Dr. Malaya Nath | Signal Processing | Best Researcher Award

Dr. Malaya Nath | Signal Processing | Best Researcher Award

Assistant Professor | National Institute of Technology Puducherry | India

Dr. Malaya Kumar Nath is an accomplished researcher and academician in the field of Electronics and Communication Engineering, specializing in Biomedical Signal and Image Processing, Pattern Recognition, Deep Learning, and Computational Neuroscience. His research primarily focuses on developing advanced computational models for medical image analysis, disease diagnosis, and intelligent healthcare systems using signal and image processing techniques integrated with artificial intelligence. Dr. Nath has significantly contributed to diagnostic automation through the application of deep learning architectures such as CNNs and EfficientNet for skin cancer, glaucoma, and retinal image analysis. His scholarly contributions have earned him recognition among the Top two percentage most influential scientists worldwide, as reported by Stanford University and Elsevier in 2025. He has an extensive publication record, with 69 Scopus-indexed documents and over 1,291 citations by 902 documents, achieving an h-index of 21 on Scopus. On Google Scholar, he has accumulated 2,185 citations with an h-index of 24 and an i10-index of 47, reflecting his impactful research influence. His interdisciplinary research integrates biomedical data analytics with machine learning and deep neural frameworks, addressing challenges in medical imaging and healthcare informatics.

Profile

Scopus | ORCID | Google Scholar

Featured Publications

Keerthana, D., Venugopal, V., Nath, M. K., & Mishra, M. (2023). Hybrid convolutional neural networks with SVM classifier for classification of skin cancer. Biomedical Engineering Advances, 5, 100069.

Anbalagan, T., Nath, M. K., Vijayalakshmi, D., & Anbalagan, A. (2023). Analysis of various techniques for ECG signal in healthcare, past, present, and future. Biomedical Engineering Advances, 6, 100089.

Elangovan, P., & Nath, M. K. (2021). Glaucoma assessment from color fundus images using convolutional neural network. International Journal of Imaging Systems and Technology, 31(2), 955–971.

Vijayalakshmi, D., & Nath, M. K. (2020). A comprehensive survey on image contrast enhancement techniques in spatial domain. Sensing and Imaging, 21(1), 40.

Venugopal, V., Raj, N. I., Nath, M. K., & Stephen, N. (2023). A deep neural network using modified EfficientNet for skin cancer detection in dermoscopic images. Decision Analytics Journal, 8, 100278.

Sarah Popenhagen | Signal Processing | Best Researcher Award

Dr. Sarah Popenhagen | Signal Processing | Best Researcher Award

Junior Researcher | University of Hawai’i at Manoa | United States

Sarah K. Popenhagen is a dedicated Earth and planetary scientist whose interdisciplinary expertise spans infrasound acoustics, machine learning, and airborne data collection. Earning her PhD in Earth and Planetary Sciences at the University of Hawaiʻi at Mānoa under the supervision of Milton Garcés, she leverages advanced audio processing and classification techniques. With robust engineering foundations, she applies these methods to detect and characterize acoustic signals from rocket launches and explosions using devices as ubiquitous as smartphones. Her research bridges cutting-edge computational methods with practical, scalable acoustic sensing, advancing both scientific understanding and real-world monitoring capabilities.

Publication Profile

Scopus

ORCID

Education Background

Sarah K. Popenhagen earned her PhD in Earth and Planetary Sciences from the University of Hawaiʻi at Mānoa, focusing on infrasound acoustics, rocket ignition and trajectory signatures, and machine learning for audio classification. Prior to that, she completed a BSc in Engineering Physics at the University of Illinois Urbana-Champaign, where she received the Laura B. Eisenstein Award. She also broadened her academic perspective as an exchange student in Physics and Astrophysics at the University of Birmingham in the UK, enriching her foundation in interdisciplinary physical sciences.

Professional Experience

During her doctoral studies at the University of Hawaiʻi at Mānoa, Sarah contributed as a Junior Researcher in the Infrasound Laboratory, authoring publications and developing Python tools for audio dataset analysis and visualization. As a Research Assistant in the Earth Sciences Department, she curated and annotated rocket acoustic signatures, designed and evaluated machine learning detection models, and analyzed multimodal explosion data from airborne platforms. Her prior roles include an engineering physics undergraduate researcher at Illinois, where she developed methane-monitoring prototypes, and multiple positions at Idaho National Laboratory and USGS, applying acoustic and seismic analysis to nonproliferation and hydrology challenges.

Awards and Honors

Sarah’s academic distinction is marked by the Laura B. Eisenstein Award, recognizing her outstanding achievement during her undergraduate studies at the University of Illinois Urbana-Champaign. Her selection as an exchange student in Physics and Astrophysics at the University of Birmingham highlights her academic adaptability and merit. Additionally, her impactful contributions to geophysical research, particularly with accessible sensor networks and machine learning methodologies, have garnered recognition in peer-reviewed publications and funded projects, demonstrating both scholarly and practical accolades throughout her burgeoning career.

