Parallelization of a dynamic SVD clustering algorithm and its application in information retrieval. - Karthick Seshadri; K. Viswanathan Iyer (Softw. Pract. Exp., 2010)

Parallel algorithms for merging topic trees and their application in meta search engines. - Karthick Seshadri; S. Mercy Shalinie (CODS, 2015)

Parallelization of a graph-cut based algorithm for hierarchical clustering of web documents. - Karthick Seshadri; S. Mercy Shalinie (Concurr. Comput. Pract. Exp., 2015)

Design and evaluation of a parallel algorithm for inferring topic hierarchies. - Karthick Seshadri; S. Mercy Shalinie; Chidambaram Kollengode (Inf. Process. Manag., 2015)

A distributed parallel algorithm for inferring hierarchical groups from large-scale text corpuses. - Karthick Seshadri; Mercy Shalinie Selvaraj; Sidharth Manohar (Concurr. Comput. Pract. Exp., 2018)

Design and evaluation of a parallel document clustering algorithm based on hierarchical latent semantic analysis. - Karthick Seshadri; K. Viswanathan Iyer; Mercy Shalinie Selvaraj (Concurr. Comput. Pract. Exp., 2019)

Deep Learning-based Framework for Smart Sustainable Cities: A Case-study in Protection from Air Pollution. - Nagarathna Ravi; Vimala Rani P; Rajesh Alias Harinarayan R; Mercy Shalinie Selvaraj; Karthick Seshadri; Pariventhan P (Int. J. Intell. Inf. Technol., 2019)

Metric Learning for comparison of HMMs using Graph Neural Networks. - Rajan Kumar Soni; Karthick Seshadri; Balaraman Ravindran (ACML, 2021)

A scalable parallel algorithm for building web directories. - Karthick Seshadri; Aswin Maruthappan; Mukunthapriya Sundar Raman (Concurr. Comput. Pract. Exp., 2021)

Anomaly Detection in ATM Vestibules Using Three-Stream Deep Learning Approach. - Mehant Kammakomati; Suryadevara Deepak Chowdary; Srikanth Naik Varthya; Karthick Seshadri (CVIP (1), 2022)

Fine-tuning the Robust Temporal Feature Magnitude Model for Enhancing the Accuracy of Anomaly Detection. - Charan Charupalli; Karthick Seshadri (MIPR, 2022)

Workload characterization and synthesis for cloud using generative stochastic processes. - Korrapati Sindhu; Karthick Seshadri; Chidambaram Kollengode (J. Supercomput., 2022)

Evaluation of Hybrid Quantum Approximate Inference Methods on Bayesian Networks. - Padmil Nayak; Karthick Seshadri (BDA, 2023)

Sentiment Analysis of Code-Mixed Telugu-English Data Leveraging Syllable and Word Embeddings. - Upendar Rao Rayala; Karthick Seshadri; Nagesh Bhattu Sristy (ACM Trans. Asian Low Resour. Lang. Inf. Process., 2023)

Joint modeling of causal phrases-sentiments-aspects using Hierarchical Pitman Yor Process. - V. R. P. S. Sastry Yadavilli; Karthick Seshadri; S. Nagesh Bhattu (Inf. Process. Manag., 2024)

Design and Evaluation of a Hierarchical Characterization and Adaptive Prediction Model for Cloud Workloads. - Karthick Seshadri; Korrapati Sindhu; S. Nagesh Bhattu; Chidambaram Kollengode (IEEE Trans. Cloud Comput., 2024)

A dynamic probabilistic graphical model for mapping tasks to virtual machines in data centers. - Korrapati Sindhu; Karthick Seshadri (Eng. Appl. Artif. Intell., 2025)

An Advancement in Huffman Coding With a Potential for Parallel Decoding. - K. Viswanathan Iyer; Karthick Seshadri; K. Srinivasulu (Concurr. Comput. Pract. Exp., 2025)

Towards quantum amenable Bayesian networks: classical transformation to facilitate quantum inference. - Padmil Nayak; Karthick Seshadri (Quantum Mach. Intell., 2025)