NIST UNIVERSITY
Institute Park, Berhampur, Odisha-761008, India

Bandhan Panda

Mr. Bandhan Panda

Assistant Professor

Computer Science and Engineering (SCHOOL OF ENGINEERING)

bandhan.panda@nist.edu
9178990836
OCT - 206

Education

No education details available.

Work Experience

No experience details available.

Research Interests

  • No research interests available.

Publications

  1. Swain, S., Swain, S., Panda, B. and Tripathy, M.C., 2025. Modeling and optimal analysis of lung cancer cell growth and apoptosis with fractional-order dynamics. Computers in Biology and Medicine, 188, p.109837.
  2. This study explores the application of fractional-order calculus in modeling lung cancer cell growth dynamics, emphasizing its advantages over traditional integer-order models. Conventional models often fail to capture the complexities of tumor behavior, such as memory effects and long-range interactions. The fractional-order logistic equation provides a more sophisticated framework that integrates intrinsic growth rates and environmental constraints, enabling a nuanced analysis of tumor progression and treatment responses. A key component of this research involves deriving a Laplace domain representation to assess transfer function characteristics, which aids in evaluating stability and response across various frequency domains. An improved fractional-order model was developed to illustrate the interplay between cancer proliferation and immune response mechanisms.
  3. This review article systematically surveys recent advancements in generative diffusion models and Gaussian splatting techniques as they are applied to augmented reality (AR) and virtual reality (VR) systems. It synthesizes developments in text-to-3D generation workflows, highlights frameworks that improve visual fidelity and generation efficiency (e.g., Turbo3D, Dive3D), and examines challenges such as computational intensity, multi-view consistency, and lack of standardized benchmarks. The review also identifies future research directions aimed at making 3D content generation faster, more physics-aware, and better evaluated across methods.