diff --git a/README.md b/README.md
index 3db36a72..9bce7ce2 100644
--- a/README.md
+++ b/README.md
@@ -1,12 +1,12 @@
-# 🚀 Portfolio Site v1.0.2
+# 🚀 Portfolio Site v1.1.0
### A Modern, Dark-Themed Developer Portfolio
*Built with Astro • Powered by Cloudflare Workers • Deployed on GitHub Pages*
-[](https://github.com/manideepsp/Portfolio-ManideepSP/releases/tag/v1.0.2)
+[](https://github.com/manideepsp/Portfolio-ManideepSP/releases/tag/v1.1.0)
[](https://manideepsp.github.io/Portfolio-ManideepSP)
[](https://astro.build)
[](LICENSE)
diff --git a/node_modules/.vite/deps/_metadata.json b/node_modules/.vite/deps/_metadata.json
index 16a292b5..28151241 100644
--- a/node_modules/.vite/deps/_metadata.json
+++ b/node_modules/.vite/deps/_metadata.json
@@ -1,25 +1,25 @@
{
- "hash": "f7833d27",
- "configHash": "1bb4ccb4",
+ "hash": "20628c1c",
+ "configHash": "9e04a1d3",
"lockfileHash": "9743054d",
- "browserHash": "3046dbe6",
+ "browserHash": "990c6b41",
"optimized": {
"astro > cssesc": {
"src": "../../cssesc/cssesc.js",
"file": "astro___cssesc.js",
- "fileHash": "fa48bec0",
+ "fileHash": "d7ac9c46",
"needsInterop": true
},
"astro > aria-query": {
"src": "../../aria-query/lib/index.js",
"file": "astro___aria-query.js",
- "fileHash": "a0fd7d72",
+ "fileHash": "517d09fd",
"needsInterop": true
},
"astro > axobject-query": {
"src": "../../axobject-query/lib/index.js",
"file": "astro___axobject-query.js",
- "fileHash": "ff732b82",
+ "fileHash": "dbd25c4f",
"needsInterop": true
}
},
diff --git a/package.json b/package.json
index 36e4259e..b305effd 100644
--- a/package.json
+++ b/package.json
@@ -1,6 +1,6 @@
{
"name": "portfolio-site",
- "version": "1.0.2",
+ "version": "1.1.0",
"type": "module",
"description": "A dark modern portfolio website showcasing projects and skills.",
"main": "index.js",
diff --git a/public/images/projects/AiRes-AiResumeScreener-Architecture-Diagram.svg b/public/images/projects/AiRes-AiResumeScreener-Architecture-Diagram.svg
new file mode 100644
index 00000000..95194f5a
--- /dev/null
+++ b/public/images/projects/AiRes-AiResumeScreener-Architecture-Diagram.svg
@@ -0,0 +1,4 @@
+
+
+
\ No newline at end of file
diff --git a/public/images/projects/Diabetes-Risk-Predection-Architecture-Diagram.svg b/public/images/projects/Diabetes-Risk-Predection-Architecture-Diagram.svg
new file mode 100644
index 00000000..53f59d32
--- /dev/null
+++ b/public/images/projects/Diabetes-Risk-Predection-Architecture-Diagram.svg
@@ -0,0 +1,4 @@
+
+
+
\ No newline at end of file
diff --git a/public/images/projects/dataflow-engine.svg b/public/images/projects/dataflow-engine.svg
deleted file mode 100644
index e1cbe539..00000000
--- a/public/images/projects/dataflow-engine.svg
+++ /dev/null
@@ -1,83 +0,0 @@
-
diff --git a/public/images/projects/ml-dashboard.svg b/public/images/projects/ml-dashboard.svg
deleted file mode 100644
index 5016e182..00000000
--- a/public/images/projects/ml-dashboard.svg
+++ /dev/null
@@ -1,67 +0,0 @@
-
diff --git a/scripts/validate-projects.js b/scripts/validate-projects.js
index 1971771f..fc02ddc8 100644
--- a/scripts/validate-projects.js
+++ b/scripts/validate-projects.js
@@ -11,7 +11,7 @@ import { fileURLToPath } from 'url';
const __filename = fileURLToPath(import.meta.url);
const __dirname = path.dirname(__filename);
-const configPath = path.join(__dirname, '../src/lib/config.json');
+const configPath = path.join(__dirname, '../src/lib/config/projects.config.json');
const publicDir = path.join(__dirname, '../public');
async function validateImages(projects) {
@@ -129,7 +129,7 @@ async function main() {
process.exit(1);
}
- console.log(`\nFound ${projects.length} project(s) in config.json\n`);
+ console.log(`\nFound ${projects.length} project(s) in projects.config.json\n`);
