Liu Zhemin | Protein Engineering | Best Researcher Award

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Dr. Liu Zhemin | Protein Engineering | Best Researcher Award

Senior Scientist at Nanjing Vazyme Biotechnology Company, China

πŸ”¬πŸŽ“ Dr. Z. Liu is a distinguished scientist specializing in enzyme engineering and microbial biotechnology. With expertise in protein rational design, directed evolution, and computational modeling, he focuses on developing high-performance enzymes for industrial and medical applications. A prolific researcher and innovator, Dr. Liu integrates cutting-edge techniques like CRISPR-assisted rational design and cooperative substitution methods to advance enzymology. πŸŒŸπŸ“ˆπŸ‘¨β€πŸ”¬

Publication Profile :Β 

Scopus

Educational Background πŸŽ“

Z. Liu has a strong academic foundation in biochemistry and molecular biology, with advanced training in enzyme engineering and microbial biotechnology. His education laid the groundwork for his expertise in protein design, directed evolution, and enzyme applications.

Professional Experience πŸ’Ό

Z. Liu is a leading researcher and academic in the fields of enzyme engineering and microbial biotechnology. He has contributed extensively to the design and optimization of enzymes for industrial and therapeutic applications, including the development of high-stability enzymes and efficient expression systems in microbial hosts such as Pichia pastoris. His professional work includes the rational design of enzymes using surface charge modifications, directed evolution for improved catalytic properties, and genome editing to enhance enzyme functionality. His research spans collaborations with industry and academia, focusing on practical solutions for enzyme stability, catalytic efficiency, and prebiotic preparation.

Research Interests πŸ”¬

Z. Liu’s research is centered on:

  • Rational Protein Design: Enhancing enzyme stability and activity using computational modeling and experimental methods.
  • Directed Evolution: High-throughput screening and mutagenesis to optimize enzyme performance.
  • Microbial Biotechnology: Developing superior expression systems in microbes like Pichia pastoris for large-scale enzyme production.
  • Enzyme Applications: Innovations in the preparation of prebiotic mannooligosaccharides and other industrial applications.
  • Thermostable Enzymes: Engineering enzymes for high-temperature and low-pH conditions.

Publications πŸ“š

  • Z. Liu, X. Fu, M. Yuan, Q. Liang, C. Zhu, H. Mou, Surface charged amino acid-based strategy for rational engineering of kinetic stability and specific activity of enzymes: Linking experiments with computational modeling. Int. J. Biol. Macromol. 182, 228–236 (2021).
  • M. Wu, L. Cao, W. Tang, Z. Liu*, S. Feng, Improving the anti-autolytic ability of alkaline protease from Bacillus alcalophilus by a rationally combined strategy. Enzyme Microb. Technol., 110561 (2024).
  • Z. Liu, L. Cao, X. Fu, Q. Liang, H. Sun, H. Mou, *A multi-functional genetic manipulation system and its use in high-level expression of a Ξ²-mannanase mutant with high specific activity in Pichia pastoris. Microb. Biotechnol. 14, 1525–1538 (2021).
  • W. Zhang#, Z. Liu#, S. Zhou, H. Mou, R. Zhang, Cloning and expression of a Ξ²-mannanase gene from Bacillus sp. MK-2 and its directed evolution by random mutagenesis. Enzyme Microb. Technol. 124, 70–78 (2019).
  • Z. Liu, C. Ning, M. Yuan, X. Fu, S. Yang, X. Wei, M. Xiao, H. Mou, C. Zhu, High-efficiency expression of a superior Ξ²-mannanase engineered by cooperative substitution method in Pichia pastoris and its application in preparation of prebiotic mannooligosaccharides. Bioresour. Technol. 311, 123482 (2020).
  • Z. Liu, L. Cao, X. Fu, Q. Liang, H. Sun, H. Mou, *A multi-functional genetic manipulation system and its use in high-level expression of a Ξ²-mannanase mutant with high specific activity in Pichia pastoris. Microb. Biotechnol. 14, 1525–1538 (2021).
  • Q. Liang, L. Cao, C. Zhu, Q. Kong, H. Sun, F. Zhang, H. Mou, Z. Liu*, *Characterization of recombinant antimicrobial peptide BMGlv2 heterologously expressed in Trichoderma reesei. Int. J. Mol. Sci. 23 (2022). doi:10.3390/ijms231810291.
  • W. Zhang#, Z. Liu#, S. Zhou, H. Mou, R. Zhang, Cloning and expression of a Ξ²-mannanase gene from Bacillus sp. MK-2 and its directed evolution by random mutagenesis. Enzyme Microb. Technol. 124, 70–78 (2019).
  • Z. Liu, C. Ning, M. Yuan, X. Fu, S. Yang, X. Wei, M. Xiao, H. Mou, C. Zhu, High-efficiency expression of a superior Ξ²-mannanase engineered by cooperative substitution method in Pichia pastoris and its application in preparation of prebiotic mannooligosaccharides. Bioresour. Technol. 311, 123482 (2020).
  • Z. Liu, C. Ning, M. Yuan, S. Yang, X. Wei, M. Xiao, X. Fu, C. Zhu, H. Mou, High-level expression of a thermophilic and acidophilic beta-mannanase from Aspergillus kawachii IFO 4308 with significant potential in mannooligosaccharide preparation. Bioresour. Technol. 295, 122257 (2019).

