Junaid Khan | Engineering | Young Scientist Award

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Dr. Junaid Khan | Engineering | Young Scientist Award

Senior Engineer at Samsung Heavy Industry, South Korea

Dr. Junaid Khan is a distinguished researcher specializing in autonomous navigation systems, intelligent transportation, and deep learning applications. He earned his Ph.D. in Environmental IT Engineering from Chungnam National University, South Korea, focusing on enhancing Alpha-Beta filters with neural networks and fuzzy systems for maritime navigation. Currently, he serves as a Senior Engineer at the Autonomous Ship Research Center, Samsung Heavy Industries. Dr. Khan has made significant contributions to machine learning, maritime traffic analysis, and energy-efficient intelligent systems, reflected in his numerous high-impact journal publications and patents. His research has advanced predictive modeling techniques for vessel trajectory optimization, epileptic seizure detection, and energy consumption reduction. With a strong academic background, international collaborations, and expertise in large language models and digital twins, he continues to drive innovation in intelligent automation and smart mobility. His work bridges theoretical advancements with real-world applications, positioning him as a leading scientist in his field.

Professional Profile 

Education

Dr. Junaid Khan holds a Ph.D. in Environmental IT Engineering from Chungnam National University, South Korea, where his research focused on enhancing Alpha-Beta filters using neural networks and fuzzy systems for improved maritime navigation. He earned his Master’s degree in Electrical Engineering from the University of Engineering and Technology (UET) Peshawar, Pakistan, specializing in machine learning and intelligent transportation systems. His academic journey laid a strong foundation in artificial intelligence, predictive modeling, and deep learning applications. Throughout his education, Dr. Khan actively engaged in interdisciplinary research, contributing to advancements in autonomous navigation, vessel trajectory optimization, and energy-efficient intelligent systems. His studies also involved extensive work in large language models, maritime traffic analysis, and epileptic seizure detection. With a solid educational background and hands-on experience in cutting-edge research, he has established himself as a leader in AI-driven smart mobility and autonomous systems, bridging theoretical knowledge with practical industry applications.

Professional Experience

Dr. Junaid Khan has extensive professional experience in artificial intelligence, autonomous navigation, and intelligent transportation systems. He is currently contributing to cutting-edge research in AI-driven smart mobility, focusing on vessel trajectory optimization, energy-efficient maritime navigation, and predictive modeling. His expertise spans deep learning, neural networks, and fuzzy logic, which he has applied to real-world problems in environmental IT engineering. Dr. Khan has worked on large-scale projects involving maritime traffic analysis, epileptic seizure detection, and autonomous system development. His industry collaborations and academic research have led to innovative solutions in smart transportation and AI-driven decision-making. Throughout his career, he has been actively involved in publishing high-impact research, mentoring students, and presenting at international conferences. With a strong technical background and hands-on experience in AI applications, Dr. Khan continues to push the boundaries of intelligent mobility, making significant contributions to both academia and industry.

Research Interest

Dr. Junaid Khan’s research interests lie at the intersection of artificial intelligence, autonomous navigation, and intelligent transportation systems. His work focuses on developing AI-driven solutions for smart mobility, including vessel trajectory optimization, energy-efficient maritime navigation, and predictive modeling for transportation networks. He is particularly interested in deep learning, neural networks, and fuzzy logic, applying these techniques to real-world challenges such as maritime traffic analysis, epileptic seizure detection, and autonomous system development. Dr. Khan’s research also explores environmental IT engineering, leveraging AI to enhance sustainability in transportation and logistics. His contributions extend to the design of intelligent decision-making systems that improve safety, efficiency, and energy conservation in autonomous vehicles. With a keen interest in interdisciplinary collaboration, he actively engages in projects that bridge AI with healthcare, maritime operations, and smart city development. Through his research, Dr. Khan aims to advance AI applications in real-world, high-impact domains.

Award and Honor

Dr. Junaid Khan has received numerous awards and honors in recognition of his outstanding contributions to artificial intelligence, autonomous navigation, and intelligent transportation systems. He has been honored with prestigious research grants and fellowships for his innovative work in AI-driven solutions for smart mobility. His contributions to vessel trajectory optimization, deep learning applications, and predictive modeling have earned him accolades from leading academic and professional organizations. Dr. Khan has also been recognized for his exceptional scholarly output, receiving awards for best research papers at international conferences. His work in interdisciplinary research, spanning maritime navigation, healthcare AI, and sustainable transportation, has been acknowledged by esteemed institutions and funding agencies. Additionally, he has been invited as a keynote speaker and session chair at various scientific gatherings, further solidifying his reputation as a leader in his field. Through these honors, Dr. Khan continues to be recognized for his pioneering contributions to AI and intelligent systems.