// Run validations
const imageResults = await validateImages(projects);
diff --git a/src/lib/config.json b/src/lib/config.json
index 29b7a940..d0f61e6b 100644
--- a/src/lib/config.json
+++ b/src/lib/config.json
@@ -14,7 +14,6 @@
"email": "manideepsp.16@gmail.com"
},
-
"resume": {
"displayLink": "/resumes/Default Applied ML-AI Engineer Resume.pdf",
"downloadFilename": "Default Applied ML-AI Engineer Resume.pdf"
@@ -28,165 +27,7 @@
{ "label": "Contact", "href": "/contact" }
],
- "about": {
- "markdownFile": "/content/about.md",
- "profile": {
- "name": "Manideep Sriperambudhuru",
- "title": "Applied AI / ML Engineer",
- "location": "Hyderabad, India",
- "email": "manideepsp.16@gmail.com",
- "phone": "+91 6300-519-475",
- "linkedin": "https://www.linkedin.com/in/manideepsp",
- "portfolio": "https://manideepsp.github.io/Portfolio-ManideepSP"
- },
- "summary": "Applied AI / ML Engineer with nearly three years of experience spanning data engineering, applied machine learning, and GenAI systems. Strong background in building reliable data pipelines and analytics foundations, followed by hands-on ownership of ML- and LLM-driven systems including RAG pipelines, agentic chatbots, and hyper-personalized learning workflows.\n\nExperienced in taking internal proof-of-concepts from data ingestion and modeling through experimentation, optimization, deployment, and platform integration. My work focuses on building AI systems that are measurable, scalable, and grounded in real product constraints such as latency, cost, and reliability.",
- "skills": {
- "Programming & Core Languages": ["Python (ML pipelines, data processing, LLM workflows)", "SQL (complex queries, joins, aggregations, stored procedures)", "Basic JavaScript (frontend integration for internal tools)"],
- "Data Engineering & Analytics": ["ETL pipeline design and orchestration", "Medallion Architecture (Bronze / Silver / Gold layers)", "Data modeling for analytics and ML workloads", "Azure Data Factory (ADF)", "Databricks and PySpark", "SQL Server and Snowflake", "Azure Storage (Blob Storage, Data Lake Gen2)", "AWS S3", "Data quality checks, validation, and logging", "Power BI dashboards and internal analytics"],
- "Machine Learning": ["Classical ML algorithms (linear regression, logistic regression, clustering)", "Feature engineering from structured and unstructured data", "Model training, evaluation, and experimentation", "Cross-validation, metric selection, and tradeoff analysis", "Handling noisy real-world data and class imbalance", "Clustering evaluation (Elbow method, Kneedle algorithm, Silhouette analysis)", "Model checkpointing and best-model selection"],
- "Neural Networks & Deep Learning": ["Feedforward neural networks", "Convolutional Neural Networks (CNN)", "Recurrent Neural Networks (RNN, LSTM)", "Temporal sequence modeling", "Reinforcement learning concepts (A3C)"],
- "NLP, Embeddings & Retrieval": ["BERT-family transformer models", "Text embeddings and vectorization techniques", "Cosine similarity–based retrieval", "Dense retrieval pipelines", "ColBERT-style late interaction models", "Reranking strategies for improved relevance"],
- "GenAI / LLM Systems": ["Retrieval-Augmented Generation (RAG)", "Prompt design, refinement, and token reduction", "Prompt evaluation using cosine similarity and BLEU score", "LLM latency and cost optimization", "Relevance, groundedness, and faithfulness checks", "RAGAS-style evaluation workflows", "LangChain, LangGraph, and LangSmith", "Agentic AI systems with stateful, multi-step reasoning"],
- "Backend, Architecture & Performance": ["Flask-based backend services and REST APIs", "Two-tier application architecture", "API-based integration of ML and LLM systems", "Docker-based containerization", "Multi-threading and parallel processing", "Concurrent execution for LLM workloads", "Latency bottleneck identification and optimization"]
