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Yogith Ramanan

Open to internships & full-time opportunities

Yogith Ramanan

Computer Science Graduate Student · Software Engineer · Cloud · Backend · AI/ML · DevOps

Cloud-native systems, production-grade APIs, ML pipelines, and serverless architectures — engineered for reliability, scale, and real-world impact.

I'm an M.S. Computer Science candidate at DePaul University, specializing in software engineering, cloud engineering, backend development, full-stack development, machine learning, and DevOps. I've shipped production features, resolved critical incidents, and built AWS-native pipelines, REST APIs, and CI/CD workflows through internships and academic projects. My current focus is research on carbon-aware scheduling for multi-region AI inference. I'm driven by scalable architecture, observability, automated testing, reproducible workflows, and clear cross-functional communication.

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Yogith Ramanan, professional portrait

Profile

About me

Education, technical focus, and the engineering mindset behind every project.

I'm pursuing an M.S. in Computer Science at DePaul University, building on my B.E. in Computer Science from Sri Krishna College of Engineering and Technology. My academic path reflects a strong foundation in software engineering, now extended with graduate-level work in cloud systems, backend architecture, applied machine learning, and DevOps pipelines.

I'm motivated by roles where reliability, scalability, and clarity matter — designing and operating backend services and APIs, shipping cloud-native and serverless systems, and applying machine learning where it delivers measurable outcomes. I'm comfortable working across the full stack when needed, with particular interest in integration, observability, and systems that teams can test, monitor, and improve with confidence.

My internship experience in product development support and full-stack delivery taught me how production issues surface for real users and how disciplined debugging, clear documentation, and proactive communication accelerate fixes. I bring a consistent bias toward automation, testing, and reproducible workflows — habits I've sharpened through coursework, hands-on projects, and research.

Campus photo

  • Graduate study

    M.S. Computer Science

    DePaul University · Chicago, IL · 2025–present

  • Undergraduate

    B.E. Computer Science

    Sri Krishna College of Engineering and Technology · 2020–2024

  • Professional focus

    Software · Cloud · Backend · AI/ML

    Full-stack delivery, cloud-native systems, applied ML & research

Work

Experience

Hands-on experience delivering production-grade software, supporting live systems, and building end-to-end features under real-world constraints.

  1. Product Development and Support Engineer Intern

    January 2024 – June 2024

    GURU Information Technology Services

    Chennai, Tamil Nadu, India

    • HTML / CSS / JavaScript
    • Production support
    • Incident response
    • Cross-functional communication
    • Diagnosed and resolved customer-facing UI issues across HTML, CSS, and JavaScript — reproducing defects, isolating root causes, and validating fixes end-to-end before deployment.
    • Triaged and responded to production incidents under time pressure, reproducing issues, identifying causes, and coordinating with engineering teams to deploy resolutions, minimizing user impact and downtime.
    • Authored clear defect reports and technical documentation that accelerated resolution cycles and enabled non-engineering teams to understand and communicate fixes to stakeholders.

  2. Full Stack Intern

    July 2022 – September 2022

    Gateway Software Solution

    Coimbatore, Tamil Nadu, India

    • Full-stack
    • Dashboards
    • GitHub workflows
    • Built and iterated on web components that surfaced backend data as interactive dashboards and customer-facing screens, improving data accessibility and user workflow efficiency.
    • Worked across frontend, backend, and database layers as requirements evolved, prioritizing stability, minimizing regressions, and ensuring consistent delivery.
    • Followed GitHub-based branching, code review, and merge workflows to keep changes traceable, well-documented, and ready for confident deployment.

Research

Featured research

Research in cloud-scale AI inference, carbon-aware scheduling, and simulation-driven evaluation for sustainable infrastructure.