Research Skill

Dr. Junaid Khan’s research interests lie at the intersection of artificial intelligence, machine learning, and intelligent transportation systems, with a strong focus on autonomous navigation, vessel trajectory optimization, and predictive analytics. His work explores deep learning algorithms, reinforcement learning, and data-driven models to enhance decision-making in maritime and land-based transportation networks. He is particularly interested in developing AI-driven solutions for optimizing vessel routing, minimizing fuel consumption, and improving safety in smart mobility systems. Dr. Khan’s research also extends to healthcare applications, where he leverages machine learning techniques for medical diagnostics and predictive modeling. His interdisciplinary approach integrates AI with real-world challenges, aiming to create sustainable and efficient solutions for global transportation and healthcare industries. With a keen interest in the ethical implications of AI, he also investigates fairness, interpretability, and transparency in automated decision-making systems, ensuring that AI advancements align with societal and industrial needs.

Conclusion

Junaid Khan, Ph.D., is a strong candidate for the Young Scientist Award due to his impressive research contributions, patents, and industry experience. His work in machine learning, maritime navigation, and intelligent transportation systems showcases innovation and impact. Strengthening independent recognition and leadership roles in research projects could further enhance his suitability. Overall, he is a competitive nominee for this award.

Publications Top Noted

  1. A higher prediction accuracy–based alpha–beta filter algorithm using the feedforward artificial neural network

    • Authors: J Khan, E Lee, K Kim
    • Year: 2023
    • Citations: 68

  2. A comprehensive review of conventional, machine learning, and deep learning models for groundwater level (GWL) forecasting

    • Authors: J Khan, E Lee, AS Balobaid, K Kim
    • Year: 2023
    • Citations: 48

  3. An improved alpha beta filter using a deep extreme learning machine

    • Authors: J Khan, M Fayaz, A Hussain, S Khalid, WK Mashwani, J Gwak
    • Year: 2021
    • Citations: 25

  4. Secure and fast image encryption algorithm based on modified logistic map

    • Authors: M Riaz, H Dilpazir, S Naseer, H Mahmood, A Anwar, J Khan, IB Benitez, …
    • Year: 2024
    • Citations: 14

  5. An efficient feature augmentation and LSTM-based method to predict maritime traffic conditions

    • Authors: E Lee, J Khan, WJ Son, K Kim
    • Year: 2023
    • Citations: 14

  6. A performance evaluation of the alpha-beta (α-β) filter algorithm with different learning models: DBN, DELM, and SVM

    • Authors: J Khan, K Kim
    • Year: 2022
    • Citations: 14

  7. An efficient methodology for water supply pipeline risk index prediction for avoiding accidental losses

    • Authors: MS Qureshi, A Aljarbouh, M Fayaz, MB Qureshi, WK Mashwani, J Khan
    • Year: 2020
    • Citations: 10

  8. Optimizing the performance of Kalman filter and alpha-beta filter algorithms through neural network

    • Authors: J Khan, E Lee, K Kim
    • Year: 2023
    • Citations: 5

  9. A Performance Evaluation of the AlphaBeta filter Algorithm with different Learning Modules ANN, DELM, CART and SVM

    • Authors: KK Junaid Khan
    • Year: 2022
    • Citations: 5*

  10. Synthetic Maritime Traffic Generation System for Performance Verification of Maritime Autonomous Surface Ships

  • Authors: E Lee, J Khan, U Zaman, J Ku, S Kim, K Kim
  • Year: 2024
  • Citations: 4

Jawad Ali | Engineering | Best Researcher Award

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Mr. Jawad Ali | Engineering | Best Researcher Award

Ph.D. Researcher at High Frequency Systems Laboratory, King Mongkut’s University of Technology North Bangkok, Bangkok 10800, Thailand

Mr. Jawad Ali is a dedicated researcher specializing in electrical engineering, IoT, and antenna design, with a strong academic background and extensive international exposure. He holds a Ph.D. in Electrical and Software Systems Engineering from King Mongkut’s University of Technology North Bangkok, along with a Master’s in Electrical Engineering (CPA 4.00/4.00) from UTHM Malaysia. His research focuses on IoT-based localization, RF and microwave systems, and biomedical applications, with collaborations at Trinity College Dublin, UTHM, and COMSATS University. Recognized with multiple awards, including the IEEE AP-S Fellowship Grant and Malaysia Technology Expo medals, he has contributed to academia through teaching and mentoring roles. His technical expertise spans antenna fabrication, MATLAB, and RF measurements. As an IEEE and Pakistan Engineering Council member, he continues to advance research through international collaborations and industrial projects. With a strong research portfolio and global impact, he is a highly suitable candidate for the Best Researcher Award.

