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AI Engineer with 1.5+ years in GANs, RAG, and MLOps.
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Full Stack Data Scientist and ML/AI Engineer with 1.5+ years at HashedIn by Deloitte and an M.Tech in CSE from IIT (BHU) Varanasi (CGPA: 9.09, graduating May 2026, available immediately). Experienced in building GAN-based super-resolution models, LLM-powered RAG pipelines, and full-stack applications using Django, FastAPI, and React. Seeking roles in Data Science, Generative AI, and ML Engineering.
Indian Institute of Technology (BHU) Varanasi
Master of Technology · Computer Science & Engineering
July 1, 2024 – May 1, 2026
Dr. A.P.J. Abdul Kalam Technical University, Lucknow
Bachelor of Technology · Computer Science & Engineering
July 1, 2018 – July 1, 2022
HashedIn by Deloitte
Software Engineer I
January 1, 2023 – July 1, 2024
Gurgaon, Haryana, India
HashedIn by Deloitte
SDE Intern
August 1, 2022 – January 1, 2023
India
Research Paper Question Answering System (RAG)
January 1, 2026 – March 1, 2026
• Built a Retrieval-Augmented Generation (RAG) system for semantic question answering across 20+ research papers using FAISS vector search and transformer-based embeddings. • Developed an automated document ingestion pipeline for PDF parsing, text chunking, embedding generation, and vector indexing using PyMuPDF and LangChain. • Generated context-aware and citation-grounded responses by retrieving the most relevant passages through semantic similarity search. • Optimized retrieval performance and inference latency using efficient FAISS indexing and 1,200+ embedding representations for multi-document querying.
PanSRGAN: Dual-Branch GAN for Pansharpening-Guided Multispectral Super-Resolution
July 1, 2025 – May 1, 2026
• Proposed PanSRGAN, a novel dual-branch GAN architecture for 4x super-resolution of multispectral satellite imagery using high-resolution panchromatic (PAN) guidance, enabling improved land-cover classification and urban mapping. • Designed PAN/MS Fusion Blocks (PMFBs) with spatial attention-guided residual injection to transfer structural details from PAN images into multispectral reconstruction. • Developed a composite loss framework combining L1, VGG-19 perceptual, Spectral Angle Mapper (SAM), and RaGAN adversarial losses to preserve both spatial and spectral fidelity. • Achieved +3.1 dB PSNR, +5-8% SSIM, SAM = 3.2°, +4.7% segmentation mIoU, and +4.4% classification accuracy on the Gaofen-2 GID-15 dataset; trained on NVIDIA A100 GPUs using the Param Shivay supercomputing facility.
Paper submitted & under review
IEEE Transactions on Geoscience and Remote Sensing
June 1, 2026 – Present
Spot Award
HashedIn by Deloitte
January 1, 2023 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from academic research in GANs for satellite imagery to personal RAG systems and professional full-stack applications, shows a broad interest and adaptability. Their involvement in mentoring and placement activities at IIT BHU indicates a collaborative and community-oriented mindset. The target role of 'Applied AI' aligns well with their demonstrated skills in building and deploying AI solutions, suggesting a strong cultural fit for a role that requires both research and practical application.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership and mentoring skills through their roles as a Teaching Assistant and Training and Placement Representative. Their experience in an Agile/Scrum environment, advocating for TDD and CI/CD, suggests a good operational fit for modern development teams. The Spot Award indicates a proactive and impactful contribution to project delivery.