | Best Researcher Award

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Assist. Prof. Dr. Pedro Pitrez | Engineering | Best Researcher Award

Assist. Prof. Dr. Pedro Pitrez  at Assistente Convidado – FEUP , Portugal

Pedro Pitrez is a Mechanical Engineer specializing in thermal energy and internal combustion engine systems. He holds a Master’s degree and is currently completing his Ph.D. at FEUP, focusing on energy systems and mechanical engineering. Pitrez has extensive experience in both academia and industry, with a passion for research, development, and teaching. He has worked as a lecturer at UTAD and FEUP, teaching subjects such as Applied Thermodynamics and Mechanics. His professional journey includes working at INEGI, where he developed a machine for cork painting, and at EDP Geração, managing operations for hydroelectric power plants. Known for his technical expertise, Pitrez combines his engineering knowledge with a drive for innovation, contributing to various research projects, academic articles, and conferences.

Publication Profile

Scopus

🎓 Education

Pedro Pitrez’s educational background includes a Bachelor’s degree in Mechanical Engineering from UTAD, followed by a Master’s degree in Mechanical Engineering from FEUP. His Ph.D. work at FEUP focuses on the areas of energy systems and combustion. Pitrez has excelled in his academic career, achieving strong results with a Master’s thesis on preparing a Porsche 911 internal combustion engine for competition. His academic training also includes specialized research in thermal energy, reflected in his current work and studies. Furthermore, he has contributed significantly to educational platforms, having taught courses such as Applied Thermodynamics II and Mechanics III. His current research at FEUP and INEGI is an embodiment of his continuous pursuit of knowledge and advancement in the field of mechanical and energy engineering.

💼 Experience

Pedro Pitrez has an extensive professional background in both academia and industry. From March 2020 to August 2022, he worked as a researcher at INEGI, where he was involved in the development of industrial machines, including a machine for cork painting. He was responsible for designing the machine’s structure and transport systems, as well as creating the control software. Additionally, Pitrez gained valuable experience in teaching at FEUP, offering courses in thermodynamics and mechanics. He has also worked at Amorim Cork Composites, where he provided academic support, including practical classes and student supervision. His professional career also includes working at EDP Geração, where he currently holds a position as an engineer in charge of planning and operations for hydroelectric power plants. Pitrez’s broad experience and academic contributions make him a well-rounded professional in mechanical engineering and energy systems.

🏆 Awards & Honors

Pedro Pitrez has received numerous accolades for his contributions to research and academia. Notably, he won the Best Paper Award at the International Conference on Technologies and Materials for Renewable Energy, Environment, and Sustainability (TMREES23) in 2023. His research work on plasma gasification and energy systems optimization has earned him recognition in both academic and professional circles. Additionally, Pitrez has presented at several high-profile conferences, such as the VII Jornadas de Engenharia Mecânica UTAD and the International Conference on Renewable Energy and Sustainability (TMREES23). His academic journey has been marked by consistent excellence, having also contributed to published articles in reputable journals such as Energy Reports and ENCIT 2020. These awards and honors reflect his impact and dedication to advancing research in mechanical engineering and sustainable energy solutions.

🔍 Research Focus

Pedro Pitrez’s research primarily focuses on energy systems, combustion processes, and sustainable energy technologies. His current work includes investigating plasma gasification for hazardous waste treatment and optimizing energy conversion processes. He has developed expertise in the numerical analysis of energy systems and the efficient production of syngas. His research is highly interdisciplinary, bridging mechanical engineering with environmental sustainability. Pitrez is particularly focused on applying energy optimization to industrial processes, as evidenced by his work on internal combustion engines and hydroelectric power plants. Additionally, his ongoing Ph.D. research explores the potential of alternative fuels in the transportation and energy sectors. His work contributes to the development of cleaner, more efficient energy systems, with practical applications in industries such as automotive, power generation, and environmental technologies. Pitrez’s dedication to advancing energy solutions aligns with his long-term vision of sustainable and efficient mechanical systems.