 

 

 

Hun-Kook Choi | Laser Optics | Best Researcher Award

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Dr. Hun-Kook Choi | Laser Optics | Best Researcher Award

Post. Doc at Gwangju Institute of Science and Technology(GIST), South Korea

Dr. Hun Kook Choi is a dynamic researcher specializing in photonics and laser applications. With expertise in femtosecond laser micromachining, he contributes to innovations in optical devices, fiber sensors, and semiconductor technologies. His collaborative work has been published in leading journals, reflecting his commitment to advancing optical engineering. πŸŒŸπŸ”¬πŸ“‘

Publication Profile :Β 

Scopus

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Educational Background πŸŽ“

Dr. Hun Kook Choi earned his Ph.D. in 2017 from the Department of Photonic Engineering at Chosun University, Gwangju, Republic of Korea. His doctoral research focused on “Characterization and Fabrication of Precise Optical Elements Using Hybrid Laser Processing.”

Professional Experience πŸ’Ό

Dr. Choi is currently a Postdoctoral Researcher at the Optical Application Systems Research Division, Advanced Photonics Research Institute (APRI), Gwangju Institute of Science and Technology (GIST), Republic of Korea. His work involves cutting-edge applications of femtosecond laser systems in fabricating precision optical devices, diffraction optical devices, fiber optic sensors, and semiconductor applications such as bevel etching, DRAM bonding, and Through Glass Via (TGV) processing. His contributions extend to the design and innovation of novel optical and photonic technologies.

Research Interests πŸ”¬

Dr. Choi’s research focuses on:

  • Precision optical devices, including micro-lens arrays (MLA)
  • Diffraction optical elements (DOE)
  • Fiber optic sensors like Fiber Bragg Gratings (FBG)
  • Semiconductor applications leveraging femtosecond lasers
  • Advanced laser processing techniques for glass cutting, micro-structuring, and photonic sensor development.

Publications πŸ“š

  1. Ahsan, M.S., Sohn, I.-B., & Choi, H.-K. (2024). Gorilla Glass Cutting Using Femtosecond Laser Pulse Filaments. Applied Sciences (Switzerland), 14(1), 312.
    (Open access)

  2. Ahsan, S., Arafat, A.I., Akter, T., Sohn, I.-B., & Choi, H.-K. (2024). Light Extraction Efficiency Enhancement of White Organic Light-Emitting Diodes (OLEDs) by Micro/Nano-Patterning the Substrate Layer. Defect and Diffusion Forum, 432, 85–106.

  3. Sohn, I.-B., Choi, H.-K., Jung, Y.-J., Oh, M.-K., & Ahsan, M.S. (2023). Measurement of Fine/Ultrafine Dust Using Lenticular Fiber-Based Particulate Measurement Devices. IEEE Sensors Journal, 23(8), 8400–8409.
  4. Lee, C.J., Choi, H.K., Sohn, I.B., & Ha, J.S. (2023). Laser Micro-Structuring of Super-Hydrophobic Surface for Lotus Effect. Journal of the Korean Society for Precision Engineering, 40(4), 291–299.
  5. Adhikary, A., Ahsan, M.S., Hossain, M.B., Choi, H.-K., & Sohn, I.-B. (2022). Light Intensity and Efficiency Enhancement of n-ZnO/NiO/p-GaN Heterojunction-Based White Light-Emitting Diodes Using Micro-Pillar Array. Journal of Optics (India), 51(3), 526–537.
  6. Choi, H.-K., Jung, Y.-J., Yu, B.-A., Kim, J.-Y., & Ahsan, M.S. (2022). Femtosecond-Laser-Assisted Fabrication of Radiation-Resistant Fiber Bragg Grating Sensors. Applied Sciences (Switzerland), 12(2), 886.
    (Open access)

  7. Lim, K.-D., Choi, H.-K., Sohn, I.-B., Lee, B.-H., & Kim, J.-T. (2021). Fabrication of Lensed Optical Fibers for Biosensing Probes Using CO2 and Femtosecond Lasers. Applied Sciences (Switzerland), 11(9), 3738.
    (Open access)

  8. Lee, S.-B., Jung, Y.-J., Choi, H.-K., Sohn, I.-B., & Lee, J.-H. (2021). Hybrid LPG-FBG Based High-Resolution Micro Bending Strain Sensor. Sensors (Switzerland), 21(1), 1–22.
  9. Shikha, Z.A., Nath, S.K.D., Sikder, N., Choi, H.-K., & Ahsan, M.S. (2021). Demonstration of a 4 Gb/s Wavelength Division Multiplexing Based Li-Fi Network. Proceedings of International Conference on Electronics, Communications and Information Technology (ICECIT).
  10. Shikha, Z.A., Nath, S.K.D., Sikder, N., Choi, H.-K., & Ahsan, M.S. (2021). Development of a Time Division Multiplexing Based Li-Fi System for Voice Communication. Proceedings of International Conference on Electronics, Communications and Information Technology (ICECIT).

