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Srinila Pogalla

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Srinila Pogalla

Who I am

I started my journey in AI & Data Science out of curiosity. It was new, exciting, and full of possibility. Pursued Bachelor of Engineering in Artificial Intelligence & Data Science at Stanley College of Engineering and Technology, Hyderabad, India, and somewhere along the way, what began as curiosity became the foundation of everything I do today: building systems that think, learn, and solve real problems.

I made my way to the U.S., first to Florida Atlantic University, and then to the University of North Dakota, drawn by the research opportunities here. Moving to Grand Forks brought me into a new environment, a different academic culture, and a completely new way of life. Over time, the city, the people, and the community helped me grow, both personally and professionally. That support made a lasting difference in my journey.

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 Defense funded project at the UND ARCTIC Lab. Alongside that, I independently built projects spanning NLP, RAG systems, agentic AI, 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 do not. I am actively looking for roles in AI Engineering, ML Engineering, Data Engineering, and Data Science where I can continue building things that matter.

Where I've Worked

Jan 2025 — Present
Graduate Research Assistant — Software Engineer
Computational Research Center (CRC), University of North Dakota · Grand Forks, ND, USA
  • Contribute to the design and development of full-stack decision support tools for Arctic and climate resilience research on a DOD-funded platform, working across the stack from API layer to frontend integration.
  • Optimized geospatial data processing pipeline by consolidating 896 individual Google Earth Engine API calls into 3 batch calls using sampleRegions() and parallelizing downstream processing with Python multiprocessing (Pool across all available CPU cores) — reducing processing time from approximately 40 minutes to approximately 4 minutes (90% reduction).
  • Extended and maintained REST APIs built with FastAPI to serve geospatial analytics, climate anomaly monitoring, and AI-powered forecasting applications for wildfire prediction, freeze/thaw forecasting, active layer thickness estimation, and geospatial similarity analysis using Google Earth Engine-based datasets.
  • Worked within a containerized, cloud-native environment using Docker, Kubernetes, Rancher, and Helm, testing locally with kind clusters before deploying to production environments.
  • Built frontend interfaces and connected them to backend data services using React, Next.js, and TypeScript.
  • Automated build, test, and deployment pipelines using GitHub Actions, maintaining consistency and reproducibility across distributed services.
  • Authored technical reports on system architecture and research methodology, including "Integration and Optimization of Kubernetes Cluster", "Apptainer Runtime Integration", "Globus-Based Disconnected Data Transfer Workflows", and "NVIDIA Spark Compute".
Current Role

Research Publications

Preprint · 2025
ASAP: A Web-based Analysis and Decision Support System for Alaska Permafrost
Stephen Miller, Sheridan Parker, Srinila Pogalla, Andrew Wilcox, Timothy Pasch
ESSOAr · Earth and Space Science Open Archive · University of North Dakota

Selected Work

01
Agentic Analytics System
16-agent orchestration system using Anthropic's Model Context Protocol (MCP) and Claude API for automated multi-step data analysis and insight generation.
MCPClaude APIAgentic AIFastAPIPostgreSQL
02
Hybrid RAG Framework for Climate Intelligence
Citation-grounded Q&A system using dense (FAISS) + lexical (BM25) hybrid retrieval with cross-encoder reranking at ~0.40s latency.
RAGFAISSBM25LLMStreamlit
03
Context-Aware Autocorrect System
Hybrid BERT + T5 NLP framework for high-accuracy text correction, evaluated on 8 metrics including WER, CER, and CharAcc 93.88%.
BERTT5NLPTransformers
04
Automated Job Market Analytics Platform
End-to-end ETL pipeline with medallion architecture, 10 automated quality checks, PostgreSQL, and Power BI dashboards delivering weekly hiring trend insights.
ETLPostgreSQLPower BIMedallion Architecture
05
Border Crossing Dynamics: Multi-Chart Exploratory Analysis
Ten Tableau visualizations analyzing U.S.–Canada and U.S.–Mexico land border crossing data from 1996–2024, uncovering temporal trends and geographic patterns across 160+ ports.
TableauData VisualizationEDAGeospatial

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.
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

AWS Cloud Practitioner Essentials
AWS Training & Certification
View Certificate ↗
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 AI Engineering, ML Engineering, Data Engineering, and Data Science. Whether you have an opportunity or just want to talk — I'd love to hear from you.

Send a message
Certificate