Presetion is titled:

“Spectrum Coexistence Between Active Technologies and Passive Sensors”

This presentation will focus on the growing challenge of radio-frequency interference (RFI) in passive remote sensing systems, and emerging methods to ensure spectrum sharing. I will also discuss results from our custom testbed and the application of deep learning–based solutions such as RFI-Net.

I’m honored to share our group’s research and contribute to the broader discussion on enabling robust and interference-aware sensing technologies.

I’m thrilled to announce that I have officially advanced to Ph.D. Candidacy at NC State University!

Successfully completing my preliminary exam marks a major milestone in my doctoral journey, and I’m deeply grateful to my committee for their guidance and support.

Committee Chairs and Members:

• Dr. Ali Gurbuz (Advisor)
• Dr. Ismail Guvenc
• Dr. Vijay Shah
• Dr. Yuchen Liu

I look forward to continuing research in spectrum coexistence, radar signal processing, and machine learning for remote sensing—and contributing to the broader research community.

Thank you to everyone who’s supported me along the way!

I’m excited to share that I’ve transferred to North Carolina State University to continue my Ph.D. studies in Electrical Engineering under the supervision of Dr. Ali Cafer Gurbuz.

This transition marks an exciting new phase in my academic journey, offering the opportunity to further explore cutting-edge research in wireless sensing, signal processing, and spectrum coexistence.

Looking forward to collaborating with a vibrant research community and contributing to impactful work in this new environment.

As my 6-month Co-Op in Audio Machine Learning and DSP Research at Bose Corporation comes to an end, I’m incredibly grateful for an experience filled with growth, collaboration, and innovation.

Over this period, I had the privilege of working with a cross-functional, highly talented team on cutting-edge projects blending acoustics, signal processing, and machine learning—delivering promising results with potential impact in spatial audio and listening zone-based EQ.

Highlights

• Collaborated closely with researchers and engineers across disciplines.
• Attended AES Show 2024 and SANE 2024 – Speech and Audio in the Northeast, gaining new insights and connecting with leading experts.
• Advanced research combining acoustics, ML, and DSP to push the boundaries of immersive sound.

Gratitude

Special thanks to my manager Miriam Israelowitz and Shuo Zhang for their mentorship, guidance, and constant encouragement. I’m also deeply appreciative of the Audio Systems Research group and Bose R&D for fostering a collaborative and inspiring environment.

This journey has strengthened my passion for audio technology and reaffirmed my commitment to contributing to the field.
Here’s to the next chapter! 🚀

Keywords: Audio Machine Learning, DSP, Spatial Audio, Research, Bose

I am honored to have been selected as the Winner of the Spring 2024 Graduate Research Symposium at Mississippi State University. This recognition was awarded for my research presentation on “Microwave Radiometer Calibration Using Deep Learning with Reduced Reference Information and 2-D Spectral Features.”

The symposium celebrated outstanding graduate research across disciplines, and I am grateful for the opportunity to share my work and represent our research group.

This recognition motivates me to continue contributing impactful work in the fields of signal processing and remote sensing.