 

 

Oana Panazan | Economics | Best Researcher Award

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Dr. Oana Panazan | Economics | Best Researcher Award

Dr at Transylvania University of Brasov, Romania

Dr. Oana Nicoleta Panazan is an academic and researcher at Transylvania University of Brasov, specializing in management, financial markets, and geopolitical risk analysis. With a Ph.D. in Engineering and Management, her research explores the intersection of technology, market behavior, and crisis management, with a focus on financial volatility during global challenges. She has authored numerous books, articles, and conference papers, contributing valuable insights into topics like corporate relocation, economic recovery, and defense industry risks. Her work is at the cutting edge of financial economics, geopolitics, and technological innovation. πŸ“ˆπŸŒπŸ’‘

Publication Profile :Β 

Orcid

Educational Background πŸŽ“

  • Ph.D. in Engineering and Management (2023)
    Transylvania University of Brasov
    Doctoral thesis: “Growth Strategies through Companies Relocation”
  • Master’s in Engineering and Management
  • Bachelor’s in Industrial Engineering

Professional Experience πŸ’Ό

Dr. Oana Nicoleta Panazan is an Associate Professor at the Faculty of Technological Engineering and Industrial Management at Transylvania University of Brasov, Romania. Her academic career has focused on management, industrial engineering, and the analysis of financial markets, particularly in the context of geopolitical risk, technological innovation, and crisis management. Dr. Panazan has contributed significantly to research on corporate relocation, stock market volatility, and the impact of global risks on financial performance. She has been involved in multiple international conferences and published extensively in journals and proceedings.

Her research expertise spans various areas, including geopolitical risk, financial economics, clean energy markets, and the relationship between technology and financial markets. Additionally, she has explored the dynamics of market behavior during crises, such as the COVID-19 pandemic, and its influence on defense industry stocks.

Research Interests πŸ”¬

  • Geopolitical Risk and its effects on financial markets and stock volatility
  • Corporate Relocation strategies and their impact on business performance
  • Clean energy markets and sustainable business models
  • Technological Innovation and its relationship with market performance
  • Crisis Management and economic recovery
  • Financial modeling (AHP, ANP-TOPSIS, EGARCH, Neural Networks)

Publications πŸ“š

  • Article Title: Investigating the effect of geopolitical risk on defense companies’ stock returns
    Journal: Heliyon
    Publication Date: December 2024
    DOI: 10.1016/j.heliyon.2024.e40974
    Contributors: Catalin Gheorghe; Oana Panazan

  • Article Title: Influence of geopolitical risk on stock volatility in the Middle East and North Africa states
    Conference Paper: Business and Management 2024
    Publication Date: September 12, 2024
    DOI: 10.3846/bm.2024.1274
    Contributors: Oana Panazan; Catalin Gheorghe

  • Article Title: Relationship between the dynamics of refugees from Ukraine and the volatility of tourism stocks: a time-frequency analysis
    Conference Paper: Business and Management 2024
    Publication Date: September 12, 2024
    DOI: 10.3846/bm.2024.1157
    Contributors: Catalin Gheorghe; Oana Panazan

  • Article Title: Effect of health system performance on volatility during the COVID-19 pandemic: A neural network approach
    Journal: Journal of Business Economics and Management
    Publication Date: February 28, 2024
    DOI: 10.3846/jbem.2024.21059
    Contributors: Catalin Gheorghe; Oana Panazan

  • Article Title: Impact of geopolitical risk on G7 financial markets: A comparative wavelet analysis between 2014 and 2022
    Journal: Mathematics
    Publication Date: January 24, 2024
    DOI: 10.3390/math12030370
    Contributors: Oana Panazan; Catalin Gheorghe

  • Article Title: Government response stringency index: An alternative for the volatility determining during pandemics
    Conference Paper: Business and Management 2023
    Publication Date: May 11, 2023
    DOI: 10.3846/bm.2023.972
    Contributors: Oana Panazan; Catalin Gheorghe

  • Article Title: Relocation trends determined by increasing risks in Eastern Europe: An ANP-TOPSIS approach
    Journal: Human Systems Management
    Publication Date: May 8, 2023
    DOI: 10.3233/HSM-220062
    Contributors: Oana Panazan; Catalin Gheorghe; Gavrila Calefariu

  • Article Title: Study on the areas affected by the COVID-19 pandemic in Romania
    Conference Paper: 12th International Scientific Conference β€œBusiness and Management 2022”
    Publication Date: May 6, 2022
    DOI: 10.3846/bm.2022.700
    Contributors: Oana Panazan; Catalin Gheorghe

  • Article Title: The influence of specific indicators on the volatility of shares on the Bucharest Stock Exchange during the COVID-19 pandemic
    Conference Paper: 12th International Scientific Conference β€œBusiness and Management 2022”
    Publication Date: May 6, 2022
    DOI: 10.3846/bm.2022.697
    Contributors: Catalin Gheorghe; Oana Panazan

  • Article Title: Model for industrial business relocation in Eastern Europe
    Conference Paper: MATEC Web of Conferences
    Publication Year: 2021
    DOI: 10.1051/matecconf/202134307011
    Contributors: Catalin Gheorghe; Oana Panazan

  • Article Title: Model of indirect expenses distribution for determining economies of scale
    Conference Paper: MATEC Web of Conferences
    Publication Year: 2021
    DOI: 10.1051/matecconf/202134307009
    Contributors: Oana Panazan; Catalin Gheorghe; Gavrila Calefariu

  • Article Title: The methodology of economic recovery of commercial companies in crisis conditions
    Conference Paper: IOP Conference Series: Materials Science and Engineering
    Publication Year: 2021
    DOI: 10.1088/1757-899x/1009/1/012044
    Contributors: Oana Panazan; Catalin Gheorghe; Gavrila Calefariu

  • Article Title: Aspects of risk in the defense industry from Romania
    Journal: RECENT – REzultatele CErcetΔƒrilor Noastre Tehnice
    Publication Date: August 27, 2020
    DOI: 10.31926/recent.2020.60.004
    Contributors: Oana Panazan; Cătălin Gheorghe