Professional Profile 

Education

Mr. Jawad Ali has a strong academic background in electrical engineering, specializing in RF, microwave, and IoT-based systems. He is currently completing his Ph.D. in Electrical and Software Systems Engineering at King Mongkut’s University of Technology North Bangkok, where he defended his dissertation with a Grade A. His doctoral research focuses on IoT-based localization of people and objects for the MICE industry. He earned his Master’s degree in Electrical Engineering from Universiti Tun Hussein Onn Malaysia (UTHM) with a perfect CPA of 4.00/4.00, researching ultra-wideband antenna arrays for human scanning under debris. His undergraduate studies were completed through a collaborative program between COMSATS University Islamabad and Lancaster University, UK, where he obtained a Bachelor’s degree in Electrical (Telecommunication) Engineering with First-Class Honours. His academic journey is marked by excellence, international exposure, and contributions to cutting-edge research, making him a distinguished scholar in his field.

Professional Experience

Mr. Jawad Ali has a diverse professional background spanning academia, research, and industry. He currently serves as a Visiting Lecturer at Khwaja Fareed University of Engineering and Information Technology, Pakistan. Previously, he was a Ph.D. Researcher at Trinity College Dublin, contributing to IoT-based localization research. As a Teaching Assistant at King Mongkut’s University of Technology North Bangkok, he worked on RF and microwave engineering projects for MuSpace and PTT Thailand. His tenure at COMSATS University Islamabad as a Laboratory Engineer involved research, academic coordination, and industrial collaborations. Additionally, he worked as a Graduate Research Assistant at UTHM Malaysia, assisting with student research and thesis projects. His early career included a role as a Junior System Support Engineer at HB Media (PVT) Capital TV, handling broadcast engineering operations. With expertise in RF measurements, IoT, and antenna design, he has significantly contributed to both academia and industry.

Research Interest

Mr. Jawad Ali’s research interests lie at the intersection of electrical engineering, RF and microwave systems, IoT, and antenna design. His work focuses on developing advanced localization techniques using multi-standard IoT for applications in the Meetings, Incentives, Conventions, and Exhibitions (MICE) industry. He has a strong background in ultra-wideband (UWB) antenna design, biomedical applications, and radar-based human scanning under debris. His research extends to environmentally friendly antenna materials, ground-penetrating radar for soil scanning, and microstrip line designs using cellulose-based substrates. Collaborating with institutions like Trinity College Dublin, UTHM Malaysia, and COMSATS University Islamabad, he actively contributes to cutting-edge innovations in wireless communications and electromagnetic applications. His expertise in RF measurements, simulation tools like CST Studio Suite and HFSS, and his commitment to advancing antenna technology position him as a leading researcher in the field, with significant contributions to both academia and industry-driven projects.

Award and Honor

Mr. Jawad Ali has received numerous awards and honors in recognition of his outstanding research contributions and academic excellence. He was awarded the Bronze Medal at the Malaysia Technology Expo MARS (2018) and the Research and Innovation Festival (2017) for his innovative work in electrical engineering. His exceptional performance during his Master’s studies earned him the Graduate on Time (GoT) Award and a Publication Award from Universiti Tun Hussein Onn Malaysia (UTHM). He was also a recipient of the prestigious UTHM Scholarship Award. His research productivity was acknowledged by COMSATS University Islamabad, where he received the Research Productivity Award. Additionally, he was selected for a fully funded study visit to the University of Lancaster, UK. His work has been further supported by major grants, including the IEEE Antennas and Propagation Society Fellowship, IDS Ingegneria Dei Sistemi Grant, and NSTDA-KMUTNB Thailand Gold Medal Scholarship, highlighting his dedication to scientific advancement.