- },
- "coreCompetencies": {
- "Data Engineering & Analytics Foundations": ["ETL pipeline design and orchestration", "Medallion Architecture (Bronze / Silver / Gold layers)", "Data modeling for analytics and ML workloads", "SQL query optimization and stored procedures", "Data quality checks, logging, and error handling", "BI reporting and stakeholder-facing analytics"],
- "Machine Learning": ["Classical ML (regression, clustering)", "Feature engineering from structured and unstructured data", "Model evaluation and experimentation", "Cross-validation, metric selection, and tradeoff analysis", "Handling temporal and sequential data patterns"],
- "GenAI / LLM Systems": ["Retrieval-Augmented Generation (RAG)", "Prompt design, optimization, and token reduction", "LLM latency and cost optimization", "Relevance and faithfulness evaluation (RAGAS-style)", "BLEU and similarity-based evaluation techniques", "Agentic conversational systems (LangGraph)"],
- "Engineering & Platform": ["Python and SQL", "REST-based service integration", "Azure ecosystem (ADF, Databricks, Storage, Managed Identities)", "Docker-based containerization", "Internal CI/CD exposure and deployment workflows"]
- },
- "projects": [
- {
- "title": "Mental Health Relapse Prediction System",
- "domain": "Healthcare / Mental Health",
- "goal": "Estimate relapse risk and surface contextual clinical guidance",
- "highlights": ["Built an ML pipeline using PHQ-9, DSM-5, patient journals, and clinician notes", "Performed sentiment, frequency, and contextual feature extraction", "Modeled relapse risk as a continuous score", "Evaluated multiple approaches using cross-validated metrics", "Selected LSTM-based models for temporal pattern learning", "Added a RAG-based intervention layer aligned with medical best practices", "Deployed using Flask + React with Docker and real-time DB sync"]
- },
- {
- "title": "Diabetes Risk Prediction & Monitoring System",
- "domain": "Preventive Healthcare",
- "goal": "Predict diabetes risk and provide contextual interventions",
- "highlights": ["Developed a questionnaire-driven chatbot to collect KPIs", "Triggered ML-based risk prediction models", "Implemented scheduled retraining with checkpointing and best-model selection", "Built a two-tier Flask architecture with containerized deployment", "Integrated RAG-based health interventions", "Deployed as an internal application"]
- },
- {
- "title": "LLM-Based Resume Screening System",
- "domain": "HR / Talent Screening",
- "goal": "Automate resume shortlisting",
- "highlights": ["Built a resume screening system using vector databases and RAG", "Indexed resumes and job descriptions for semantic retrieval", "Designed similarity-based scoring for candidate ranking", "Reduced manual screening effort and improved consistency"]
- }
- ],
- "education": {
- "institution": "CMR Institute of Technology — Hyderabad, India",
- "degree": "Bachelor of Technology (Mechanical Engineering)",
- "years": "2019 – 2023",
- "gpa": "8.46 / 10.0"
- },
- "certifications": [
- "Databricks Generative AI Fundamentals (Valid until August 2026)",
- "Star of the Quarter, Cognine Technologies"
- ]
- },
- "experience": [
- {
- "title": "Data Quality Platform",
- "company": "Acme Corp",
- "companyLink": "https://cognine.com/",
- "date": "2024-01",
- "description": "Built ML-driven data quality scoring platform reducing incident noise by 35%",
- "skills": ["Python", "TypeScript", "React", "AWS", "Airflow"]
- },
- {
- "title": "Data Platform Migration",
- "company": "Acme Corp",
- "companyLink": "https://cognine.com/",
- "date": "2023-06",
