HPC & distributed systems
I’m interested in the systems and infrastructure behind large-scale computation, and how they can use shared and heterogeneous resources effectively.
- High-performance computing
- Distributed systems
PhD student & Graduate Research Assistant
Sunil Shrestha.
I’m a PhD student at Rochester Institute of Technology, exploring how computing systems can balance performance, resources, and energy.
Working in HPDSL, advised by
Prof. M. Mustafa Rafique.
Computing and Information Sciences Research informed by engineering.
What I’m exploring
Research
interests
My interests center on making better use of computing resources, from distributed infrastructure to the demands of machine learning.
Collaborate on researchResource & energy-aware scheduling
I want to understand how scheduling decisions shape resource utilization, performance, and energy use, and how to balance these competing goals.
- Resource scheduling
- Energy-aware computing
Machine learning & AI
My interests include ML and AI, both as workloads that place new demands on computing systems and as tools for understanding and solving practical problems.
- Machine learning
- Artificial intelligence
Selected work
Projects from my engineering and applied ML background.
Applied ML · Previous work at AFID
Automated fish identification
Working with conservation researchers to bring fish identification and measurement into a practical ML application.
My contribution
At AFID, I collaborated with fish ecologists and conservation experts on automated identification and measurement. My work included ML data and training pipelines, application development, CI/CD, and Kubernetes deployment on Oracle Cloud.
- Computer vision
- ML pipelines
- Kubernetes
Open source · Observability
Tracing asynchronous workloads
OpenTelemetry instrumentation for Dramatiq, bringing tracing into Python’s background task processing.
My contribution
I developed opentelemetry-instrumentor-dramatiq to instrument Dramatiq applications with OpenTelemetry. The package lets an application enable instrumentation alongside its task actors and tracing setup.
- Python
- OpenTelemetry
- Dramatiq
Open source · Task processing
Task results, backed by Django
A result backend that connects Dramatiq tasks with Django’s database layer.
My contribution
I developed django-dramatiq-result-backend to store and retrieve task results through Django’s ORM, with automatic result expiration. It connects background task execution with the application’s existing database tools.
- Python
- Django
- Database systems
Papers &
reports
Earlier academic work, with its original context.
Realization of Mental Hygiene Using Deep Learning
Institute of Engineering, Pulchowk Campus
An undergraduate project exploring sentiment analysis and conversational AI in a mobile application for mental well-being.
About this report
This project explored the integration of deep learning text analysis, conversational AI, and smartphone applications for digital well-being. The team developed a Flutter-based cross-platform application with sentiment analysis as part of the undergraduate project. This is a project report, rather than a peer-reviewed publication.
From building
to researching.
Experience developing software and ML applications shapes the questions I bring to systems research.
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Rochester Institute of Technology
PhD student & Graduate Research Assistant
Computing and Information Sciences. Working in HPDSL with Prof. M. Mustafa Rafique, with interests in HPC, distributed systems, scheduling, and ML/AI.
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AFID
Full Stack Engineer
Collaborated with conservation researchers on fish identification and measurement, and developed ML pipelines, application services, and cloud deployment workflows.
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Logic Information System Nepal
Software Engineer
Worked on information systems, database applications, isolated code execution, and deployment automation with Docker and Kubernetes.
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Sireto Technology
Software Developer Intern
Contributed to CloudFirewall using Python and Linux nftables, including REST and gRPC APIs for state synchronization between virtual machines.
Education
My academic path, from computer engineering to systems research.
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2026 – present
PhD in Computing and Information Sciences
Rochester Institute of TechnologyWorking in HPDSL, advised by Prof. M. Mustafa Rafique.
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2017 – 2021
Bachelor of Computer Engineering
Tribhuvan University · IOE, Pulchowk CampusGraduated with distinction.
Engineering foundation
The technical tools behind my engineering and applied ML work.
System design
Tools from my work on service architectures, interfaces, and distributed applications.
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Go -
Python -
C++ -
Linux
Software engineering
Languages and frameworks I have used to build application services and user-facing software.
- Python
- Go
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JavaScript -
Django -
FastAPI -
React - C++
Database systems
Relational databases and data stores from my software engineering background.
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PostgreSQL -
MySQL -
Redis -
SQLite
Docker
Containerized application development and deployment on Linux.
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Docker - Linux
Kubernetes
Container orchestration and infrastructure tools used in cloud deployment workflows.
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Kubernetes - Docker
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Terraform -
Oracle Cloud
DevOps
Version control, deployment automation, and cloud platforms from my engineering work.
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Git - Docker
- Kubernetes
- Terraform
- Linux
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AWS -
Azure -
Google Cloud - Oracle Cloud
ML & AI
Tools from my applied machine learning and computer vision background.
- Python
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PyTorch -
TensorFlow -
NumPy -
Pandas -
Computer vision
Let’s compare notes.
I welcome conversations about systems research, efficient computing, and ML. Get in touch to exchange ideas or explore a collaboration.
My research home HPDSL
High Performance Distributed Systems Laboratory
Rochester Institute of Technology