Research Skill

Mr. Jawad Ali possesses strong research skills in the fields of electrical engineering, RF and microwave systems, and IoT-based localization technologies. He is highly proficient in antenna design, microwave circuit fabrication, and RF measurements, enabling him to develop innovative solutions for communication and sensing applications. His expertise extends to advanced simulation and design tools such as CST Studio Suite, HFSS, and Microwave Office, which he utilizes for optimizing antenna and radar system performance. He is skilled in programming with MATLAB and C/C++ for signal processing and data analysis. His research methodology is strengthened by hands-on experience in industrial projects, including RF far-field measurements and liquid resonance studies. His ability to collaborate with international research groups, secure funding, and publish in high-impact journals demonstrates his analytical thinking, problem-solving capabilities, and commitment to advancing technological innovations in wireless communication and electromagnetic applications.

Conclusion

Jawad Ali has a strong academic, research, and professional profile, making him a highly suitable candidate for the Best Researcher Award. His contributions in antenna design, IoT-based localization, and RF engineering are significant. To further strengthen his candidacy, he should focus on publishing in high-impact journals, securing major research leadership roles, and expanding global collaborations. With his technical expertise, international exposure, and innovative contributions, he stands out as a competitive nominee for this award.

Publications Top Noted

  1. Metasurface-Loaded Biodegradable Mobile Phone Back Cover for Enhanced Radiation Performance

    • Authors: Juin Acharjee, Jawad Ali, Muhammad Uzair, Thipamas Phakaew, Prayoot Akkaraekthalin, Yaowaret Maiket, Rungsima Yeetsorn, Suramate Chalermwisutkul
    • Year: 2025
    • DOI: 10.3390/ma18040730

  2. Low-Cost Indoor Localization Using Dual-Chip RFID Tag

    • Authors: Jawad Ali, Kamol Kaemarungsi, Thipamas Phakaew, Muhammad Uzair, Adam Narbudowicz, Suramate Chalermwisutkul
    • Year: 2024
    • DOI: 10.1109/OJAP.2024.3372030

  3. Enhancement of Radio Frequency Identification Coverage for Various Indoor Scenarios Using Diversified Radiation Patterns of Tag and Reader Antennas

  4. Dual-Chip RFID Tag for Enhanced Indoor Localization of IoT Assets

  5. Optimization of Planar Capacitive Sensors Embedded Between Two 6mm Thick Glass Sheets

  6. Post-Design Modifications for Impedance Matching of UHF RFID Tag Antenna

  7. Dual-Chip UHF RFID Tag Antenna for Distinction of Movement Directions

  8. Modeling and Design of Enhanced All Optical Signal Regeneration Technique

  9. Antenna Design Using UWB Configuration for GPR Scanning Applications

  10. Design a Compact Square Ring Patch Antenna with AMC for SAR Reduction in WBAN Applications

Yibo Ding | Engineering | Best Researcher Award

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Assoc.Prof.Dr.Yibo Ding | Engineering | Best Researcher Award

Associate professor atNorthwestern Polytechnical University, China

Dr. Yibo Ding is an Associate Professor at Northwestern Polytechnical University, specializing in aerospace guidance and control. With a Ph.D. in aeronautical and astronautical science from Harbin Institute of Technology, he has dedicated his research to cooperative game guidance and multi-constraint adaptive control of hypersonic vehicles. He has led over 20 research projects, including national-level initiatives, and collaborated with key aerospace institutions in China. His contributions include innovative guidance algorithms, high-precision self-learning control technologies, and the development of national standards. Dr. Ding has published over 30 academic papers, authored two books, and holds 12 patents. His research has been recognized by esteemed academicians and has had significant applications in aerospace engineering and defense technology. With multiple awards, editorial appointments, and international presentations, he stands out as a leading researcher in his field, making him a strong candidate for the Best Researcher Award.

Professional Profile

Education

Dr. Yibo Ding earned his B.S. degree in Aircraft Design and Engineering and his Ph.D. in Aeronautical and Astronautical Science and Technology from Harbin Institute of Technology, China, in 2015 and 2020, respectively. His academic training provided a strong foundation in aerospace engineering, with a focus on advanced guidance and control systems for hypersonic vehicles. His doctoral research emphasized intelligent cooperative game guidance and adaptive control, addressing key challenges in aerospace flight dynamics. With his rigorous education and specialized expertise, Dr. Ding has emerged as a leading researcher in aerospace engineering, contributing significantly to flight safety, optimal flight performance, and national defense technology.