 

 

 

Hailong Yan | Energy Storage | Best Researcher Award

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Mr. Hailong Yan | Energy Storage | Best Researcher Award

Professor at Nanyang Normal University, China

Shahzeb Khan πŸŽ“βœ¨ is a passionate Data Scientist and Assistant Professor with a flair for innovation and research. With expertise in AI, ML, and data science, he blends academic rigor with practical problem-solving skills. He has been recognized for his research excellence, including the prestigious Best Researcher Award (2024), and holds qualifications like GATE 2020 and UGC-NET 2023. Beyond his professional pursuits, Shahzeb enjoys reading, writing, cooking, solo traveling, swimming, and singing. πŸŒπŸ“–πŸŽ€

Publication Profile :Β 

Scopus

Educational Background πŸŽ“

Shahzeb Khan is a dedicated Data Scientist and educator with a strong background in information systems analysis, programming, teaching, and research. He earned his M.Tech in Computer Science from Mahatma Gandhi Central University, Bihar, in 2023 with an impressive 8.5 CGPA, after completing his B.Tech from AKTU Uttar Pradesh in 2020 with a 6.8 CGPA. Shahzeb demonstrated academic excellence from an early age, achieving 9.2 CGPA in matriculation (CBSE) in 2013 and 75% in his intermediate studies in 2015.

Professional Experience πŸ’Ό

Shahzeb is currently serving as an Assistant Professor in Computer Science and Applications at Sharda University, Greater Noida, where he teaches Artificial Intelligence, Machine Learning, Big Data Analytics, Data Science, and Data Analytics (since September 2023). His professional journey also includes a web development internship at IIY Software Pvt. Ltd. in 2019 and key coordination roles, such as the TSML (Time Series Machine Learning) Summer Training Program at MGCUB in 2023. Shahzeb is actively involved in conducting workshops and seminars, including those at IIT Delhi, where he engaged in IoT and Machine Learning training.

Research Interests πŸ”¬

Shahzeb’s research interests lie at the intersection of Artificial Intelligence, Machine Learning, Deep Learning, and Statistical Modeling. He is particularly focused on predictive modeling, hybrid model development, and comparative analysis of advanced algorithms for time-series data. His notable work includes a publication on a novel Hybrid GRU-CNN model for PTB diagnostic ECG time series data in the Biomedical Signal Processing and Control journal, which boasts a 5.9 impact factor.

Publications πŸ“š

  1. Khan, S. (2024). A Novel Hybrid GRU-CNN and Residual Bias (RB) Based RB-GRU-CNN Models for Prediction of PTB Diagnostic ECG Time Series Data. Biomedical Signal Processing and Control, Impact Factor: 5.9.

 

 

Shahzeb Khan | AI in Healthcare | Best Researcher Award

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Mr. Shahzeb Khan | AI in Healthcare | Best Researcher Award

Assistant professor at Sharda University, India

Shahzeb Khan πŸŽ“βœ¨ is a passionate Data Scientist and Assistant Professor with a flair for innovation and research. With expertise in AI, ML, and data science, he blends academic rigor with practical problem-solving skills. He has been recognized for his research excellence, including the prestigious Best Researcher Award (2024), and holds qualifications like GATE 2020 and UGC-NET 2023. Beyond his professional pursuits, Shahzeb enjoys reading, writing, cooking, solo traveling, swimming, and singing. πŸŒπŸ“–πŸŽ€

Publication Profile :Β 

Google Scholar

Educational Background πŸŽ“

Shahzeb Khan is a dedicated Data Scientist and educator with a strong background in information systems analysis, programming, teaching, and research. He earned his M.Tech in Computer Science from Mahatma Gandhi Central University, Bihar, in 2023 with an impressive 8.5 CGPA, after completing his B.Tech from AKTU Uttar Pradesh in 2020 with a 6.8 CGPA. Shahzeb demonstrated academic excellence from an early age, achieving 9.2 CGPA in matriculation (CBSE) in 2013 and 75% in his intermediate studies in 2015.

Professional Experience πŸ’Ό

Shahzeb is currently serving as an Assistant Professor in Computer Science and Applications at Sharda University, Greater Noida, where he teaches Artificial Intelligence, Machine Learning, Big Data Analytics, Data Science, and Data Analytics (since September 2023). His professional journey also includes a web development internship at IIY Software Pvt. Ltd. in 2019 and key coordination roles, such as the TSML (Time Series Machine Learning) Summer Training Program at MGCUB in 2023. Shahzeb is actively involved in conducting workshops and seminars, including those at IIT Delhi, where he engaged in IoT and Machine Learning training.

Research Interests πŸ”¬

Shahzeb’s research interests lie at the intersection of Artificial Intelligence, Machine Learning, Deep Learning, and Statistical Modeling. He is particularly focused on predictive modeling, hybrid model development, and comparative analysis of advanced algorithms for time-series data. His notable work includes a publication on a novel Hybrid GRU-CNN model for PTB diagnostic ECG time series data in the Biomedical Signal Processing and Control journal, which boasts a 5.9 impact factor.

Publications πŸ“š

  1. Khan, S. (2024). A Novel Hybrid GRU-CNN and Residual Bias (RB) Based RB-GRU-CNN Models for Prediction of PTB Diagnostic ECG Time Series Data. Biomedical Signal Processing and Control, Impact Factor: 5.9.

