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.

 

 

Mehr Un Nisa | Telecommunications | Best Researcher Award

Ms. Mehr Un Nisa | Telecommunications | Best Researcher Award

Ms. Mehr Un Nisa -PhD student, AGH university of krakow, Poland.

Mehr Un Nisa is a passionate and versatile academic and professional with a strong foundation in computer systems engineering. She is currently pursuing a Ph.D. in Computer Science and Telecommunications at AGH University in Krakow, Poland. Known for her commitment to excellence and innovation, Mehr brings a multidisciplinary background that encompasses research, teaching, IT operations, and data analysis. Her expertise spans technical domains such as image processing, cybersecurity, and artificial intelligence. With her combined academic and industrial exposure, Mehr aims to create meaningful solutions, especially in underwater content analysis and smart system security, contributing to both academic advancements and practical applications.

Publication Profile

ORCID

Education Background

Mehr holds a robust academic portfolio, beginning with a Bachelor’s degree in Computer Systems Engineering (2014–2018) and followed by a Master’s in Computer Systems Engineering (2018–2021) from UET Peshawar, Pakistan. Her bachelor’s thesis focused on facial recognition systems, while her master’s work developed a cybersecurity framework for GPS-protected smart containers using PGP encryption. Currently enrolled in a Ph.D. program at AGH University, Krakow, she is researching underwater visual content analysis, exploring both objective and subjective methods for quality assessment. Her academic trajectory reflects a deep commitment to technical rigor, innovation, and research-driven problem-solving in modern computing environments.

Professional Experience

Mehr has a diverse professional journey marked by significant roles in academia, industry, and research. She served as a Junior Manager Operations at Unilever Pakistan and previously worked at Nestle Pakistan in operations and sales. Her academic experience includes teaching microprocessors, digital logic design, and object-oriented programming as a visiting faculty member at IMSciences. She also worked as an IT support officer at Telenor and as a research assistant at the National Center for Cyber Security, where she led experiments on smart sensors and data analytics. Her roles across sectors highlight her adaptability and multifaceted engineering competence.

Awards and Honors

Mehr has earned recognition through certifications and prestigious course completions in advanced computing and cybersecurity. She successfully completed the 8th Advanced Course on Data Science and Machine Learning (ACDL 2025) and a crash course in Cyber Security from KPCERC KPITB Peshawar. Additionally, she acquired training in marketing automation strategies. While currently undertaking her Ph.D. research, her growing publication record in peer-reviewed journals and conferences also reflects her standing in the academic community. Her continuing efforts in interdisciplinary fields position her as a strong candidate for future academic honors and awards.

Research Focus

Mehr’s research centers on computer vision, deep learning, cybersecurity, and smart systems. Her Ph.D. thesis is dedicated to underwater content analysis, developing systems for visual quality validation using technical descriptors, cognitive modeling, and dataset formulation. She also has research experience in secure GPS communications, face recognition, and image classification using convolutional neural networks. Through a blend of experimental design and computational modeling, her work aims to improve the reliability and security of intelligent systems and enhance human-computer interaction in visually complex environments such as AR/VR and underwater imagery.

Top Publications Notes 

  1. Improved Binary Classification of Underwater Images Using a Modified ResNet-18 Model
    Published in – 2025
    Citation: Cited by 3 articles

  2. Unveiling the Art of Video Enhancement: A Comprehensive Examination of Content Selection and Sequencing for Optimal Quality in Conventional and AR/VR Environments
    Published in – 2025
    Citation: Cited by 2 articles

  3. Comparative Performance Analysis of Deep Learning Architectures in Underwater Image Classification
    Published in. – 2024
    Citation: Cited by 1 article

  4. Minutia Extraction Based Electronic Voting Machine
    Published in– 2023
    Citation: Cited by 1 article

  5. A Comprehensive Study of GPS Communication Security
    Published in– 2022
    Citation: Cited by 2 articles

  6. Application of Deep Convolution Neural Network for Image Classification: A Review
    Published in– 2022
    Citation: Cited by 1 article

  7. A New Strategy to Enhance the Security of GPS Location by PGP Algorithm in Smart Containers
    Published in – 2022
    Citation: Cited by 2 articles

  8. Implementation of Novel PGP Algorithm for Encrypted GPS Communication in Smart Containers
    Published in – 2021
    Citation: Cited by 3 articles

Conclusion

Mehr Un Nisa exemplifies a well-rounded researcher and practitioner in the field of computer science and telecommunications. With a blend of academic strength, industrial engagement, and a proactive learning approach, she continues to explore critical research areas with real-world impact. Her evolving contributions in image classification, cybersecurity, and intelligent systems demonstrate her capability to bridge theoretical understanding with practical innovation. She is poised for a promising future in research and academia, contributing significantly to emerging technologies and global knowledge communities.