Professional Experience

Since 2020, Dr. Yibo Ding has been serving as an Associate Professor at Northwestern Polytechnical University, Xi’an, China, where he is affiliated with the National Key Laboratory of Aerospace Flight Dynamics Technology. He is a core member of the “Innovation Team of Sanqin Special Support Program for Talents” and actively contributes to aerospace research and development. He holds various prestigious roles, including Director of the Shaanxi Vibration Engineering Society and an expert for the Xi’an Science and Technology Bureau. Recognized as a Young Top Talent under the Shaanxi Special Support Program, he has also been selected for the China Association for Science and Technology Young Talent Lift Project and the Northwest Polytechnical University Soaring Star Program. His research focuses on cooperative game guidance and multi-constraint adaptive control for hypersonic vehicles, aiming to enhance flight safety and optimize performance. Additionally, he collaborates closely with key aerospace research institutes, contributing to national defense projects and cutting-edge aerospace technology.

Research Interest

Dr. Yibo Ding’s research interests primarily focus on aerospace guidance and control, with a particular emphasis on cooperative game guidance and multi-constraint adaptive control for hypersonic vehicles. His work aims to enhance flight safety, optimize flight performance, and support the future development of aerospace aircraft technology. He specializes in intelligent cooperative game guidance under threat assessment, designing advanced algorithms that improve aircraft maneuverability in high-threat environments. Additionally, his research addresses critical challenges such as intake constraints, flight transient constraints, aerodynamic-propulsion coupling, and strong system uncertainties in hypersonic vehicles. By developing high-precision self-learning control technologies, including fixed-time anti-saturation compensation algorithms and adaptive parameter tuning methods, he contributes to ensuring stable and efficient aerospace flight dynamics. His research findings have significant applications in national defense and future aerospace missions, advancing the capabilities of next-generation aerospace vehicles.

Award and Honor

Dr. Yibo Ding has received several prestigious awards and honors in recognition of his outstanding contributions to aerospace research and innovation. He was selected as a Young Top Talent under the Shaanxi Special Support Program and was also recognized by the China Association for Science and Technology’s Young Talent Lift Project. Additionally, he was honored as a Soaring Star at Northwestern Polytechnical University. His research excellence has been acknowledged through the Excellent Paper Award at the China Commercial Space Summit Forum in 2023. He has also played a significant role in national defense projects, where his contributions were recognized at the national level for ensuring the successful execution of key aerospace missions. His work has received high praise from leading academicians and scholars, further solidifying his reputation as a distinguished researcher in aerospace guidance and control.

Conclusion

Given his strong research output, industry collaborations, patents, and contributions to aerospace engineering, Yibo Ding is a strong candidate for the Best Researcher Award. While he has areas for growth, particularly in international visibility and industry application, his achievements make him highly deserving of recognition in his field.

Publications Top Noted

  • Title: Prospective cohort studies underscore the association of abnormal glycemic measures with all-cause and cause-specific mortalities
    Authors: Juzhong Ke, Xiaonan Ruan, Wenbin Liu, Zhitao Li, Guangwen Cao
    Year: 2024
    Citations: 0
  • Title: Trends in disease burden and risk factors of asthma from 1990 to 2019 in Belt and Road Initiative countries: evidence from the Global Burden of Disease Study 2019
    Authors: Wenjing Ye, Xue Xu, Yibo Ding, Xiaopan Li, Wen Gu
    Year: 2024
    Citations: 0
  • Title: Smoke and Spike: Benzo[a]pyrene Enhances SARS-CoV-2 Infection by Boosting NR4A2-Induced ACE2 and TMPRSS2 Expression
    Authors: Wenbin Liu, Yue Zhao, Junyan Fan, Xiaojie Tan, Guangwen Cao
    Year: 2023
    Citations: 1
  • Title: Remote detection device for bioaerosol: research progress
    Authors: Letian Fang, Wenbin Liu, Yibo Ding, Guangwen Cao
    Year: 2023
    Citations: 0

Janani Priyanka Perumpally Rajakumar | Engineering | Best Researcher Award

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Ms. Janani Priyanka Perumpally Rajakumar | Engineering | Best Researcher Award

Student at Dong-A University, India

Janani Priyanka P.R. is a dedicated researcher specializing in civil and environmental engineering, with a strong academic background and expertise in air quality monitoring, data analysis, and smart city engineering. She has a passion for tackling environmental challenges using advanced technologies such as big data and IoT-based monitoring systems. With multiple Q1 journal publications and international conference presentations, she has demonstrated her ability to contribute impactful research. Her technical proficiency in Python, AutoCAD, C++, and Microsoft tools further enhances her analytical capabilities. She has received notable recognition, including an Editor’s Choice selection for one of her research papers and a Second Paper Award at ICTSCE 2023. She aspires to further her research in sustainable construction and urban planning, aiming to integrate technology and environmental solutions for smarter, safer cities.

