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.

 

 

Ms. Hina Magsi | Signal Processing | Best Researcher Award

Ms. Hina Magsi | Signal Processing | Best Researcher Award

PhD Scholar, Sukkur IBA University, Pakistan

Engr. Hina Magsi is a dedicated lecturer at Mehran University of Engineering & Technology, Khairpur, with over four years of experience in research and teaching in the fields of telecommunication, electronics, embedded systems, AI, and machine learning 📚. She is passionate about advancing the education of her students and has co-supervised several impactful projects, including an IoT-based flood monitoring system 🌊, wireless electric vehicle charging 🚗, and a real-time drowsiness detection system 🛣️. Hina has a strong academic background and actively contributes to research in satellite communication and space weather, with a focus on improving navigation systems using adaptive algorithms 📡.

Publication Profile

ORCID

Education

Hina Magsi holds a PhD in Electrical Engineering (Signal Processing) from Sukkur IBA University, where she earned a CGPA of 3.57 🎓. She completed her M.E. in Electronics and Communication from the same university with a CGPA of 3.47, and her B.E. in Telecommunication Engineering from Mehran University of Engineering & Technology with an impressive CGPA of 3.72. Her thesis topics include MIMO CO-OFDM in Free Space Optical Communication and Received Signal Quality Monitoring (RSQM) algorithms for improved navigation 🧠.

Experience

With diverse experience, Engr. Magsi has worked as a lecturer at Mehran University of Engineering & Technology, delivering courses across various electronic engineering subjects. She previously served as a research associate at Sukkur IBA University, focusing on satellite communication and space weather. Engr. Magsi also worked as a research assistant in bio-sensing, developing adaptive battery-aware methods for smart healthcare systems 💡. Early in her career, she gained practical experience at PTCL and SAKI Institute Sukkur.

Research Interests

Her primary research interests include satellite communication, signal processing, IoT applications, real-time monitoring systems, AI and machine learning in engineering, and adaptive algorithms for improved navigation accuracy 📡🔍. She is particularly interested in applying these technologies to healthcare and transportation systems 🚑🚗.

Awards

Engr. Magsi has received several prestigious awards, including merit-based scholarships at Mehran University and Sukkur IBA University 🎓, as well as the International Merit Scholarship for her Ph.D. at Sukkur IBA University. She has also received funding for research projects from HEC NRPU and has been recognized for her contributions to education and research 🌟.

Publications

  • Accurate Monitoring and Timely Prediction of Ionospheric Scintillation Using Support Vector Machine
  • Improved Navigation Based on Received Signal Quality Monitoring (RSQM)
  • Adaptive Data Length Method for GPS Signal Acquisition in Weak to Strong Fading Conditions
  • Decentralized Energy Efficient Model for Data Transmission in IoT-based Healthcare System
  • A Novel Adaptive Battery-Aware Algorithm for Data Transmission in IoT-based Healthcare Applications