AI/ML Engineer
Computer Vision ✦ LLM Systems ✦ Edge AI
I'm an AI/ML Engineer building and operating production AI systems across computer vision, retrieval, and applied machine learning. At The Data Island, I work on Unilever Bangladesh's retail intelligence platform, where our computer vision pipeline processes 1.5M+ field images each month across 600+ SKUs. My work spans production ML pipeline operations, model training, fine-tuning and deployment, and evolving our systems toward more scalable service-oriented architectures.
Beyond production engineering, I contribute to open-source machine learning projects that align with my areas of expertise and conduct academic research in deep learning and edge AI.
BS in Computer Science and Engineering
January 2022 - December 2025
Major: Artificial Intelligence
Higher Secondary Certificate (HSC)
2018 - 2020
Group: Science
Built a self-hosted annotation platform for dense retail shelves that pre-labels products with a detector, suggests SKUs by embedding search and exports signed-off dataset versions with leak-free train/test splits.
Built a RAG system combining speculative query planning, hybrid retrieval, reranking and evidence-grounded synthesis with provenance tracking for reliable answers.
Built an on-device Android app for real-time pose and hand tracking to analyze form, count reps and provide posture feedback. Added gesture-based controls and per-user calibration with robust rep quality scoring.
Built a production-ready multi-tenant workspace management REST API with passwordless auth, role-based access control and real-time email invitations, deployed live on Railway.
Additional Projects
Built and deployed a full-stack AI-assisted deliberation platform that transforms multi-participant positions into grounded steelmans, shared foundations, and clearly classified disagreements. Implemented secure authentication, moderation, privacy-aware exports, and email notifications.
Built and designed an AI-powered research workspace that turns long-form audio and video sources into timestamped transcripts, searchable evidence and citation-backed answers.
Built an end-to-end fraud detection pipeline with offline training, stream-style scoring, analyst feedback ingestion, online model updates and Prometheus/Grafana observability for latency, anomaly flow and update health.
Built a security-focused Python CLI for encrypted file vaults with outer and hidden-volume workflows, including authenticated encryption, passphrase-based key derivation, integrity verification and streaming file handling.
Built a full-stack AI-powered repository intelligence platform that analyzes GitHub codebases and delivers architecture dashboards plus retrieval-augmented chat over indexed code.
Built a full-stack decision intelligence platform for capturing time-locked decisions, tracking outcomes and surfacing reasoning patterns through AI-powered analysis.
Built a full-stack civic-issue reporting platform with map-based reporting, community verification and a role-gated admin workflow that tracks each report from submission to resolution.
Built a production-style research automation platform with multi-node planning, evidence gathering, analysis and citation-aware report generation with live progress tracking.
Built a browser-based P2P watch-party streaming app with WebTorrent/WebRTC that supports room signaling, synchronized playback, chat, reconnect recovery, tracker failover, subtitle upload (.vtt/.srt) and validation reporting.
Built a userspace copy-on-write filesystem with FUSE that versions every write, supports snapshots/restore/GC/diff and ships with tested CI/CD and automated PyPI releases.
Built a Rust-based explainable backup and restore tool with deduplicated snapshots, a guided terminal UI, integrity checks, restore rehearsal, storage analysis and filesystem remote sync.
Built a full-stack platform that turns any OpenAPI specification into a tested, ready-to-ship TypeScript MCP server, using deterministic code generation with a human approval gate, isolated Docker-sandbox testing, and an LLM-powered self-repair loop.
Built and deployed a secure computer-vision dataset auditing platform for YOLO and COCO, with asynchronous cloud audits, integrity and leakage detection, actionable reports, and automated CI/CD on AWS.
Built an end-to-end predictive maintenance platform with validation-gated ensemble selection, production inference APIs and a dashboard for model decisions and live checks.
Built a serverless AI invoice processing platform with direct uploads, structured extraction, validation, human review and monitoring.
Built a distributed file service with resumable chunk uploads, HTTP range downloads, checksum validation and reliable state transitions with auth and audit logging.
Built a high-performance real-time log aggregation CLI with multi-source tailing, structured parsing, resilient rotation handling and a live WebSocket dashboard for throughput, severity trends and health metrics.
Built a Python CLI that parses dependencies across 7 ecosystems (npm, pip, Go, Rust, Ruby, Maven, YAML) and builds directed graphs from scratch. Detects cycles, ranks critical packages via PageRank, computes blast-radius impact, and runs offline security (OSV) and license (SPDX) audits, all visualized in an interactive D3.js dashboard.
Built an offline-first AI note-taking app in Flutter with rich-text editing, local persistence and on-device summarization using an ONNX-based runtime pipeline.
Built an offline Android app in Flutter to track habit streaks with a panic mode, relapse insights, milestone notifications and a native Kotlin home-screen widget.
Built a VS Code extension that displays inline cyclomatic complexity via CodeLens with a sortable sidebar report and JSON/CSV export across JavaScript, TypeScript, Python, Java and C# codebases.
Built a research framework for comparing FedAvg, client-level DP-FedAvg and sample-level DP-SGD across synthetic, MNIST and CIFAR-10 datasets. The project includes configurable federated simulations, RDP privacy accounting, IID/non-IID partitioning, experiment sweeps, report generation and a dashboard for privacy-utility analysis.
Built a research framework for joint probabilistic forecasting and anomaly detection on multivariate time series. The project implements MDN-LSTM and regime-aware joint models, full SMD benchmark evaluation, calibrated thresholding, persistence-based false-alarm reduction, CRPS/Energy Score metrics and reproducible experiment reporting with tested pipelines.
Designed and implemented a blockchain protocol for carrying privacy-preserving AI model attestations across chains, combining zero-knowledge verification, permissioned-to-public relay flows and automated end-to-end orchestration.
Enabled strict mypy type checking across core modules and fixed a model-context bug that reinitialized the detection head against cleared weights, in this real-time detection transformer library.
Added pose error metrics and AUC scoring to kornia.metrics, carrying a stalled contributor branch to completion and fixing silent-broadcast, threshold-truncation and NaN-propagation defects that produced out-of-range AUC values, in this differentiable computer vision library.
Extended mypy checking from the library into the test suite across component directories, fixing list-invariance and protocol-narrowing failures, in this LLM orchestration framework.
Fixed the Amazon provider's GCSToS3Operator so match_glob filtering is validated after Jinja template rendering.
IEEE 4th International Conference on Artificial Intelligence, Blockchain and Internet of Things, 2026.
ACM Transactions on Intelligent Systems and Technology, 2026.
Link2nd IEEE Conference on Secure and Trustworthy Cyberinfrastructure for IoT and Microelectronics (SaTC), 2026.
Link5th International Conference on Sentiment Analysis and Deep Learning (ICSADL), 2026.
LinkChainAttest: Cross-Chain Verification of Privacy-Preserving ML Attestations from Permissioned to Public Blockchains
HAMP: Hardware-Aware Mixed-Precision Quantization via Sensitivity-Guided Evolutionary Search
Artificial Dexterity: A Unified Survey of Robotic Hand Architectures, Multimodal Perception and Embodied AI