Publication Top Notes

  • Energy Recovery from Infectious Hospital Waste and Its Safe Neutralization

    • Authors: P. Pitrez, Pedro; E.L.M. Monteiro, Eliseu L.M.; A.I. Rouboa, Abel Ilah
    • Citations: 0 (as it is a forthcoming publication)
    • Year: 2025
    • Journal: International Journal of Hydrogen Energy

  • Numerical Analysis of Plasma Gasification of Hazardous Waste Using Aspen Plus

    • Authors: Not provided in the reference.
    • Citations: 0
    • Year: 2023
    • Journal: Energy Reports
    • Volume: 9, Pages 418-426

  • Optimization of Plasma Gasification System for Treatment of COVID-19 Hazardous Waste for Valorization of LHV and H2 Composition

    • Authors: Not provided in the reference.
    • Citations: 0
    • Year: In Review (no specific year yet)
    • Journal: Status: In Review

 

Rayk Fritzsche | Engineering | Best Scholar Award

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Dr. Rayk Fritzsche | Engineering | Best Scholar Award

Gruppenleiter at Fraunhofer IWU, Germany

Dr.-Ing. Rayk Fritzsche is a distinguished researcher and group leader at Fraunhofer IWU, specializing in adaptable assembly systems and intelligent manufacturing. With a Dr.-Ing. (magna cum laude) from TU Dresden, he has made significant contributions to automation, AI-driven assembly, and car body manufacturing. His six patents and numerous peer-reviewed publications in CIRP, IEEE, and Automatica highlight his innovative work in industrial automation. Dr. Fritzsche’s research integrates artificial intelligence, robotics, and software-assisted design, making impactful advancements in automotive, aerospace, and fuel cell production. His Best Paper Award at CIRP ICME 2022 underscores his excellence in academic contributions. Beyond research, his leadership at Fraunhofer IWU and collaborations with industry leaders drive innovation in smart manufacturing. To further enhance his global recognition, expanding interdisciplinary projects and academic mentorship could elevate his influence in the field. His expertise and contributions make him a strong candidate for the Best Scholar Award.

Professional Profile

Education

Dr. Rayk Fritzsche’s educational journey reflects a blend of athletic excellence and academic rigor. He graduated from the Sportgymnasium Chemnitz with an Abitur in 1996, after years of pursuing speed skating at a competitive level. Following this, he transitioned into mechanical engineering, earning a Dipl.-Ing. degree from TU Chemnitz in 2009, specializing in construction and drive technology. His academic path was marked by internships and practical experiences, including at BMW and IAV GmbH, where he gained hands-on exposure to quality management and powertrain development. Dr. Fritzsche’s commitment to further education led him to pursue a doctoral degree at TU Dresden, where he successfully completed his dissertation in 2022 with the distinction magna cum laude. His thesis focused on adaptable assembly systems, solidifying his expertise in advanced manufacturing technologies and positioning him as a leader in the field of intelligent production systems.

Professional Experience

Dr. Rayk Fritzsche has had a distinguished career at Fraunhofer IWU, where he has held several key positions since 2009. After starting as an assistant scientist in 2009, he quickly advanced to become a research associate and later a group leader in the Assembly Systems Department, focusing on body construction and assembly. By 2018, he was appointed deputy head of the department, leading research in adaptable assembly systems. Dr. Fritzsche’s leadership culminated in his current role as group leader in charge of adaptable assembly systems at Fraunhofer IWU. His professional experience is complemented by valuable internships and roles at BMW Leipzig and IAV GmbH, where he focused on quality management and powertrain development. Throughout his career, Dr. Fritzsche has consistently contributed to cutting-edge research and technological advancements in intelligent manufacturing, automation, and AI-driven assembly systems, influencing both industry and academia.

Research Interest

Dr. Rayk Fritzsche’s research interests focus on advancing intelligent manufacturing and automation technologies with a particular emphasis on adaptable assembly systems. He is deeply engaged in the integration of artificial intelligence and robotics into industrial production, aiming to enhance flexibility, efficiency, and precision in assembly processes. His work addresses key challenges in automated fixture design, utilizing software-supported systems for positioning and clamping in car body manufacturing. Additionally, Dr. Fritzsche explores the use of mathematical algorithms and geometry-based search methods to optimize production workflows and reduce resource consumption. His research also extends to advanced AI applications, including machine learning for optimizing assembly system configurations and leveraging virtual reality and augmented reality for real-time process improvements. Dr. Fritzsche’s interests span across high-rate production, fuel cell manufacturing, and bio-inspired design, positioning him at the forefront of innovation in smart and sustainable manufacturing.

