Anish Shrestha

About Me: I like to solve problems with code. I have an appetite for feedback, sharing, growth, and continuous improvement. Outside my study and work, I like outdoor sports, trekking, and cycling.

Reach me out anywhere! I will respond.
2023
I am a Software Engineer working for Bioinformatics and Computational Biosciences Branch of NIAID. I am working primarily with Python-based tools such as Flask for web development and Prefect for workflow deployment. The softwares are heavily used by micro-biologists and microscopy experts.
2021
I was a graduate research assistant in Department of Computer Science at Miami University. I worked in DACHB lab under the supervision of Dr. Giabbanelli. We emphasized on using emerging technologies to solve lackings in participatory modeling, such as using emerging LLMs like GPT to automatically explain concept maps and Microsoft Hololens to enable modelers to collaborate virtually in a remote environment setting.
I am also enrolled in Master's degree in Computer Science. I intend to graduate at the end of Spring 2023.
2020 - 2021
I was a software developer at Togglecorp. Togglecorp is a private company aiming for humanitarion aid through data. I worked on an administrative web application for Internal Displacement Monitoring Centre (IDMC) to monitor displacements across the globe.
2018 - 2019
I was a full-stack developer at WhyUnified.
2016 - 2019
I was a software developer at Infinia Hub.
Here is where I started coding as a professional. I came across the most amazing people in the industry while I was working there. Therefore this workplace has some of the fondest memories.
2012 - 2016
Bachelor in Computer Engineering at Tribhuvan University. This is where I first got exposed to nits and bits of computer science. I, along with few of my classmates, created a machine learning application for recognizing facial expressions. We were advised by Dr. Joshi.
Research

My research interests lie in web and data science especially in the health domain.

I researched on Natural Language Generation using OpenAI's GPT and their effectiveness on less-explored domains like causal mapping and health informatics. I was able to publish this work at "Proceedings of the 2022 Winter Simulation Conference, ACM/IEEE" which you can find here: PAPER.

I also got the opportunity to work in mixed reality using HoloLens 2. Being able to work in such emerging technologies is simply astounding.
The DEMO of our work is shown here: YOUTUBE, and our work as of the current state is available publicly in Open Science Framework.

Publications & Appearances

  • Shrestha, A., Mielke, K., Nguyen, T.A., Giabbanelli, P.J. (2022) Automatically explaining a model: using deep neural networks to generate text from causal maps. Proceedings of the 2022 Winter Simulation Conference, ACM/IEEE. [Link]
  • Automatic text generation to explain simulations. Symposium on Natural Language Processing and Simulation, 2022, Miami University [Link]
Miscellaneous
View my resume. You can download it here: github