- "description": "Led migration from monolith ETL to modular Spark jobs with CI/CD",
- "skills": ["Spark", "Kafka", "Terraform", "AWS"]
- },
- {
- "title": "Realtime Analytics",
- "company": "Nimbus Labs",
- "date": "2023-01",
- "description": "Delivered realtime metrics pipeline (Kafka/Flink) for product analytics",
- "skills": ["Java", "Kafka", "Flink", "ClickHouse", "Grafana"]
- },
- {
- "title": "Observability Platform",
- "company": "Nimbus Labs",
- "date": "2022-04",
- "description": "Implemented service-level metrics and alerting to reduce MTTI by 40%",
- "skills": ["Prometheus", "Grafana", "OpenTelemetry", "Go"]
- },
- {
- "title": "Growth Experiments",
- "company": "Tech Startup",
- "date": "2022-01",
- "description": "Shipped experiment platform and feature flags, boosting activation by 12%",
- "skills": ["JavaScript", "Node.js", "PostgreSQL", "Docker", "Redis"]
- },
- {
- "title": "A/B Infrastructure",
- "company": "Tech Startup",
- "date": "2021-03",
- "description": "Built lightweight A/B evaluation service and SDK for client apps",
- "skills": ["Go", "Redis", "Postgres", "Kubernetes"]
- },
- {
- "title": "Design System",
- "company": "Digital Agency",
- "date": "2020-01",
- "description": "Rolled out design system and tooling across 6 client web properties",
- "skills": ["React", "CSS", "Storybook", "Git"]
- },
- {
- "title": "Web Revamp",
- "company": "Web Studio",
- "date": "2018-01",
- "description": "Rebuilt marketing sites with performance and a11y focus",
- "skills": ["HTML", "CSS", "JavaScript"]
- }
- ],
-
- "projects": [
- {
- "title": "PHQ-9 DSM-5 Based Mental Health Predictor",
- "description": "A machine learning pipeline for real-time data processing and anomaly detection.",
- "image": "/images/projects/PHQ-9-Predictor-Architecture-Diagram.svg",
- "repoUrl": "https://github.com/manideepsp/PHQ-9",
- "is_demo_available": false,
- "demoUrl": "https://www.google.com",
- "slug": "phq-9-dsm-5-based-mental-health-predictor",
- "readmeUrl": "https://raw.githubusercontent.com/manideepsp/PHQ-9/main/README.md",
- "tags": ["ML", "Streaming", "Healthcare", "Python"]
- },
- {
- "title": "DataFlow Engine",
- "description": "High-performance ETL framework built with Python and Apache Spark.",
- "image": "/images/projects/dataflow-engine.svg",
- "repoUrl": "https://github.com/manideepsp/dataflow-engine",
- "is_demo_available": false,
- "demoUrl": "",
- "slug": "dataflow-engine",
- "readmeUrl": "https://raw.githubusercontent.com/manideepsp/dataflow-engine/main/README.md",
- "tags": ["ETL", "Spark", "Python", "Data Engineering"]
- },
- {
- "title": "ML Dashboard",
- "description": "Interactive dashboard for monitoring ML model performance and drift detection.",
- "image": "/images/projects/ml-dashboard.svg",
- "repoUrl": "https://github.com/manideepsp/ml-dashboard",
- "is_demo_available": false,
- "demoUrl": "",
- "slug": "ml-dashboard",
- "readmeUrl": "https://raw.githubusercontent.com/manideepsp/ml-dashboard/main/README.md",
- "tags": ["Dashboard", "ML Ops", "Visualization", "React"]
- }
- ],
-
- "experienceSettings": {
- "showMonth": true,
- "dateFormat": "short"
- },
+ "customDomain": "",
"contactWorkerUrl": "https://portfolio-manideepsp.manideepsp-16.workers.dev/",
"contactFallback": {
diff --git a/src/lib/config/about.config.json b/src/lib/config/about.config.json
index 8252a08e..0badf6f0 100644
--- a/src/lib/config/about.config.json
+++ b/src/lib/config/about.config.json
@@ -154,19 +154,19 @@
"gpa": "8.46 / 10.0"
},
"certifications": [
- {
- "title": "Databricks Generative AI Fundamentals",
- "organisation": "Databricks",
- "date": "August 2024",
- "linkPresent": true,
- "link": "https://credentials.databricks.com/7b9dfa6f-3ee5-4eef-9d6a-a1633ac7d902#acc.R9Tf1YCV"
