trec-eval

Search engine experimentation on the TREC collections. Currently focused on zero-shot reranking implementations with typesafe.ai's JEV model

imi_mug support code and resources from our participation at the TREC 2017 Precision Medicine Track

Validate TREC qrels and runs in CI; explore a MiniLM browser lab and FAISS + DeBERTa product-search pipeline.

Advanced IR Experiments with SBERT, Elasticsearch and trec_eval

Trec Evaluation of ranked documents retrieved by searching on ElasticSearch Index

Information Retrieval pipeline leveraging TFIDF and BM25 to evaluate ranking accuracy over MSMARCO Passage dataset

Recommendation-oriented version of trec_eval with more metrics

Support code and resources for participation at the TREC Precision Medicine Track (TREC-PM)

The goal of this project is to implement various IR models, evaluate the IR system and improve the search result based on our understanding of the models, the implementation and the evaluation.

The projects are a part of the course CSE-535: Information Retrieval, that I had taken up for Fall 2022 at the University at Buffalo.

Information Retrieval Kit - Utilities for IR in python

Cranfield collection in TREC XML format.

imi_mug support code and resources from our participation at the TREC 2017 Precision Medicine Track

Microblog information retrieval system. Implementing an Information Retrieval (IR) system based on a collection of documents (X messages).

Search engine that queries for information to find the best results based on custom analysers and indexing techniques.

A multi-phase Information Retrieval system built for IR2025, exploring query expansion techniques using BM25, WordNet, and Word2Vec. Includes full evaluation using TREC metrics (MAP, avgPre@k) and implemented in Python with Elasticsearch, Gensim, and NLTK.

Information Retrieval course assignments (HW1–HW8): classic retrieval models, indexing, evaluation, link analysis, and ML; includes a runnable Cranfield end‑to‑end pipeline with reported metrics.

The projects are a part of the course CSE-535: Information Retrieval, that I had taken up for Fall 2019 at the University at Buffalo.