 

 

Muhammad Ahsan Saleem | Additive Manufacturing | Best Researcher Award

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Mr. Muhammad Ahsan Saleem | Additive Manufacturing | Best Researcher Award

Ph.D. Student at Nanjing University of Science and Technology, China

Muhammad Ahsan Saleem is an innovative Mechatronics Engineer currently pursuing a Doctorate in Mechanical Engineering at Nanjing University of Science and Technology. With expertise in data-driven applications for 3D printing and machine learning, he works at the cutting edge of material science, electronics, and mechanical systems. Passionate about interdisciplinary collaboration, he applies his technical expertise to solving complex engineering challenges. His hands-on experience includes projects in servo motor control, smart applications, and multi-material 3D printing. Muhammad’s work contributes to significant advancements in the fields of automation, manufacturing, and functional electronics. πŸ› οΈπŸ”¬πŸ“

Publication Profile :Β 

Scopus

Educational Background πŸŽ“

Muhammad Ahsan Saleem holds a Doctor of Engineering in Mechanical Engineering (ongoing, since 2020) from Nanjing University of Science and Technology, China. He completed his Master of Engineering in Mechanical Engineering in 2018 and his Bachelor of Science in Mechatronics Engineering in 2013, both from the same institution in Nanjing, China, and University of Engineering and Technology (UET) Taxila, Pakistan, respectively.

Professional Experience πŸ’Ό

Currently, Muhammad is a Researcher at Nanjing University of Science and Technology (2020-present), where he collaborates on building plans, timelines, and proposal writing for product development in the fields of 3D printing, inkjet printing, and data-driven approaches for high-viscosity inks. His role involves experiment design for optimizing inkjet printing processes and the development of multi-material ink applications. Prior to this, he worked as a Mechatronics Engineer at Enginesound Automation Technology in Shanghai (2019), where he designed and implemented a Flexible Bend Control (FBC) device for textile machine calibration and developed an android app for wireless data transfer using Bluetooth. His work also includes performance analysis of electric motors and the design of test benches for comprehensive motor analysis. Earlier, he interned as a Trainee Engineer at Attock Refinery Limited, Pakistan, in 2015, working on HVAC equipment installation and maintenance.

Research Interests πŸ”¬

Muhammad’s research spans 3D printing, machine learning, and materials science, with particular focus on inkjet printing technology, piezoelectric inks, and multi-material composites. He explores data-driven methodologies to improve the precision of 3D-printed electronic circuits and has contributed to studies on the jetting behaviors of high-viscosity inks and functional electronics printing.

Publications πŸ“š

Rehman, A. U., Saleem, M. A., Liu, T., Pitir, F., & Salamci, M. U. (2022). Influence of Silicon Carbide on Direct Powder Bed Selective Laser Process (Sintering/Melting) of Alumina. Materials, 15(2), 637. https://doi.org/XXXXXX

Aslam, M. S., Qaisar, I., & Saleem, M. A. (2020). Quantized Event-triggered feedback control under fuzzy system with time-varying delay and actuator fault. Nonlinear Analysis: Hybrid Systems, 35, 100823. https://doi.org/XXXXXX

 

 

 

Kanneboina Ashok | Internet of Medical Things | Best Researcher Award

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Dr. Kanneboina Ashok | Internet of Medical Things | Best Researcher Award

Assistant professor at Mallareddy university, India

Dr. Kanneboina Ashok is an Assistant Professor at Mallareddy University, Hyderabad, where he applies his expertise in IoT and healthcare. With 9 publications, 1 book, and 2 patents, his research aims to improve healthcare systems using IoT technologies, focusing on efficiency, energy, and security. πŸŒπŸ“šπŸ’‘

Publication Profile :Β 

Scopus

Educational Background πŸŽ“

Dr. Kanneboina Ashok is an Assistant Professor at Mallareddy University, Hyderabad, specializing in the intersection of healthcare and technology. With a solid academic foundation, he has made significant contributions in the field of Remote Health Monitoring using the Internet of Medical Things (IoMT). He holds a wealth of research experience, having published 9 research papers in prestigious journals (SCI, Scopus) and authored a book currently under review. His research focuses on optimizing IoMT systems in healthcare to overcome challenges such as delays, energy inefficiencies, and security vulnerabilities, all while maintaining scalability. Dr. Ashok has filed one patent in 2023 and has another ready for publication.

Professional Experience πŸ’Ό

Dr. Ashok has significant teaching and research experience in the field of engineering and healthcare technologies. His expertise extends beyond the classroom, having worked on several ongoing research projects that aim to revolutionize healthcare through the use of IoT. He collaborates with global researchers to address pressing challenges in healthcare technology. Dr. Ashok is dedicated to advancing the potential of IoT in healthcare systems for more efficient, real-time patient monitoring.