Research Focus

Sarah’s research centers on detecting and interpreting acoustic signatures of rockets and explosions using machine learning and infrasound analysis. She develops and maintains Python-based tools and repositories for processing open-access audio datasets, enabling training and evaluation of classification models. Her work includes leveraging smartphone audio to study rocket ignition, launch, and trajectory features, designing ensemble learning models for explosion detection with high accuracy, and deploying airborne collection platforms. Her focus combines acoustic physics with AI, aiming to democratize sensor networks for environmental and security monitoring.

Top  Publications

Rocket Launch Detection with Smartphone Audio and Transfer Learning
Published Year: 2025
Citation: 1

Acoustic Rocket Signatures Collected by Smartphones
Published Year: 2025
Citation: 1

Explosion Detection using Smartphones: Ensemble Learning with the Smartphone High-explosive Audio Recordings Dataset and the ESC-50 Dataset
Published Year: 2024
Citation: 4

Acoustic Waves from a Distant Explosion Recorded on a Continuously Ascending Balloon in the Middle Stratosphere
Published Year: 2023
Citation: 9

Skyfall: Signal Fusion from a Smartphone Falling from the Stratosphere
Published Year: 2022
Citation: 12

Conclusion

Sarah K. Popenhagen’s career blends engineering physics, geoscience, and machine learning to tackle complex challenges in acoustic monitoring. Her work harnesses everyday technology—like smartphones—alongside advanced modeling to detect rocket and explosion events with precision and scalability. Through her publications, software development, and interdisciplinary research projects, she contributes to more accessible, effective environmental and geophysical sensing. Her trajectory signals a growing influence in leveraging AI-enhanced acoustics for real-world monitoring, scientific innovation, and societal benefit.

 

 

Yashi Zhou | Signal Processing | Best Researcher Award

Prof. Dr. Yashi Zhou | Signal Processing | Best Researcher Award

Prof. Dr. Yashi Zhou | Senior Engineer | China Academy of Space Technology | China

Yashi Zhou is a Chinese researcher and senior engineer specializing in synthetic aperture radar (SAR) signal processing. He received his B.S. degree in electronic information science and technology from Central South University in 2016 and earned his Ph.D. in space microwave remote sensing systems from the Institute of Electronics, Chinese Academy of Sciences in 2021. He currently works at the Institute of Remote Sensing Satellite, China Academy of Space Technology. With notable contributions in high-resolution, wide-swath SAR technologies, Dr. Zhou has published widely in top conferences and journals. His research integrates technical innovation and practical applications in remote sensing systems.

Publication Profile

ORCID

Education Background

Yashi Zhou completed his undergraduate studies at Central South University, earning a B.S. in electronic information science and technology in 2016. He then pursued his doctoral education at the University of Chinese Academy of Sciences, affiliated with the Institute of Electronics, where he focused on space microwave remote sensing systems and SAR imaging. He received his Ph.D. degree in 2021. His academic background provided a solid foundation in advanced electronic systems, signal processing, and synthetic aperture radar technologies, which now serve as the basis of his engineering and research work in satellite-based remote sensing.

Professional Experience

After receiving his Ph.D., Yashi Zhou joined the Institute of Remote Sensing Satellite at the China Academy of Space Technology in Beijing as a senior engineer. In this role, he has been actively engaged in developing and deploying cutting-edge SAR systems. His work focuses on the design and implementation of wide-swath and high-resolution imaging modes, as well as digital beamforming technologies. Dr. Zhou has collaborated with multidisciplinary teams in both research and application-driven projects, playing a key role in airborne and satellite-based SAR missions and contributing to the advancement of China’s remote sensing capabilities.

Awards and Honors

In recognition of his outstanding contributions to SAR signal processing and remote sensing technology, Yashi Zhou was awarded the Youth Talent Program by the China Association for Science and Technology in 2023. This prestigious national honor acknowledges promising early-career researchers who demonstrate leadership in science and technology innovation. The award underscores Dr. Zhou’s impact and potential in the field, highlighting his role in pushing the boundaries of synthetic aperture radar technologies, particularly in the areas of wide-swath imaging, multichannel systems, and frequency diverse arrays.

Research Focus

Dr. Yashi Zhou’s research focuses primarily on high-resolution and wide-swath synthetic aperture radar (SAR) signal processing and its application in real-world systems. His expertise includes digital beamforming (DBF), multichannel SAR, frequency diverse arrays, and airborne X-band SAR technologies. His work aims to resolve long-standing challenges in SAR imaging, such as phase bias, channel calibration, and Doppler centroid estimation. By integrating theoretical models with experimental data from platforms like the GF-3 satellite and airborne systems, he advances the performance and accuracy of modern SAR imaging systems in remote sensing.