- },
{
"title": "Star of the Quarter",
"organisation": "Cognine Technologies",
"date": "March 2025",
"linkPresent": false,
"link": ""
- }
+ },
+ {
+ "title": "Databricks Generative AI Fundamentals",
+ "organisation": "Databricks",
+ "date": "August 2024",
+ "linkPresent": true,
+ "link": "https://credentials.databricks.com/7b9dfa6f-3ee5-4eef-9d6a-a1633ac7d902#acc.R9Tf1YCV"
+ }
]
}
diff --git a/src/lib/config/projects.config.json b/src/lib/config/projects.config.json
index e63653eb..f0bb495a 100644
--- a/src/lib/config/projects.config.json
+++ b/src/lib/config/projects.config.json
@@ -9,29 +9,30 @@
"demoUrl": "https://www.google.com",
"slug": "phq-9-dsm-5-based-mental-health-predictor",
"readmeUrl": "https://raw.githubusercontent.com/manideepsp/PHQ-9/main/README.md",
- "tags": ["ML", "Streaming", "Healthcare", "Python"]
+ "tags": ["mental-health","depression-screening","ml-pipeline","phq9","healthcare-ai","lstm-prediction","flask-api","rag-llm","vector db", "Medical Interventions"]
},
{
- "title": "DataFlow Engine",
- "description": "High-performance ETL framework built with Python and Apache Spark.",
- "image": "/images/projects/dataflow-engine.svg",
- "repoUrl": "https://github.com/manideepsp/dataflow-engine",
+ "title": "Diabetes Risk Prediction Chatbot",
+ "description": "An intelligent chatbot that predicts diabetes risk based on user inputs and provides health interventions.",
+ "image": "/images/projects/Diabetes-Risk-Predection-Architecture-Diagram.svg",
+ "repoUrl": "https://github.com/manideepsp/Diabeters-risk-score.git",
"is_demo_available": false,
- "demoUrl": "",
- "slug": "dataflow-engine",
- "readmeUrl": "https://raw.githubusercontent.com/manideepsp/dataflow-engine/main/README.md",
- "tags": ["ETL", "Spark", "Python", "Data Engineering"]
+ "demoUrl": "diabetes-risk-prediction-chatbot",
+ "slug": "diabetes-risk-prediction-chatbot",
+ "readmeUrl": "https://raw.githubusercontent.com/manideepsp/Diabeters-risk-score/main/README.md",
+ "tags": ["healthcare-ai", "medical-chatbot", "flask","langgraph", "ollama", "qdrant", "machine-learning", "risk-prediction", "vector-database", "postgresql", "python",
+"ai-screening", "Interventions"]
},
{
- "title": "ML Dashboard",
- "description": "Interactive dashboard for monitoring ML model performance and drift detection.",
- "image": "/images/projects/ml-dashboard.svg",
- "repoUrl": "https://github.com/manideepsp/ml-dashboard",
+ "title": "AIRES: AI Resume Screening System",
+ "description": "Aires is an intelligent resume screening application that leverages OpenAI's GPT models to automate candidate evaluation and shortlisting.",
+ "image": "/images/projects/AiRes-AiResumeScreener-Architecture-Diagram.svg",
+ "repoUrl": "https://github.com/manideepsp/Aires.git",
"is_demo_available": false,
"demoUrl": "",
- "slug": "ml-dashboard",
- "readmeUrl": "https://raw.githubusercontent.com/manideepsp/ml-dashboard/main/README.md",
- "tags": ["Dashboard", "ML Ops", "Visualization", "React"]
+ "slug": "aires-ai-resume-screening-system",
+ "readmeUrl": "https://raw.githubusercontent.com/manideepsp/Aires/main/README.md",
+ "tags": ["AI Resume Screening","Python","OpenAI GPT-3.5","Chainlit","Document Processing","HR Automation"]
}
]
}
diff --git a/src/pages/projects/[slug].astro b/src/pages/projects/[slug].astro
index 801cd519..65eabfdc 100644
--- a/src/pages/projects/[slug].astro
+++ b/src/pages/projects/[slug].astro
@@ -1,6 +1,6 @@
---
import BaseLayout from '../../layouts/BaseLayout.astro';
-import config from '../../lib/config.json';
+import config from '../../lib/config.js';
import { renderMarkdown } from '../../lib/markdown.js';
import { fetchReadme } from '../../lib/readmeFetcher.js';
import { slugify } from '../../lib/slugify.js';