Research Interests πŸ”¬

  • Remote Health Monitoring
  • Internet of Medical Things (IoMT)
  • Healthcare System Optimization
  • IoT-based Security and Energy Efficiency in Healthcare

Publications πŸ“š

  1. Ashok, K., & Gopikrishnan, S. (2024). A hybrid secure signcryption algorithm for data security in an Internet of Medical Things environment. Journal of Information Security and Applications, 85, 103836. [Link Disabled]
  2. Kanneboina, A., & Sundaram, G. (2024). Improving security performance of the Internet of Medical Things using a hybrid metaheuristic model. Multimedia Tools and Applications. [Link Disabled]
  3. Ashok, K., & Gopikrishnan, S. (2024). Q-learning model for blockchain security in Internet of Medical Things networks. International Journal of Computer Networks and Communications, 16(1), 33–50. [Link Disabled]
  4. Ashok, K., & Gopikrishnan, S. (2024). A framework provides authorized personnel with secure access to their electronic health records. In Lecture Notes in Networks and Systems (Vol. 894, pp. 137–148). [Link Disabled]
  5. Ashok, K., & Gopikrishnan, S. (2023). Improving security performance of healthcare data in the Internet of Medical Things using a hybrid metaheuristic model. International Journal of Applied Mathematics and Computer Science, 33(4), 623–636. [Open Access]
  6. Ashok, K., & Gopikrishnan, S. (2023). Statistical analysis of remote health monitoring-based IoT security models & deployments from a pragmatic perspective. IEEE Access, 11, 2621–2651. [Open Access]

 

 

 

Anita Gehlot | Sustainable Development Goals | Women Researcher Award

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Prof. Dr. Anita Gehlot | Sustainable Development Goals | Women Researcher Award

Professor at Uttaranchal University, India

Dr. Anita is an experienced educator, researcher, and innovator with a strong background in electronics and communication engineering. She is highly regarded for her work in AI, IoT, and sensor networks, with over 350+ published papers and 47 granted patents. She has mentored multiple Ph.D. students, contributing to advancements in technology and innovation. Dr. Anita was also ranked 6th among India’s top inventors (2010–2020) by Clarivate Analytics in March 2021. With a passion for mentoring and innovation, she continues to inspire students and researchers to push the boundaries of technology. πŸŒŸπŸ“šπŸ’‘πŸ”¬

Publication Profile :Β 

Scopus

Orcid

Educational Background πŸŽ“

  • Ph.D. in Electronics Engineering, University of Petroleum and Energy Studies, Dehradun (2018)
    Thesis: Modelling, Optimization, and Implementation of Sensor Nodes for Authentication of Two-Wheeler Ignition
  • M.E. in Electronics & Communication Engineering, Panjab University, Chandigarh (2009)
    Title: Performance Analysis of Neural Network-Based Particle Swarm Optimization Algorithm for Wireless Sensor Networks
  • B.Tech in Electronics & Communication Engineering, Guru Jambheshwar University, Hisar (2005)

Professional Experience πŸ’Ό

Dr. Anita has over 16 years of experience in academia, with a notable leadership role as Professor & Head of Research & Innovation at Uttaranchal University since 2021. She has previously held significant teaching and administrative roles at esteemed institutions such as Lovely Professional University, University of Petroleum and Energy Studies, and Baddi University. Her experience spans across assistant professor to lecturer roles, where she has contributed to the growth of engineering education and research. Dr. Anita has supervised numerous research projects and Ph.D. candidates, including topics in machine learning, IoT, and sensor networks.

Research Interests πŸ”¬

  • Embedded Systems
  • Artificial Intelligence (AI)
  • Machine Learning (ML)
  • Wireless Sensor Networks (WSN)
  • Automation
  • Internet of Things (IoT)

Dr. Anita’s research primarily focuses on the modeling and optimization of sensor networks, machine learning applications, and IoT-based systems. She is particularly interested in AI algorithms, wireless communication, and smart technologies for real-time applications.

Publications πŸ“š

  • Vaish, K., Sharma, M., Kathuria, S., Akram, S.V., Malik, P.K. (2024). Leveraging wireless technology and IoT in developing a smart judiciary system with smart dust sensors. Intelligent Networks: Techniques, and Applications, 129–151.
  • Tiwari, S., Gehlot, A., Singh, R., Twala, B., Priyadarshi, N. (2024). Design of an iterative method for disease prediction in finger millet leaves using graph networks, dyna networks, autoencoders, and recurrent neural networks. Results in Engineering, 24, 103301.
  • Swami, S., Singh, R., Gehlot, A., Kumar, D., Shah, S.K. (2024). Vision-based approach for human motion detection and smart appliance control. IAES International Journal of Robotics and Automation, 13(4), 445–451.
  • Kumar, V., Singh, R., Gehlot, A., Priyadarshi, N., Twala, B. (2024). Various computational methods for highway health monitoring in terms of detection of black ice: a sustainable approach in Indian context. Discover Sustainability, 5(1), 245.
  • Bhatt, H., Bahuguna, R., Swami, S., Priyadarshi, N., Twala, B. (2024). Integrating industry 4.0 technologies for the administration of courts and justice dispensationβ€”a systematic review. Humanities and Social Sciences Communications, 11(1), 1076.
  • Gopichand, G., Sarath, T., Dumka, A., Priyadarshi, N., Twala, B. (2024). Use of IoT sensor devices for efficient management of healthcare systems: a review. Discover Internet of Things, 4(1), 8.
  • Pachouri, V., Chandramauli, A., Singh, R., Priyadarshi, N., Twala, B. (2024). Removal of contaminants by chlorella species: an effort towards sustainable remediation. Discover Sustainability, 5(1), 19.
  • Krishna, G., Singh, R., Gehlot, A., Akram, S.V. (2024). An IoT-based predictive model for improved battery management system using advanced LSTM model. Journal of Energy Storage, 101, 113694.
  • Singh, R., Gehlot, A., Joshi, K. (2024). Revolutionizing health services: Industry 4.0 aligned systems for the future. In Advanced Technologies for Realizing Sustainable Development Goals: 5G, AI, Big Data, Blockchain, and Industry 4.0 Application (pp. 231–237).
  • Singh, R., Gehlot, A., Joshi, K. (2024). The integration of robotics in advancing smart health echo systems. In Advanced Technologies for Realizing Sustainable Development Goals: 5G, AI, Big Data, Blockchain, and Industry 4.0 Application (pp. 238–243).