Publication Top Notes

  1. A Novel Approach to Doppler Centroid and Channel Errors Estimation in Azimuth Multi-Channel SAR
    Year: 2019
    Cited by: 28 articles

  2. Digital Beamforming Synthetic Aperture Radar (DBSAR): Experiments and Performance Analysis in Support of 16-Channel Airborne X-Band SAR Data
    Year: 2021
    Cited by: 50 articles

  3. High-Resolution and Wide-Swath SAR Imaging Mode Using Frequency Diverse Planar Array
    Year: 2021
    Cited by: 49 articles

  4. Very High Resolution SAR Imaging With DGPS-Supported Airborne X-Band Data
    Year: 2020
    Cited by: 10 articles

  5. Phase Bias Estimation and Imaging for High-Squint Multichannel SAR in Azimuth
    Year: 2023
    Cited by: 1 articles

Conclusion

Yashi Zhou is an accomplished researcher whose academic training and engineering expertise make significant contributions to the field of remote sensing and SAR technologies. His work bridges the gap between fundamental signal processing and practical implementation in satellite systems. With recognized achievements, numerous high-impact publications, and a national talent award, Dr. Zhou continues to be a key figure in advancing China’s capabilities in spaceborne Earth observation. His future research is expected to further enhance imaging precision and efficiency in SAR systems across national and international platforms.

Yueming Ma | Signal Processing | Best Researcher Award

Mr. Yueming Ma | Signal Processing | Best Researcher Award

Mr. Yueming Ma , PhD Student , Shenyang Institute of Automation Chinese Academy of Sciences , China.

Yueming Ma is a Ph.D. candidate at the Shenyang Institute of Automation, Chinese Academy of Sciences, specializing in marine robotics and underwater signal processing. His academic journey is marked by continuous excellence, from earning his bachelor’s degree in Vehicle Engineering to securing direct admission into the doctoral program through a master-to-Ph.D. transfer. He has co-authored impactful research on passive synthetic aperture methods for underwater vehicles and has presented his work at notable conferences like IEEE OES. His contributions reflect a commitment to advancing underwater acoustic technologies for scientific and industrial applications.

Publication Profile

Google Scholar

🎓 Education Background

Yueming Ma completed his undergraduate studies in Vehicle Engineering from Hefei University of Technology, where he earned academic scholarships for three consecutive years. Following his undergraduate success, he was admitted to the master’s program in Pattern Recognition and Intelligent Systems at the Shenyang Institute of Automation, Chinese Academy of Sciences, based on academic merit. During his postgraduate studies, he transitioned into the Ph.D. program through an internal academic transfer, highlighting his research potential and dedication to scientific exploration in underwater robotics and signal processing.

🧑‍💼 Professional Experience

Yueming Ma has built his professional foundation within the Shenyang Institute of Automation, CAS, engaging in advanced research under the guidance of distinguished scientists like Dr. Jie Sun and Dr. Shuo Li. He has collaborated on underwater signal processing projects, including joint initiatives with the School of Navigation at Northwestern Polytechnical University. His work emphasizes hands-on experimental validation through pool-based and sea trials, including the deployment of the Haiyi 1000 underwater glider. Though early in his career, his research is already contributing to the evolving landscape of underwater sensing technologies.

🏆 Awards and Honors

While formal awards are pending, Yueming Ma’s academic and research excellence is demonstrated through competitive scholarships during his undergraduate years and admission into graduate and doctoral programs based on merit. His selection for conference presentations and publication in high-impact journals like the Journal of Marine Science and Engineering reflect peer recognition and scientific merit. His progression through academic ranks and collaborative research efforts position him as a promising scholar worthy of future accolades and honors in the fields of robotics and signal processing.

🔬 Research Focus

Yueming Ma’s research centers on underwater target detection and signal processing for marine robotic systems. His work emphasizes passive synthetic aperture techniques for direction-of-arrival (DOA) estimation using single-hydrophone underwater vehicles. He addresses challenges such as motion-induced distortions and limited aperture size by developing trajectory correction and motion-compensated models. Validated through real-world trials, his research pushes the boundaries of autonomous underwater sensing. His current interests include integrating data-driven methodologies to enhance DOA estimation robustness under complex underwater motion conditions, combining theory with practical experimentation for marine applications.

📝 Conclusion

Yueming Ma represents a new generation of dedicated marine robotic researchers with an emphasis on signal processing innovation. Through rigorous academic training, hands-on fieldwork, and multidisciplinary collaborations, he contributes meaningful advancements to underwater acoustic sensing. His research achievements, combined with growing publication activity and conference participation, position him as a strong candidate for the Best Researcher Award. With continued dedication, he is set to make significant impacts in underwater robotics, signal intelligence, and autonomous navigation technologies.

📄 Top Publications

  1. Passive Synthetic Aperture for Direction-of-Arrival Estimation Using an Underwater Glider with a Single Hydrophone
    🗓 Year: 2025
    📚 Journal: Journal of Marine Science and Engineering (JMSE)

  2. A Passive Synthetic Aperture Direction-of-Arrival Estimation Method Under the Autonomous Underwater Vehicle Yaw Motion
    🗓 Year: 2024
    📚 Conference: 2024 IEEE OES China Ocean Acoustics (COA)