PhD researcher · University at Albany
I study how machine learning can shape the signals we transmit and the receivers that recover them.
My research connects wireless and optical communications with learning—working toward reliable systems under channel impairments, hardware limits, and constrained computation.
01 / Research
What can we gain by learning the waveform and receiver together? I explore this question across radio-frequency and optical systems, with particular attention to robustness and receiver complexity.
Designing waveform bases that reorganize how symbols interact in fractional delay–Doppler channels, so a receiver can focus on a limited number of dominant interactions.
Comparing learned designs with OTFS and AFDM under matched channels and receiver budgets to understand where adaptation helps.
Jointly learning transmit and receive bases to reduce interference from residual carrier-frequency offset, alongside a model-guided receiver that refines symbol estimates.
The work explores the tradeoff between communication reliability and peak-to-average power ratio.
Learning constellation geometry and receiver decisions together under LED clipping constraints, including modulation orders beyond the usual powers of two.
This allows finer control of transmission rate in visible light communication systems.
Using cross-stitch neural networks to recover multiple information streams within a composite VLC waveform, sharing useful features between related demodulation tasks.
An interpretable measure of task dependence helps explain when that shared processing is useful.
02 / Publications
IEEE MILCOM Accepted for presentation
IEEE ICMLCN Presented
IEEE ICMLCN Presented
Applied Optics · 64(29), 8716–8721
Communications & Networks Connect · 1(1)
Collaborative work · IEEE MECOM 2025
Manuscript · Submitted
Submitted to IEEE Communications Magazine.
03 / Background
Before my doctoral research, I worked across software development and technical product delivery. That experience continues to inform how I approach research: from a promising idea to a system that works.
University at Albany–SUNY
Expected December 2028. Research assistant through the University at Albany–IBM collaboration since January 2026.
University at Albany–SUNY
Multi-task learning for composite VLC waveform demodulation.
Punjab Engineering College · Chandigarh, India
IEEE Transactions on Communications
University at Albany–SUNY
ECE fundamentals, digital systems, control theory, reconfigurable computing, and integrated circuit devices.
Kolligate · Busywizzy · Quantela
Technical product management and full-stack development, including a dental staffing platform and a real-time public-data dashboard.
Tools I work with
Python / PyTorch / MATLAB / TensorFlow / CUDA / Linux / Git
04 / Contact
For conversations about research, collaboration,
or opportunities in wireless systems and machine learning.