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Srinila Pogalla

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Srinila Pogalla
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Who I am

I started my journey in AI & Data Science out of curiosity — it was new, exciting, and full of possibility. What I didn't expect was how deeply I'd fall in love with the research and the science behind it.

Originally from India, I made my way to the U.S. — first to Florida Atlantic University, then to the University of North Dakota, drawn by the research opportunities here. Grand Forks surprised me. I came in knowing no one, navigating a new country, a new university, and a new culture all at once — but the city, the people, and the community gave me the foundation to grow. That support made all the difference.

Joining the Computational Research Center at UND was a turning point. I walked in with no software engineering background and built my way up — gaining real hands-on experience in full-stack development and MLOps, while contributing to impactful research including a U.S. Department of Energy funded project at the UND ARCTIC Lab. Alongside that, I independently built projects spanning NLP, RAG systems, ETL pipelines, and data analytics — reflecting my passion for both applied AI and data-driven decision making.

Today I sit at the intersection of both worlds: an engineer who can ship production ML systems, and a researcher who genuinely cares about why models work — and when they don't. I'm actively looking for roles in AI, Machine Learning, and Data Science where I can keep building things that matter.

LinkedIn profile →

Where I've Worked

Jan 2025 — Present
Graduate Research Assistant — Software Engineer
Computational Research Center (CRC), University of North Dakota · Grand Forks, ND, USA
  • As a Graduate Research Assistant, take on a software engineering role helping the team design and develop decision support tools for Arctic and climate resilience research
  • Build scalable full-stack platforms using React, Next.js, TypeScript, FastAPI, GraphQL, and PostgreSQL
  • Build and maintain secure GraphQL and REST APIs for geospatial analytics, climate anomaly monitoring, and AI-powered forecasting applications
  • Develop and integrate machine learning models for wildfire prediction, freeze/thaw forecasting, active layer thickness estimation, and geospatial similarity analysis using Earth Engine based datasets
  • Manage containerized deployments and cloud-native workflows using Docker, Kubernetes, Rancher, and Helm testing locally with kind clusters before deploying to production environments
  • Automate build, testing, and deployment pipelines using GitHub Actions, improving development efficiency, reproducibility, and system reliability across distributed services
  • Author technical reports documenting research methodologies, system architectures, and experimental findings — one of which includes "Integration and Optimization of Kubernetes Cluster"
Current Role

Selected Work

01
Hybrid RAG Framework for Climate Intelligence
Citation-grounded Q&A system using dense (FAISS) + lexical (BM25) hybrid retrieval with ~0.40s latency.
RAGFAISSBM25LLMStreamlit
02
Automated Job Market Analytics Platform
End-to-end ETL pipeline with PostgreSQL and Power BI dashboards delivering weekly hiring trend insights.
ETLPostgreSQLPower BIAutomation
03
Context-Aware Autocorrect System
Hybrid BERT + T5 NLP framework for high-accuracy text correction, validated with WER and CER metrics.
BERTT5NLPTransformers

Beyond the Classroom

AGU 2025 Conference
Conference · Research
AGU 2025 — American Geophysical Union Annual Meeting
Attended AGU 2025 in New Orleans, Louisiana as a presenting member of the UND ARCTIC Lab team. Shared the lab's work with the wider scientific community, coinciding with the team's December publication in the AGU JGR Machine Learning and Computation journal.
Data Visualization · Research
Border Crossing Dynamics: Multi-Chart Exploratory Analysis
Developed ten Tableau visualizations analyzing U.S.–Canada and U.S.–Mexico land border crossing data from 1996–2024. Uncovered temporal trends, geographic clusters, mode-specific patterns, and outliers across 160+ ports using advanced preprocessing and statistical methods.
Grand Forks Summer Intern Cohort
Community · Internship
Grand Forks EDC Summer Intern Cohort
Selected as part of the Grand Forks Economic Development Corporation's Summer Intern Cohort — a program connecting university interns with the local business community to foster professional growth, networking, and regional economic engagement.

Credentials & Licences

Mentors Helping Mentors
University of North Dakota
View Certificate ↗
AWS SageMaker & EKS
Amazon Web Services
View Certificate ↗
Data Classification and Summarization Using IBM Granite
IBM
View Certificate ↗
The AI Ladder: A Framework for Deploying AI in your Enterprise
IBM
View Certificate ↗

Let's Connect

I'm actively looking for internships, research roles, and full-time positions in ML and Data Science. Whether you have an opportunity or just want to talk — I'd love to hear from you.

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Certificate