 

 

Rajesh Singh | Engineering | Best Researcher Award

Published on by Innovation Technologist

Prof. Dr. Rajesh Singh | Engineering | Best Researcher Award

Professor at Uttaranchal University, India

Rajesh Singh, Ph.D., is an accomplished academician and researcher with over 20 years of experience in engineering and innovation. He currently serves as the Director of Research & Innovation at Uttaranchal University, as well as the Head of Innovation & Entrepreneurship at Lovely Professional University and Head of the Robotics Research Centre at the University of Petroleum & Energy Studies. Dr. Singh has been instrumental in driving various research and innovation initiatives, with notable accomplishments in the fields of Wireless Sensor Networks, Embedded Systems, Robotics, Artificial Intelligence, Machine Learning, Automation, IoT, and Raspberry Pi.

Publication Profile :Β 

Scopus

Educational Background πŸŽ“

  • Ph.D. in Electronics Engineering from the University of Petroleum and Energy Studies, Dehradun (2016).
  • M.Tech in Electronics & Communication Engineering from Rajiv Gandhi Technical University (2009).
  • B.E. in Electronics & Communication Engineering from Dr. B.R Ambedkar University, Agra (2002).

Professional Experience πŸ’Ό

Held various positions in academia, including Associate Professor, Assistant Professor, and Director, with a focus on innovation, research, and entrepreneurship across multiple institutions, including Uttaranchal University, Lovely Professional University, and University of Petroleum & Energy Studies.

Research Interests πŸ”¬

  • Wireless Sensor Networks
  • Embedded Systems
  • Robotics
  • Artificial Intelligence
  • Machine Learning
  • Internet of Things (IoT)
  • Automation

Awards & Recognition

  • Award of Excellence for Research and Innovation in Science, conferred by the State Minister of Uttarakhand, India
  • Recognized for significant contributions to innovation, technology, and academic excellence both nationally and internationally.

Publications πŸ“š

  • Title: Lumpy skin disease virus identification using image-based and deep learning approach
  • Authors: Sharma, S., Joshi, K., Singh, R., Sharma, G., Kumar, G.
  • Conference: Computational Methods in Science and Technology – Proceedings of the 4th International Conference on Computational Methods in Science and Technology, ICCMST 2024
  • Year: 2025
  • Volume: 2
  • Pages: 30–35
  • Title: Leveraging wireless technology and IoT in developing a smart judiciary system with smart dust sensors
  • Authors: Vaish, K., Sharma, M., Kathuria, S., Akram, S.V., Malik, P.K.
  • Book: Intelligent Networks: Techniques, and Applications
  • Year: 2024
  • Pages: 129–151
  • Title: Design of an iterative method for disease prediction in finger millet leaves using graph networks, dyna networks, autoencoders, and recurrent neural networks
  • Authors: Tiwari, S., Gehlot, A., Singh, R., Twala, B., Priyadarshi, N.
  • Journal: Results in Engineering
  • Year: 2024
  • Volume: 24
  • Article ID: 103301
  • Title: Vision-based approach for human motion detection and smart appliance control
  • Authors: Swami, S., Singh, R., Gehlot, A., Kumar, D., Shah, S.K.
  • Journal: IAES International Journal of Robotics and Automation
  • Year: 2024
  • Volume: 13(4)
  • Pages: 445–451
  • Title: Various computational methods for highway health monitoring in terms of detection of black ice: a sustainable approach in Indian context
  • Authors: Kumar, V., Singh, R., Gehlot, A., Priyadarshi, N., Twala, B.
  • Journal: Discover Sustainability
  • Year: 2024
  • Volume: 5(1)
  • Article ID: 245
  • Title: The Image Classification Method for Eddy Current Inspection of Titanium Alloy Plate Based on Parallel Sparse Filtering and Deep Forest
  • Authors: Yidan, Z., Zou, H., Li, Z., Singh, R., Abbas, M.
  • Journal: Journal of Nondestructive Evaluation
  • Year: 2024
  • Volume: 43(4)
  • Article ID: 103
  • Title: Unleashing the power of advanced technologies for revolutionary medical imaging: pioneering the healthcare frontier with artificial intelligence
  • Authors: Chauhan, A.S., Singh, R., Priyadarshi, N., Suthar, S., Swami, S.
  • Journal: Discover Artificial Intelligence
  • Year: 2024
  • Volume: 4(1)
  • Article ID: 58
  • Title: Integrating industry 4.0 technologies for the administration of courts and justice dispensationβ€”a systematic review
  • Authors: Bhatt, H., Bahuguna, R., Swami, S., Priyadarshi, N., Twala, B.
  • Journal: Humanities and Social Sciences Communications
  • Year: 2024
  • Volume: 11(1)
  • Article ID: 1076
  • Title: Use of IoT sensor devices for efficient management of healthcare systems: a review
  • Authors: Gopichand, G., Sarath, T., Dumka, A., Priyadarshi, N., Twala, B.
  • Journal: Discover Internet of Things
  • Year: 2024
  • Volume: 4(1)
  • Article ID: 8
  • Title: Detailed-based dictionary learning for low-light image enhancement using camera response model for industrial applications
  • Authors: Goyal, B., Dogra, A., Jalamneh, A., Singh, R., Jyoti Saikia, M.
  • Journal: Scientific Reports
  • Year: 2024
  • Volume: 14(1)
  • Article ID: 17122

 

 

 

Yi Gou | Medicinal Chemistry | Best Researcher Award

Published on by Innovation Technologist

Mr. Yi Gou | Medicinal Chemistry | Best Researcher Award

Associate Researcher at Guilin Medical University, China

Yi Gou is a distinguished researcher in anticancer drug chemistry with a strong academic background and a track record of innovation. He has authored over 40 SCI papers, with a significant number of first-author publications. His groundbreaking research has led to multiple patents and contributions to international scientific literature. Yi has also served as a guest editor for renowned journals such as Frontiers in Pharmacology and Drug Development Research. His expertise and research are recognized globally, contributing to advancements in cancer therapy.