Professional Profile

Education

Janani holds a Master’s degree in ICT Integrated Oceanfront Smart City Engineering from Dong-A University, Busan, South Korea, with an impressive GPA of 4.19/5. Her interdisciplinary education integrates architecture, civil, and electronic engineering, providing a comprehensive understanding of sustainable urban development. She previously earned a Bachelor of Technology in Civil Engineering from Adi Shankara Institute of Engineering and Technology, Kerala, India, graduating with an outstanding CGPA of 9.11/10. She ranked second in her department during her undergraduate studies, reflecting her academic excellence. Throughout her academic journey, she actively participated in research projects, technical conferences, and internships, which helped her develop expertise in environmental sustainability, air pollution control, and smart construction methodologies.

Professional Experience

Janani has gained valuable research and industry experience through various internships and projects. She interned at SFS Homes, Kakkanad, where she worked on an ongoing construction project, gaining hands-on experience in structural design and project management. Additionally, she completed an internship at the civil department of FACT Ltd., Eloor, where she explored industrial construction techniques and environmental safety protocols. She has actively participated in international conferences, including ICTSCE 2021 & 2023 and IEEE Big Data 2021, where she presented her research on particulate matter control and toxic gas monitoring. Her research on air pollution control in construction activities, toxic gas detection systems, and sustainable building practices has been widely recognized. With her technical skills in data analysis, programming, and engineering design, she is well-equipped to contribute to innovative solutions in urban development and environmental sustainability.

Research Interest

Janani Priyanka P.R.’s research focuses on air quality monitoring, environmental sustainability, and smart city engineering. She is particularly interested in developing data-driven solutions to address pollution control challenges in urban environments. Her studies explore big data analytics, IoT-based toxic gas monitoring, and particulate matter control measures in construction activities. She has conducted extensive research on real-time gas detection systems for worker safety and efficient air pollution mitigation strategies using advanced technologies. Her interdisciplinary approach integrates civil engineering, environmental science, and data analytics, making her work highly relevant to sustainable urban development. She aspires to further explore machine learning applications in air quality forecasting, climate-resilient infrastructure, and smart urban planning. By leveraging her technical skills in Python, C++, AutoCAD, and MS Project, she aims to contribute to innovative solutions that enhance environmental sustainability and public health in rapidly urbanizing regions.

Awards and Honors

Janani has received several prestigious awards and honors for her academic excellence and research contributions. She was awarded the Second Paper Award at ICTSCE 2023 in Busan, South Korea, recognizing her work in air pollution control and sustainable construction practices. Her research paper published in the Sensors Journal was selected as an Editor’s Choice Article, highlighting its significance in the field of toxic gas detection and worker safety. She has published three Q1 journal articles, a testament to the impact and quality of her research. Additionally, she ranked second in her undergraduate civil engineering department, showcasing her consistent academic excellence. Her Master’s thesis on toxic gas exposure detection received a remarkable score of 94 out of 100, further reinforcing her expertise in environmental monitoring systems. With multiple international conference presentations and impactful research publications, she continues to make significant contributions to sustainable urban engineering and environmental science.

Conclusion

Janani Priyanka P.R. is a strong contender for the Best Researcher Award, given her exceptional academic performance, Q1 publications, technical skills, and international recognition. However, further strengthening through a Ph.D., leadership in research, and interdisciplinary collaborations would enhance her profile further. If she continues on this trajectory, she has high potential to be an outstanding researcher in her field.

Publications Top Noted

  • Ham, Y.-B., Cheriyan, D., Kim, H.-U., Janani Priyanka, P.R., Choi, J.-H. (2024). “Particulate matter reduction efficiency analysis of sprinkler system as targeted control measures for construction activity.” Heliyon, 10(7), e27765.
    • Year: 2024
    • Citations: 0
  • Janani Priyanka, P.R., Cheriyan, D., Choi, J.-H. (2022). “A proactive approach to execute targeted particulate matter control measures for construction works.” Journal of Cleaner Production, 368, 133168.
    • Year: 2022
    • Citations: 5
  • Priyanka, J., Cheriyan, D., Choi, J.-H. (2021). “Issues with Current PM Monitoring Techniques and Control Measures and the Way Forward Using Big Data.” Proceedings – 2021 IEEE International Conference on Big Data (Big Data 2021), pp. 5997.
    • Year: 2021
    • Citations: 1