Posts by Collection

portfolio

Fine-Tuning Llama 3.2–3B on IPCC Climate Reports

Finetuning, Pretraining, and building a RAG pipeline using a Llama3.2-3B model on IPCC Climate Reports in a distributed environment

AI as a Service – Containerized ML Pipeline on Kubernetes

Cloud-native ML pipeline with CNN training as a K8s batch job and scalable multi-replica FastAPI inference on GKE

Market Recovery Dynamics During the 2020 Crash

Large-scale data lake pipeline integrating stock, COVID, mobility, and macroeconomic data via HDFS, MapReduce, and Hive/Trino for crash/recovery analysis

MOT-TR: DETR Fine-Tuning for Moved-Object Detection

Robust, reproducible pipeline designed to fine-tune the DETR (DEtection TRansformer) model for the task of detecting moved objects in pairs of images taking from parking lots and intersections (VIRAT dataset).

Limit Order Book Midpoint prediction for Cryptocurrency Stocks

Evaluated classical ML model performance and designed light-weight neural networks with custom loss functions for SoTA limit order book midpoint prediction for a cryptocurrency stock

OS Simulation Suite

Compact suite of operating system simulations in modern C++ spanning - linking/loading, CPU scheduling, memory paging, and disk I/O scheduling

CoBaLI – Continuous Batching for LLM Inference

C++/CUDA inference engine achieving 6.2× throughput via GPU-assisted scheduling on top of llama.cpp, without modifying model kernels

EcoScan – Sustainable Fashion Scanner

1st Place HackNYU 2025 (MLH) — Mobile app that scans clothing items and returns Eco-Scores with AI-powered greener alternatives

RepoRecSys – GitHub Repository Recommendation System

Two-tower neural recommender with cold-start handling, hot model reloading, and containerized FastAPI inference (<100ms latency)

VisaPulse – AI-Powered F-1 Visa Mock Interview Platform

LangGraph-orchestrated agentic interview system with voice interaction, document analysis, RAG over Reddit cases, and personalized PDF evaluations

Handwritten Character Classification Pipeline

ResNet50V2-based EMNIST classifier achieving 93.55% test accuracy with mixed precision and optimized data pipeline

publications

Context-Aware Behavioral Fingerprinting in IoT Devices

Published in 20th International Conference on Security and Cryptography, SECRYPT 2023, 2023

We propose a context-aware behavioral fingerprinting of IoT devices that takes into account the circumstances or contexts under which the devices are operating. Our fingerprinting strategy uses supervised learning for classifying the IoT devices.Finally, Experimental results show that our fingerprinting technique is quite effective and is capable of identifying IoT devices with more than 94% accuracy.

Recommended citation: Prasad, A.; Biju, K.; Somani, S. and Mitra, B. (2023). Context-Aware Behavioral Fingerprinting of IoT Devices via Network Traffic Analysis. 20th International Conference on Security and Cryptography, SECRYPT 2023.
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Auto-Markup BenchMark: towards an industry-standard benchmark for evaluating automatic document markup

Published in Balisage: The Markup Conference 2023 — Balisage Series on Markup Technologies, Vol. 28, 2023

We introduce an early benchmark (Auto-Markup BenchMark) for evaluating automatic markup engines and propose XATER (XML Translation Edit Rate) alongside a validation-error metric to standardize comparisons across tools and tasks.

Recommended citation: Prescod, P.; Feuer, B.; Hladkyi, A.; Paulk, S.; Prasad, A. (2023). Auto-Markup BenchMark: towards an industry-standard benchmark for evaluating automatic document markup. Proceedings of Balisage: The Markup Conference 2023, Balisage Series on Markup Technologies, Vol. 28.
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research_experience

Graduate Researcher – Search and Ranking

Architected multi-stage RAG pipelines and embedding infrastructure for 5.7M+ documents; reduced retrieval latency from 380ms to 130ms.

Research Project

Built a metric-extraction + ML pipeline to flag bug-prone Java files with >91% accuracy; informed Agile policy updates to reduce post-release defects.