Saksham Dewan

PhD Researcher University at Albany — SUNY

Advisor: Dr. Hany Elgala

I design waveforms for wireless and optical communication systems.

Get in touch:

Google Scholar GitHub LinkedIn
Portrait of Saksham Dewan

Research

I study applications of machine learning and artificial intelligence for physical layer waveform design and signal processing in wireless and optical communications. My research explores how learning-based methods can improve the reliability, efficiency, and adaptability of communication systems.

Current projects focus on learned waveforms, adaptive constellations, and receiver methods that address channel impairments and hardware constraints.

Ongoing research

Learned waveforms for fractional delay-Doppler channels

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 orthogonal time frequency space (OTFS) modulation and affine frequency division multiplexing (AFDM) under matched channels and receiver budgets to understand where adaptation helps.

Collaboration with IBM T.J. Watson Research Center
IEEE MILCOM 2026Publication details

Learned waveforms for robustness to residual CFO

Jointly learning transmit and receive bases to reduce interference from residual carrier frequency offset (CFO), alongside a model-guided receiver that refines symbol estimates.

The work explores the tradeoff between communication reliability and peak-to-average power ratio (PAPR).

Collaboration with IBM T.J. Watson Research Center
IEEE ICMLCN 2026Publication details

Enabling non-power-of-two modulations in VLC constellations

Learning constellation geometry and receiver decisions together under light-emitting diode (LED) clipping constraints, including modulation orders beyond the usual powers of two.

This allows finer control of transmission rate in visible light communication (VLC) systems.

Master’s thesisThesis

Exploring multi-task learning and defining task relationships in VLC

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.

Publications

Google Scholar
  1. 2026

    Jointly Learned Waveforms for Residual CFO Robustness and PAPR Reduction

    Saksham Dewan, Hany Elgala, Asaf Tzadok, and Ming-Ching Chang

    IEEE MILCOM 2026Code

  2. 2026

    End-to-End Learned Non-Power-of-Two Constellations for Adaptive VLC Transmission

    Saksham Dewan and Hany Elgala

    IEEE ICMLCN 2026Code

  3. 2025

    Leveraging Multi-Task Learning to Model Task Relationships in Composite VLC Waveform Demodulation

    Saksham Dewan, Hany Elgala, Sami Muhaidat, and Paschalis Sofotasios

    Applied OpticsVol. 643, Issue 29, pp. 8716–8721Code

  4. 2024

    Towards Low Complexity VLC Systems: A Multi-Task Learning Approach

    Saksham Dewan and Hany Elgala

    Communications & Networks ConnectVol. 1

Collaborative work

  1. 2026

    Optical OFDM Modulation Identification with Deep Learning

    Honglan Chen, Hany Elgala, Saksham Dewan, and Siyuan Cheng

    IEEE ICMLCN 2026

  2. 2025

Education

  1. 2023 — Present

    Doctor of Philosophy, Electrical & Computer Engineering

    University at Albany — SUNY Albany, NY, USA

  2. 2022 — 2024

    Master of Science, Electrical & Computer Engineering

    University at Albany — SUNY Albany, NY, USA

  3. 2017 — 2021

    Bachelor of Technology, Electrical Engineering

    Punjab Engineering College Chandigarh, India

Experience & service

Doctoral research & service

  1. Jan 2026 — Present

    Research Assistant

    University at Albany — SUNY Albany, NY, USA

    In collaboration with IBM, developing learned waveforms for fractional delay–Doppler channels and robustness to residual CFO, with receiver-aware design and evaluation against conventional baselines.

  2. Jun 2026

    Peer reviewer

    IEEE Transactions on Communications

Graduate teaching & campus service

  1. Jan 2023 — Dec 2025

    Teaching Assistant

    University at Albany — SUNY Albany, NY, USA

    • ECE 111: Introduction to ECE
    • ECE 231: Digital Systems
    • ECE 401: Advanced Electronic Circuits
    • ECE 422: Integrated Circuits
    • ECE 431: Reconfigurable Computing
    • ECE 481: Linear Control Theory
  2. May — Aug 2025

    Graduate Assistant, The Honors College

    University at Albany — SUNY Albany, NY, USA

    Returned to support preparation for Honors Orientation 2025 and related Honors College activities.

  3. Aug — Dec 2022

    Graduate Assistant, The Honors College

    University at Albany — SUNY Albany, NY, USA

    Supported student programming, communications, orientation, and student-leader development for The Honors College.

    Graduate Ambassador, The Graduate School

    Represented the university in prospective-student webinars and supported applicants and newly admitted graduate students.

Industry experience

  1. Jun 2020 — Jan 2022

    Technical Product Manager

    Kolligate Seattle, WA, USA Remote

    • Led delivery of a dental staffing platform, including feature planning, payment integration, and onboarding workflows; supported 300+ users in its first quarter.
    • Designed 120+ screens across web, iOS, and Android; coordinated engineering priorities, QA, and vendors.
  2. May — Dec 2021

    Full-Stack Developer

    Busywizzy Gurugram, India

    • Led a seven-person team delivering Kolligate and designed Laravel/MySQL REST APIs for web and mobile applications.
    • Authored 200+ test cases covering functionality and performance requirements.
  3. Jan — Jun 2020

    Full-Stack Developer Intern

    Quantela Bengaluru, India

    • Developed a real-time COVID-19 dashboard covering India and worldwide statistics.
    • Built Angular/TypeScript components and integrated Node.js APIs and municipal data feeds.