Akshita Ramya Kamsali

Selected Publications

1. IEEE-WRAP

   Experimental Verification of Enhanced Photoluminescence in p-doped GaAs using Fluorescence Lifetime Measurements

   Ramya, Kamsali Akshita, Jinal, Tapar, Saurabh, Kishen, and Emani, Naresh Kumar

   In 2019 Workshop on Recent Advances in Photonics (WRAP) Dec 2019

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   The realization of low threshold, room temperature operation of semiconductor NIR nanolasers is still a challenge. Large surface-to-volume ratio of the nanostructures aggravates surface recombination leading to non-radiative decay of excited carriers. P-doping of active material is a viable solution to bring down the lasing threshold without surface passivation. Here, we report an improved quantum yield of p-doped GaAs over intrinsic, with the help of carrier lifetime measurement using FLIM system. We aim to study how the onset of the Auger process affects the PL and carrier lifetime at higher pump fluence.

2. NeurIPS-WiML

   Graph-based Change Detection for Natural Language

   Kamsali, Akshita Ramya

   In Dec 2024

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   Computational models such as machine learning (ML) and deep learning (DL) excel at processing structured data, including numbers, images, audio signals, and spectral data. These types of data can be easily converted into numerical patterns, which models can analyze to extract meaningful insights. In contrast, processing text is significantly more complex. Language is inherently rich, intricate, and nuanced. Techniques like tokenization and word embeddings, which transform text into numerical representations, often struggle to fully capture the subtle context and deeper meaning within the text. Challenges such as context dependency, disambiguation, and diverse writing styles can lead to multiple interpretations of the same text, even for humans. This complexity is further magnified in specialized domains, such as legal or medical documents. In this work we present LLM-based solution to build consistent knowledge graphs for change detection.