Sambit Mishra

PhD Student · USC Viterbi

Learning the structure
of cause and effect.

I’m Sambit Mishra, a first-year PhD student in Electrical & Computer Engineering at the University of Southern California, advised by Prof. Urbashi Mitra. My work centers on causal inference and probabilistic graphical models — particularly scalable continuous-optimization methods for causal discovery in high-dimensional, distribution-shifted data.

Read the researchCurriculum Vitaesambitmi@usc.edu
X₁X₂ZY₁Y₂Y₃

fig. 01 — a directed acyclic graph

Causal Discovery◆Probabilistic Graphical Models◆Continuous Optimization◆Distribution Shift◆Soft Interventions◆Structure Learning◆
Causal Discovery◆Probabilistic Graphical Models◆Continuous Optimization◆Distribution Shift◆Soft Interventions◆Structure Learning◆

§ 01 — Currently

Three threads I’m pulling on.

Reliable structure learning under distribution shift, with applications to fraud detection and high-stakes decision systems.

  1. 01
    Causal discovery
    Continuous-optimization methods for scalable DAG estimation with differentiable acyclicity constraints.
  2. 02
    Intervention design
    Soft-intervention selection frameworks that lower experimental cost while preserving identifiability.
  3. 03
    Identifiability
    Finite-sample and latent-variable regimes — what can structure tell us, and when does it fail?

§ 02 — Selected publications

Recent work.

View all research →
  1. [01]

    ICASSP 2026

    Accepted

    Learning to Intervene: Optimized Soft Intervention Selection for Causal Discovery

    C. Peng, S. Mishra, U. Mitra

  2. [02]

    IEEE TGCN, vol. 10

    2026

    SER-Optimized Multi-Level ASK Modulations for RIS-Assisted Communications With Energy- and Sign-Based Noncoherent Reception

    S. Mishra, S. P. Dash, G. C. Alexandropoulos

    doi: 10.1109/TGCN.2025.3633182
  3. [03]

    IEEE WCL, vol. 15

    2026

    Error Analysis With Optimal Receiver and Multi-Level ASK for RIS-Assisted Noncoherent Wireless System

    S. Mishra, S. P. Dash

    doi: 10.1109/LWC.2025.3624154

§ 03 — Background

From wireless systems to causal graphs.

Before USC, I studied Electronics & Communication Engineering at IIT Bhubaneswar, graduating with a B.Tech (Hons.) in 2025 and a 9.14/10.00 GPA. There I worked with Dr. Soumya P. Dash on SER-optimized modulation schemes for RIS-assisted noncoherent wireless systems — work that has since appeared in IEEE TGCN and IEEE WCL.

I spent the summer of 2024 as an ASIC Engineering Intern at NVIDIA, verifying CHI protocol compliance on the CHI-VIP team. Outside of research I served as General Secretary of the Science & Technology Council at IIT Bhubaneswar, where I led the Inter-IIT Tech Meet team to a top-ten finish among 23 IITs.

These days, I’m drawn to questions at the intersection of optimization theory and inference: when can we recover causal structure cheaply, and what does it take to trust the answer?