Parallel Bayesian Network Structure Learning for Genome-Scale Gene Networks. - Sanchit Misra; Md. Vasimuddin; Kiran Pamnany; Sriram P. Chockalingam; Yong Dong; Min Xie; Maneesha R. Aluru; Srinivas Aluru (SC, 2014)

Dtree: Dynamic Task Scheduling at Petascale. - Kiran Pamnany; Sanchit Misra; Md. Vasimuddin; Xing Liu; Edmond Chow; Srinivas Aluru (ISC, 2015)

Parallel Exact Dynamic Bayesian Network Structure Learning with Application to Gene Networks. - Md. Vasimuddin; Srinivas Aluru (HiPC, 2017)

Performance extraction and suitability analysis of multi- and many-core architectures for next generation sequencing secondary analysis. - Sanchit Misra; Tony C. Pan; Kanak Mahadik; George Powley; Priya N. Vaidya; Md. Vasimuddin; Srinivas Aluru (PACT, 2018)

A Parallel Algorithm for Bayesian Network Inference Using Arithmetic Circuits. - Md. Vasimuddin; Sriram P. Chockalingam; Srinivas Aluru (IPDPS, 2018)

Efficient Architecture-Aware Acceleration of BWA-MEM for Multicore Systems. - Md. Vasimuddin; Sanchit Misra; Heng Li 002; Srinivas Aluru (IPDPS, 2019)

LISA: Towards Learned DNA Sequence Search. - Darryl Ho; Jialin Ding 001; Sanchit Misra; Nesime Tatbul; Vikram Nathan; Md. Vasimuddin; Tim Kraska (CoRR, 2019)

Deep Graph Library Optimizations for Intel(R) x86 Architecture. - Sasikanth Avancha; Md. Vasimuddin; Sanchit Misra; Ramanarayan Mohanty (CoRR, 2020)

GenomicsBench: A Benchmark Suite for Genomics. - Arun Subramaniyan 001; Yufeng Gu; Timothy Dunn; Somnath Paul; Md. Vasimuddin; Sanchit Misra; David T. Blaauw; Satish Narayanasamy; Reetuparna Das (ISPASS, 2021)

Tensor processing primitives: a programming abstraction for efficiency and portability in deep learning workloads. - Evangelos Georganas; Dhiraj D. Kalamkar; Sasikanth Avancha; Menachem Adelman; Cristina Anderson; Alexander Breuer; Jeremy Bruestle; Narendra Chaudhary; Abhisek Kundu; Denise Kutnick; Frank Laub; Md. Vasimuddin; et al. (SC, 2021)

DistGNN: scalable distributed training for large-scale graph neural networks. - Md. Vasimuddin; Sanchit Misra; Guixiang Ma; Ramanarayan Mohanty; Evangelos Georganas; Alexander Heinecke; Dhiraj D. Kalamkar; Nesreen K. Ahmed; Sasikanth Avancha (SC, 2021)

Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads. - Evangelos Georganas; Dhiraj D. Kalamkar; Sasikanth Avancha; Menachem Adelman; Cristina Anderson; Alexander Breuer; Narendra Chaudhary; Abhisek Kundu; Md. Vasimuddin; Sanchit Misra; Ramanarayan Mohanty; Hans Pabst; et al. (CoRR, 2021)

DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86 via Minibatch Sampling. - Md. Vasimuddin; Ramanarayan Mohanty; Sanchit Misra; Sasikanth Avancha (CoRR, 2022)

Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning and HPC Workloads. - Evangelos Georganas; Dhiraj D. Kalamkar; Sasikanth Avancha; Menachem Adelman; Deepti Aggarwal; Cristina Anderson; Alexander Breuer; Jeremy Bruestle; Narendra Chaudhary; Abhisek Kundu; Denise Kutnick; Frank Laub; et al. (Frontiers Appl. Math. Stat., 2022)

Accelerating minimap2 for long-read sequencing applications on modern CPUs. - Saurabh Kalikar; Chirag Jain; Md. Vasimuddin; Sanchit Misra (Nat. Comput. Sci., 2022)

GenDP: A Framework of Dynamic Programming Acceleration for Genome Sequencing Analysis. - Yufeng Gu; Arun Subramaniyan 001; Timothy Dunn; Alireza Khadem; Kuan-Yu Chen 001; Somnath Paul; Mohammad Vasimuddin; Sanchit Misra; David T. Blaauw; Satish Narayanasamy; Reetuparna Das (Commun. ACM, 2025)