Rohan Mackin Jha

Rohan Jha

rjha5[at]cs.jhu.edu
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I'm a first-year PhD student at the Center for Language and Speech Processing at Johns Hopkins University, advised by Benjamin Van Durme and Reno Kriz.

I study neural information retrieval models and the systems in which they are integrated. I aim to design retrieval systems that efficiently address complex information needs.

This summer, I'll be interning at Mixedbread AI as a Research Scientist.

Previously, I graduated from UT Austin with an M.S. in Computer Science and from Carnegie Mellon University with a B.S. in Artificial Intelligence, where I did retrieval research with Jamie Callan. I also interned at Jina AI, mentored by Bo Wang, to train their multilingual, multi-vector ColBERT retrieval model.

Publications

A Brief Comparison of Training-Free Multi-Vector Sequence Compression Methods
Rohan Jha , Chunsheng Zuo , Reno Kriz , Benjamin Van Durme
1st Late Interaction Workshop @ ECIR 2026 | paper
Multi-Vector Index Compression in Any Modality
Hanxiang Qin , Alexander Martin , Rohan Jha , Chunsheng Zuo , Reno Kriz , Benjamin Van Durme
arXiv 2026 | paper | code
semantic-features: A User-Friendly Tool for Studying Contextual Word Embeddings in Interpretable Semantic Spaces
Jwalanthi Ranganathan , Rohan Jha , Kanishka Misra , Kyle Mahowald
SCiL 2025 | paper | code
Jina-ColBERT-v2: A General-Purpose Multilingual Late Interaction Retriever
Rohan Jha , Bo Wang , Michael Günther , Georgios Mastrapas , Saba Sturua , Isabelle Mohr , Andreas Koukounas , Mohammad Kalim Akram , Nan Wang , Han Xiao
MRL 2024 | paper | code
Generalizable Tip-of-the-Tongue Retrieval with LLM Re-ranking
Luís Borges , Rohan Jha , Jamie Callan , Bruno Martins
SIGIR 2024 | paper | code
COILcr: Efficient Semantic Matching in Contextualized Exact Match Retrieval
Zhen Fan , Luyu Gao , Rohan Jha , Jamie Callan
ECIR 2023 | paper