Research highlight

Carbon-Aware Scheduling for Multi-Region AI Inference

January 2026 – March 2026

  • Python
  • Cloud systems
  • Simulation
  • Sustainability

This research explores how AI inference workloads can be routed across global cloud regions when both carbon intensity and latency constraints must be simultaneously optimized. The work involved building a discrete-event simulator using real-world workload traces, designing adaptive hybrid routing policies, and benchmarking them against static geographic and carbon-only baselines to identify strategies that reduce carbon impact without violating service-level objectives (SLOs).

View paper (PDF)Repository

Key outcomes

  • Constrained Hybrid routing policy — 54.8-point reduction in carbon intensity while meeting latency SLOs
  • Adaptive Hybrid controller — dynamically selects the best-performing policy based on real-time conditions
  • Pareto analysis across policies — trade-off characterization between carbon savings, latency, and cost
  • Simulation framework grounded in real AWS pricing, carbon intensity data, and network latency metrics

Builds

Projects

Selected projects demonstrating cloud engineering, applied machine learning, full-stack development, and production-ready system design.

Screenshot placeholder. Replace the file at /images/projects/drug-prioritization.jpg or point imageSrc to your asset in src/data/portfolio.ts.

Featured project

Cloud-Native Multimodal AI Platform for Drug Candidate Prioritization

February 2026 – April 2026

End-to-end pipeline for drug candidate scoring, combining molecular structure features with multimodal learning. Built a FastAPI backend serving the trained model with containerized deployment via Docker, enabling scalable inference for chemistry and biotech workflows.

  • Python
  • RDKit
  • PyTorch
  • scikit-learn
  • MLflow
  • FastAPI
  • Docker Compose
  • GitHub Actions
  • Prometheus
  • pytest

Highlights

  • YAML-driven training workflows with structured evaluation across classical, tree-based fusion, and GCN-style graph–tabular fusion models.
  • Deterministic ranking with descriptor penalties, confidence, tie-breaks, and reason codes for explainable decision support.
  • Containerized FastAPI service (predict / rank / batch-rank), Docker Compose packaging, automated tests, and metrics-ready instrumentation.
DemoRepository

  • Screenshot placeholder. Replace the file at /images/projects/a2a-sdk.jpg or point imageSrc to your asset in src/data/portfolio.ts.

    A2A Java SDK — Agent-to-Agent Communication Platform

    January 2025 – June 2025

    Designed and implemented a Java SDK for agent-to-agent messaging, featuring strongly typed contracts, streaming response handling, and task lifecycle management — enabling structural interoperability between autonomous AI agents.

    • Java
    • Maven
    • JUnit
    • Streaming APIs
    • Structured logging

    Highlights

    • Typed request/response models with metadata for extensible agent protocols.
    • Streaming handlers and structured logs to support observability across calls.

    +1 more in full resume

    DemoRepository

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    Food Calorie Tracker

    August 2025 – October 2025

    Streamlit-powered food recognition app using MobileNetV2 on the Food-101 dataset for calorie estimation and nutritional tracking. Deployed as an interactive web application with real-time image classification.

    • Python
    • TensorFlow
    • MobileNetV2
    • Streamlit
    • Food-101

    Highlights

    • Transfer learning with MobileNetV2 plus filtering to reduce non-food traffic.
    • Caching and preprocessing tuned for responsive CPU inference.

    +1 more in full resume

    Live demoRepository

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    Serverless Document Processing System (AWS)

    December 2025 – January 2026

    Event-driven document processing pipeline on AWS using S3 triggers, Lambda functions, and Amazon Textract for asynchronous text extraction with idempotent processing and DynamoDB-backed state management. REST API with API-key authentication, latency monitoring, and error tracking via CloudWatch.

    • AWS Lambda
    • S3
    • Textract
    • DynamoDB
    • API Gateway
    • CloudWatch
    • +1 more

    Highlights

    • Asynchronous Textract with DynamoDB-backed idempotent processing.
    • REST retrieval with API-key auth; latency and error signals in CloudWatch.