Publication Profile :Β 

Scopus

Educational Background πŸŽ“

Yi Gou earned a Ph.D. in Inorganic Chemistry in 2016. During his doctoral research, he specialized in the field of anticancer drug chemistry, laying the foundation for his subsequent work. His extensive education and training have provided him with a solid understanding of both inorganic chemistry and medicinal chemistry, particularly in designing and synthesizing anticancer small molecule agents. This expertise has guided his research in the development of novel drug candidates, and his academic achievements include numerous publications in high-impact journals.

Professional Experience πŸ’Ό

Yi Gou is currently serving as an Associate Researcher at Guilin Medical University, where he continues his pioneering research on anticancer drug chemistry. His professional career includes both independent research projects and collaborative work, notably contributing to the National Natural Science Foundation of China (NSFC) projects. He has led one completed NSFC project (Project No. 22007023) and is actively conducting another (Project No. 22267004). In addition to his research, Yi Gou has also been recognized for his editorial contributions, serving as a guest editor for journals such as Frontiers in Pharmacology and Drug Development Research. Over the years, his work has resulted in numerous publications, patents, and positive evaluations in the international research community.

Research Interests πŸ”¬

Yi’s primary research focus is on the design and synthesis of small molecule anticancer agents, particularly those involving metal-based complexes. His work merges the fields of inorganic chemistry and medicinal chemistry, with a focus on developing novel therapeutics to combat cancer. Yi has received significant funding for his research, completing one National Natural Science Foundation of China project (Project No. 22007023) and currently leading another (Project No. 22267004). His work has led to eight Chinese invention patents and multiple collaborations, including research on metal-antitumor complexes based on traditional Chinese medicine components.

Key Achievements

πŸ”¬ Over 40 published SCI papers, with an h-index of 24
πŸ“œ 8 Chinese invention patents granted, 6 in the process of application
πŸ”— Collaborations with leading researchers and national projects
🌍 Recognized as a guest editor for prominent journals
πŸŽ“ Member of the Chinese Chemical Society

Publications πŸ“š

  • Li, A., Pan, W., Zhang, Z., Zhang, Y., & Ma, L. (2025). Hydrazone copper(II) complexes suppressed lung adenocarcinoma by activating multiple anticancer pathways. Bioorganic Chemistry, 154, 107994.
  • Li, A., Huang, K., Pan, W., Ma, L., & Gou, Y. (2024). Thiosemicarbazone mixed-valence Cu(I/II) complex against lung adenocarcinoma cells through multiple pathways involving cuproptosis. Journal of Medicinal Chemistry, 67(11), 9091–9103.

  • Wu, Y., Wu, D., Lan, J., Xu, Y., & Gou, Y. (2024). Assessment of mononuclear/dinuclear copper acylhydrazone complexes for lung cancer treatment. Bioorganic Chemistry, 144, 107122.

  • Deng, J., Wu, Y., Li, A., Yang, F., & Gou, Y. (2023). Dithiocarbazate-Zn(II) complexes for photodynamic therapy and chemotherapy against lung cancer. Inorganic Chemistry Frontiers, 10(22), 6526–6536.

  • Wu, Y., Hou, L., Lan, J., Liu, W., & Gou, Y. (2023). Mixed-ligand copper(II) hydrazone complexes: Synthesis, structure, and anti-lung cancer properties. Journal of Molecular Structure, 1279, 134986.
  • Gou, Y., Liu, L., & Liang, H. (2022). Editorial: The developments of metal-based agents against lung cancer. Frontiers in Pharmacology, 13, 1101890.
  • Chen, M., Chen, X., Huang, G., Gou, Y., & Deng, J. (2022). Synthesis, anti-tumour activity, and mechanism of benzoyl hydrazine Schiff base-copper complexes. Journal of Molecular Structure, 1268, 133730.
  • Deng, J., Peng, C., Hou, L., Huang, G., & Gou, Y. (2022). Dithiocarbazate-copper complex loaded thermosensitive hydrogel for lung cancer therapy via tumor in situ sustained-release. Inorganic Chemistry Frontiers, 9(23), 6190–6201.
  • Guo, J., Li, A., Guo, R., Jin, J., & Huang, G. (2022). C1orf74 positively regulates the EGFR/AKT/mTORC1 signaling in lung adenocarcinoma cells. PeerJ, 10, e13908.
  • Gou, Y., Jia, X., Hou, L. X., Jiang, H. W., & Yang, F. (2022). Dithiocarbazate-Fe(III), -Co(III), -Ni(II), and -Zn(II) complexes: Design, synthesis, structure, and anticancer evaluation. Journal of Medicinal Chemistry, 65(9), 6677–6689.