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SHREYAN
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gupta
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SHREYAN
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GUPTA
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SHREYAN
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gupta
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SHREYAN
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GUPTA
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machine learning
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generative ai
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software engineering
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machine learning
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generative ai
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software engineering
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about
I
about
I
I’m Shreyan Gupta — an AI/ML Engineer and Backend Developer building intelligent systems that scale for over 2 years.
I’m pursuing a Bachelor of Science in Computer Science at Drexel University, where I focus on AI/ML and Data Science. Along the way, I’ve built multi-use AI models, engineered full-stack applications, and optimized large-scale data systems that support real-world users.
At my core, I love optimizing even the tiniest details, enjoy solving tough problems, and using technology to create experiences that matter.
education
II
education
II
education
II
Bachelor of Science in Computer Science
Drexel University, PA
2022 — 2026
Focused on Machine Learning with a specialization in Computer Vision, backend engineering, and scalable software systems. Built a strong foundation in algorithms, data structures, and systems design.
Bachelor of Science in Computer Science
Drexel University, PA
2022 — 2026
Focused on Machine Learning with a specialization in Computer Vision, backend engineering, and scalable software systems. Built a strong foundation in algorithms, data structures, and systems design.
Bachelor of Science in Computer Science
Drexel University, PA
2022 — 2026
Focused on Machine Learning with a specialization in Computer Vision, backend engineering, and scalable software systems. Built a strong foundation in algorithms, data structures, and systems design.
Minor in Data Science
Drexel University, PA
2022 — 2026
Developed skills in data analysis, statistical modeling, and machine learning. Applied data-driven methods to real-world problems.
Minor in Data Science
Drexel University, PA
2022 — 2026
Developed skills in data analysis, statistical modeling, and machine learning. Applied data-driven methods to real-world problems.
Minor in Data Science
Drexel University, PA
2022 — 2026
Developed skills in data analysis, statistical modeling, and machine learning. Applied data-driven methods to real-world problems.
Years of Experience
SuccessfulProjects
experience
III
experience
III
experience
III
Data Scientist
Exelon Corp.
Sept. 2024 — Mar. 2025
Engineered pipelines that delivered $6M annual savings ($30M over 5 years) for the SPCC program by automating document processing with Python and Azure Functions. Built preprocessing workflows for large, unstructured compliance docs and deployed production pipelines on Azure Blob Storage, secured with Key Vault and Managed Identity.
At ImageAI, designed distributed pipelines in PySpark on Azure Synapse Analytics to process 30M+ PII records with high throughput and security. Integrated SQL and data lake storage for scalable transformations, and optimized ETL jobs for downstream analytics and ML workflows.
At SIA, developed a document ingestion pipeline supporting multi-use RAG applications, capable of processing thousands of files in parallel at ~35ms per file. Leveraged Azure Cognitive Search and Blob Storage to enable fast, schema-aware retrieval across diverse enterprise datasets.
Data Scientist
Exelon Corp.
Sept. 2024 — Mar. 2025
Engineered pipelines that delivered $6M annual savings ($30M over 5 years) for the SPCC program by automating document processing with Python and Azure Functions. Built preprocessing workflows for large, unstructured compliance docs and deployed production pipelines on Azure Blob Storage, secured with Key Vault and Managed Identity.
At ImageAI, designed distributed pipelines in PySpark on Azure Synapse Analytics to process 30M+ PII records with high throughput and security. Integrated SQL and data lake storage for scalable transformations, and optimized ETL jobs for downstream analytics and ML workflows.
At SIA, developed a document ingestion pipeline supporting multi-use RAG applications, capable of processing thousands of files in parallel at ~35ms per file. Leveraged Azure Cognitive Search and Blob Storage to enable fast, schema-aware retrieval across diverse enterprise datasets.
Data Scientist
Exelon Corp.
Sept. 2024 — Mar. 2025
Engineered pipelines that delivered $6M annual savings ($30M over 5 years) for the SPCC program by automating document processing with Python and Azure Functions. Built preprocessing workflows for large, unstructured compliance docs and deployed production pipelines on Azure Blob Storage, secured with Key Vault and Managed Identity.
At ImageAI, designed distributed pipelines in PySpark on Azure Synapse Analytics to process 30M+ PII records with high throughput and security. Integrated SQL and data lake storage for scalable transformations, and optimized ETL jobs for downstream analytics and ML workflows.
At SIA, developed a document ingestion pipeline supporting multi-use RAG applications, capable of processing thousands of files in parallel at ~35ms per file. Leveraged Azure Cognitive Search and Blob Storage to enable fast, schema-aware retrieval across diverse enterprise datasets.