I am currently a research scientist at ThirdAI. Previously, I was an applied scientist on the Amazon product search team, working on research challenges in information retrieval and building scalable machine learning pipelines. Before that, I studied computational mathematics at Stanford University.

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Preprints

Down with the Hierarchy: The 'H' in HNSW Stands for "Hubs"
Blaise Munyampirwa, Vihan Lakshman, Benjamin Coleman
Preprint | Code

CARAMEL: A Scalable Index for Succinct Multi-Set Retrieval
David Torres Ramos, Benjamin Coleman, Vihan Lakshman, Chen Luo, Anshumali Shrivastava
Preprint | Code

Publications

On the Diminishing Returns of Width for Continual Learning
Etash Guha, Vihan Lakshman
ICML 2024
Paper | Code

CAPS: A Practical Partition Index for Filtered Similarity Search
Gaurav Gupta, Jonah Yi, Benjamin Coleman, Vihan Lakshman, Chen Luo, Anshumali Shrivastava
International Workshop on Interactive and Scalable Information Retrieval Methods for eCommerce, WSDM 2024
Paper | Code

DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries.
Joshua Engels, Benjamin Coleman, Vihan Lakshman, Anshumali Shrivastava
NeurIPS 2023
Paper | Code

BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendations Models on Commodity CPU Hardware
Nicholas Meisburger, Vihan Lakshman, Benito Geordie, Joshua Engels, David Torres Ramos, Pratik Pranav, Benjamin Coleman, Benjamin Meisburger, Shubh Gupta, Yashwanth Adunukota, Tharun Medini, Anshumali Shrivastava
CIKM 2023
Paper | Code

From Research to Production: Towards Scalable and Sustainable Neural Recommendation Models on Commodity CPU Hardware
Anshumali Shrivastava, Vihan Lakshman, Tharun Medini, Nicholas Meisburger, Joshua Engels, David Torres Ramos, Benito Geordie, Pratik Pranav, Shubh Gupta, Yashwanth Adunukota, Siddharth Jain
RecSys (Industry Extended Abstract) 2023
Paper | Code

Massive Text Normalization via an Efficient Randomized Algorithm
Nan Jiang, Chen Luo, Vihan Lakshman, Yesh Dattatreya, Yexiang Xue
WWW 2022
Paper | Code

ROSE: Robust Caches for Amazon Product Search
Chen Luo, Vihan Lakshman, Anshumali Shrivastava, Tianyu Cao, Sreyashi Nag, Rahul Goutam, Hanqing Lu, Yiwei Song, Bing Yin
WWW (Industry Track) 2022
Paper

Embracing Structure in Data for Billion-Scale Semantic Product Search
Vihan Lakshman, Choon Hui Teo, Xiaowen Chu, Priyanka Nigam, Abhinandan Patni, Pooja Maknikar, S.V.N Vishwanathan
International Workshop on Interactive and Scalable Information Retrieval Methods for eCommerce, WSDM 2022
Paper

Low-Precision Quantization for Efficient Nearest Neighbor Search
Anthony Ko, Iman Keivanloo, Vihan Lakshman, Eric Schkufza
Manuscript
Paper

Semantic Product Search
Priyanka Nigam, Yiwei Song, Vijai Mohan, Vihan Lakshman, Weitian Ding, Ankit Shinghavi, Choon Hui Teo, Hao Gu, Bing Yin
KDD 2019
Paper

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Patents

Locality Sensitive Hashing to Clean and Normalize Text Logs
Vihan Lakshman, Chen Luo, Yesh Dattatreya, Nan Jiang
US Patent 11,244,156, 2022
Filing

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