    +1 more in full resume

    DemoRepository

Academics

Education

Formal training that underpins software, systems, cloud, AI/ML, and DevOps work.

  • Master of Science in Computer Science

    DePaul University

    Chicago, IL, USA

    January 2025 – Present

  • Bachelor of Engineering in Computer Science

    Sri Krishna College of Engineering and Technology

    Coimbatore, Tamil Nadu, India

    July 2020 – May 2024

Stack

Technical skills

Organized by category to match my resume - everything listed below appears there; nothing is trimmed for effect.

  • Programming Languages

    • Java
    • Python
    • SQL
    • JavaScript

  • Frontend / UI

    • React
    • HTML5
    • CSS
    • Streamlit

  • Backend / Integration

    • REST APIs
    • FastAPI
    • OpenAPI
    • Uvicorn
    • Flask
    • Django
    • Spring Boot
    • Node.js
    • Data Integration
    • Real-Time Data Processing
    • JUnit
    • Maven

  • Cloud / DevOps

    • AWS (EC2, S3, RDS, Lambda, API Gateway, CloudWatch, AWS Batch, VPC, SageMaker, EKS)
    • Docker
    • Docker Compose
    • Kubernetes
    • Terraform
    • Git
    • GitHub Actions
    • CI/CD
    • Jenkins
    • Linux
    • MLflow
    • pytest

  • Platforms / Tools

    • Databricks
    • VS Code
    • PyCharm
    • Eclipse
    • IntelliJ IDEA
    • Jupyter Notebook
    • MySQL Workbench
    • Google Colab
    • YAML

  • Databases

    • PostgreSQL
    • MySQL
    • Oracle
    • MongoDB
    • SQL Server
    • DynamoDB

  • Software Engineering Principles

    • Data Structures and Algorithms
    • OOP
    • SDLC
    • Agile/Scrum
    • SOLID Principles
    • Design Patterns
    • Unit Testing
    • Integration Testing
    • Debugging
    • Production Support
    • Incident Investigation
    • API Security
    • Cloud Security Fundamentals
    • Reproducible ML
    • Ranking / Decision Support

  • AI / ML

    • Machine Learning
    • Deep Learning
    • Multimodal AI
    • Graph Neural Networks (GCN)
    • TensorFlow
    • PyTorch
    • scikit-learn
    • NumPy
    • Pandas
    • Feature Engineering
    • Model Evaluation
    • Experiment Tracking
    • Data Preprocessing

  • Biotech / Cheminformatics

    • RDKit
    • SMILES
    • Molecular Descriptors
    • Morgan Fingerprints
    • Drug Candidate Prioritization
    • Molecular Property Prediction

  • Visualization

    • Tableau
    • Power BI
    • Plotly
    • Matplotlib
    • Excel

Resume

Quick highlights & download

At-a-glance signals for recruiters; explore projects and experience above for depth.

Graduate study

M.S. in Computer Science

DePaul University · 2025–present · Chicago, IL

Internships

Two software engineering internships

Product development & support (GURU IT) · full-stack delivery (Gateway Software)

Build & ship

Cloud, backend, and applied ML projects

AWS serverless pipelines, APIs, SDK work, and multimodal ML platforms

Research

Simulation-driven, sustainability-aware systems

Carbon-aware multi-region inference routing — evaluation & decision frameworks

Full resume

Download a single PDF with consolidated experience, education, and skills—easy to share with recruiters and hiring managers.

Download Resume
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Reach out

Contact

I’m actively seeking internships and full-time opportunities in Software Engineering, SDE, Cloud/DevOps, Backend Development, and AI/ML roles. I’m especially interested in building scalable systems, cloud-native platforms, reliable backend services, automation pipelines, and applied machine learning solutions that create real-world impact.

If you’re hiring or want to discuss a project, reach me by email or the form—LinkedIn works too.

Send a message

Submitting opens your email app with a pre-filled message—no server storage. You can also email me directly at yogithramana@gmail.com.