Award and Honor

Dr. Rayk Fritzsche has received several notable awards and honors in recognition of his groundbreaking contributions to intelligent manufacturing and automation. One of his most distinguished accolades is the Best Paper Award in 2022 at the CIRP ICME Conference, for his innovative work on software-assisted clamping point classification and position optimization for flexible car body fixtures. This recognition highlights his excellence in applying mathematical geometry-based algorithms to optimize production processes. In addition to this prestigious award, Dr. Fritzsche holds multiple patents for his inventions in automated fixture systems and adaptable assembly technologies, underscoring his impact on the industrial sector. His extensive contributions to both academic and practical advancements in automation, robotics, and AI in manufacturing have earned him recognition as a leader in his field. Dr. Fritzsche’s work continues to influence manufacturing practices, ensuring his place among top researchers in industrial engineering.

Conclusion

Dr. Rayk Fritzsche is highly suitable for the Best Scholar Award due to his strong research output, patents, industry impact, and academic excellence. His contributions to intelligent manufacturing, automation, and AI-driven assembly systems place him among top scholars in his field. While already highly accomplished, expanding international collaboration and interdisciplinary research could further enhance his scholarly profile.

Publications Top Noted

  • Title: Computer-based design and development of a fully automated assembly of aircraft doors made of thermoplastic composite material
    Authors: Fritzsche, R., Jäger, E.
    Year: 2024
    Citations: 0
  • Title: Development of a suction gripper network based on the biological role model of an octopus
    Authors: Fritzsche, R., Kunze, H., Jäger, E.
    Year: 2024
    Citations: 0
  • Title: Autonomous assembly and disassembly by cognition using hybrid assembly cells
    Authors: Frieß, U., Oberfichtner, L., Hellmich, A., Fritzsche, R., Ihlenfeldt, S.
    Year: 2023
    Citations: 0
  • Title: Software support for the development of flexible plant technology in highly automated and high-rate body-in-white production
    Authors: Fritzsche, R., Ahrens, A.
    Year: 2023
    Citations: 0
  • Title: Autonomous assembly and disassembly – Key technologies and links for the adaptive self-optimization of future circular production
    Authors: Ihlenfeldt, S., Lorenz, M., Frieß, U., Fritzsche, R.
    Year: 2023
    Citations: 0
  • Title: Automated gripper design | DesignAssistant – multikriterielle optimierte Konstruktion mit digitalen Baukästen Automatisierter Greiferentwurf
    Authors: Ahrens, A., Oberfichtner, L., Richter-Trummer, V., Frieß, U., Ihlenfeldt, S.
    Year: 2022
    Citations: 0
  • Title: Solving a multi-dimensional matching problem for grouping clamping points on car body parts
    Authors: Oberfichtner, L., Ahrens, A., Fritzsche, R., Richter-Trummer, V., Todtermuschke, M.
    Year: 2022
    Citations: 3
  • Title: Software assisted clamping point classification and position optimization for the efficient flexibilization of carbody fixtures using mathematical geometry-based search algorithms
    Authors: Fritzsche, R., Schaffrath, R., Todtermuschke, M.
    Year: 2021
    Citations: 4
  • Title: Automated design of product-flexible car body fixtures with software-supported part alignment using particle swarm optimization
    Authors: Fritzsche, R., Voigt, E., Schaffrath, R., Todtermuschke, M., Röber, M.
    Year: 2020
    Citations: 9
  • Title: Hololens AR-using vuforia-based marker tracking together with text recognition in an assembly scenario
    Authors: Knopp, S., Klimant, P., Schaffrath, R., Fritzsche, R., Allmacher, C.
    Year: 2019
    Citations: 11

 

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