PAGER: Parameterless, Accurate, Generic, Efficient kNN-Based Regression. - Himanshu Singh; Aditya Desai; Vikram Pudi (DEXA (2), 2010)

SEAR - Scalable, Efficient, Accurate, Robust kNN-based Regression. - Aditya Desai; Himanshu Singh; Vikram Pudi (KDIR, 2010)

Knowledge management and software testing. - Aditya Desai; S. Shah (ICWET, 2011)

DISC: Data-Intensive Similarity Measure for Categorical Data. - Aditya Desai; Himanshu Singh; Vikram Pudi (PAKDD (2), 2011)

Facilitating Verification in Program Loops by Identification of Static Iteration Patterns. - Aditya Desai; Era Jain; Subhajit Roy 001 (APSEC (1), 2013)

Wideband printed dipole antenna with embedded loops and coupling patches for digital TV signal reception. - Deepak C. Karia; Madhuri Bhujbal; Aditya Desai (ICACCI, 2014)

Inbuilt Multiband Microstrip Antenna for Portable Devices. - Aditya Desai; Deepak C. Karia; Madhuri Bhujbal (SIRS, 2014)

A Full Body Steerable Wind Display for a Locomotion Interface. - Sandip D. Kulkarni; Charles Fisher; Price Lefler; Aditya Desai; Shanthanu Chakravarthy; Eric R. Pardyjak; Mark A. Minor; John M. Hollerbach (IEEE Trans. Vis. Comput. Graph., 2015)

Program synthesis using natural language. - Aditya Desai; Sumit Gulwani; Vineet Hingorani; Nidhi Jain; Amey Karkare; Mark Marron; Sailesh R; Subhajit Roy 001 (ICSE, 2016)

Raw Nav-merge Seismic Data to Subsurface Properties with MLP based Multi-Modal Information Unscrambler. - Aditya Desai; Zhaozhuo Xu; Menal Gupta; Anu Chandran; Antoine Vial-Aussavy; Anshumali Shrivastava (NeurIPS, 2021)

Active Sampling Count Sketch (ASCS) for Online Sparse Estimation of a Trillion Scale Covariance Matrix. - Zhenwei Dai; Aditya Desai; Reinhard Heckel; Anshumali Shrivastava (SIGMOD Conference, 2021)

Smart Car Features using Embedded Systems and IoT. - Abhishek Das; Vivek Dhuri; Aditya Desai; Suyash Ail; Ameya Kadam (CoRR, 2021)

Density Sketches for Sampling and Estimation. - Aditya Desai; Benjamin Coleman; Anshumali Shrivastava (CoRR, 2021)

Beyond Convolutions: A Novel Deep Learning Approach for Raw Seismic Data Ingestion. - Zhaozhuo Xu; Aditya Desai; Menal Gupta; Anu Chandran; Antoine Vial-Aussavy; Anshumali Shrivastava (CoRR, 2021)

Semantically Constrained Memory Allocation (SCMA) for Embedding in Efficient Recommendation Systems. - Aditya Desai; Yanzhou Pan; Kuangyuan Sun; Li Chou; Anshumali Shrivastava (CoRR, 2021)

Random Offset Block Embedding Array (ROBE) for CriteoTB Benchmark MLPerf DLRM Model : 1000× Compression and 2.7× Faster Inference. - Aditya Desai; Li Chou; Anshumali Shrivastava (CoRR, 2021)

An efficient neural-network model for real-time fault detection in industrial machine. - Amar Kumar Verma; Shivika Nagpal; Aditya Desai; Radhika Sudha (Neural Comput. Appl., 2021)

Random Offset Block Embedding (ROBE) for compressed embedding tables in deep learning recommendation systems. - Aditya Desai; Li Chou; Anshumali Shrivastava (MLSys, 2022)

The trade-offs of model size in large recommendation models : 100GB to 10MB Criteo-tb DLRM model. - Aditya Desai; Anshumali Shrivastava (NeurIPS, 2022)

Efficient model compression with Random Operation Access Specific Tile (ROAST) hashing. - Aditya Desai; Keren Zhou 001; Anshumali Shrivastava (CoRR, 2022)

The trade-offs of model size in large recommendation models : A 10000 × compressed criteo-tb DLRM model (100 GB parameters to mere 10MB). - Aditya Desai; Anshumali Shrivastava (CoRR, 2022)

Surgical gestures as a method to quantify surgical performance and predict patient outcomes. - Runzhuo Ma; Ashwin Ramaswamy; Jiashu Xu; Loc Trinh; Dani Kiyasseh; Timothy N. Chu; Elyssa Y. Wong; Ryan S. Lee; Ivan Rodriguez; Gina Demeo; Aditya Desai; Maxwell X. Otiato; et al. (npj Digit. Medicine, 2022)

Hardware-Aware Compression with Random Operation Access Specific Tile (ROAST) Hashing. - Aditya Desai; Keren Zhou 001; Anshumali Shrivastava (ICML, 2023)

Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time. - Zichang Liu; Aditya Desai; Fangshuo Liao; Weitao Wang; Victor Xie; Zhaozhuo Xu; Anastasios Kyrillidis; Anshumali Shrivastava (NeurIPS, 2023)

Heterogeneous federated collaborative filtering using FAIR: Federated Averaging in Random Subspaces. - Aditya Desai; Benjamin Meisburger; Zichang Liu; Anshumali Shrivastava (CoRR, 2023)

Machine learning for cognitive behavioral analysis: datasets, methods, paradigms, and research directions. - Priya Bhatt; Amanrose Sethi; Vaibhav Tasgaonkar; Jugal Shroff; Isha Pendharkar; Aditya Desai; Pratyush Sinha; Aditya Deshpande; Gargi Joshi; Anil Rahate; Priyanka Jain; Rahee Walambe; et al. (Brain Informatics, 2023)

Training Against Disguises: Addressing and Mitigating Bias in Facial Emotion Recognition with Synthetic Data. - Aadith Sukumar; Aditya Desai; Peeyush Singhal; Sai Gokhale; Deepak Kumar Jain 001; Rahee Walambe; Ketan Kotecha (FG, 2024)

In defense of parameter sharing for model-compression. - Aditya Desai; Anshumali Shrivastava (ICLR, 2024)

SS1: Accelerating Inference with Fast and Expressive Sketch Structured Transform. - Aditya Desai; Kimia Saedi; Apoorv Walia; Jihyeong Lee; Keren Zhou 001; Anshumali Shrivastava (NeurIPS, 2024)

HashAttention: Semantic Sparsity for Faster Inference. - Aditya Desai; Shuo Yang; Alejandro Cuadron; Ana Klimovic; Matei Zaharia; Joseph E. Gonzalez; Ion Stoica (CoRR, 2024)

IDentity with Locality: An Ideal Hash for Gene Sequence Search. - Tianyi Zhang 011; Gaurav Gupta; Aditya Desai; Anshumali Shrivastava (KDD (1), 2025)

The Danger of Overthinking: Examining the Reasoning-Action Dilemma in Agentic Tasks. - Alejandro Cuadron; Dacheng Li; Wenjie Ma; Xingyao Wang 002; Yichuan Wang; Siyuan Zhuang; Shu Liu; Luis Gaspar Schroeder; Tian Xia; Huanzhi Mao; Nicholas Thumiger; Aditya Desai; et al. (CoRR, 2025)