| 2026 | CCGRID | EAFAL: An Edge-Based Agentic Framework for Adaptive Selection Between SLMs and LLMs. | Chamara Madarasingha, Prajyot Singh, Redowan Mahmud, Mahbuba Afrin, Aneesh Krishna, Salil S. Kanhere |
| 2026 | WWW | Machine Learning as a Service (MLaaS) Dataset Generator Framework for IoT Environments. | Deepak Kanneganti, Sajib Mistry, Sheik Mohammad Mostakim Fattah, Joshua Boland, Aneesh Krishna |
| 2025 | ENASE | An Empirical Framework for Automatic Identification of Video Game Development Problems Using Multilayer Perceptron. | Pratham Maan, Lov Kumar, Vikram Singh, Lalita Bhanu Murthy Neti, Aneesh Krishna |
| 2025 | ICWS | Adaptive Composition of Machine Learning as a Service (MLaaS) for IoT Environments. | Deepak Kanneganti, Sajib Mistry, Sheik Mohammad Mostakim Fattah, Aneesh Krishna, Monowar Bhuyan |
| 2025 | WWW | TIME 2025: 1st International Workshop on Transformative Insights in Multi-faceted Evaluation. | Lei Wang, Md. Zakir Hossain, Syed M. S. Islam, Tom Gedeon, Sharifa Alghowinem, Isabella Yu, Serena Bono, Xuanying Zhu, Gennie Nguyen, Nur Al Hasan Haldar, Seyed Mohammad Jafar Jalali, Md. Abdur Razzaque, Imran Razzak, Md. Rafiqul Islam, Shahadat Uddin, Naeem Janjua, Aneesh Krishna, Manzur Ashraf |
| 2025 | WWW | Personalised News Summarisation Using Demographic-aware BART Model. | Daniel M. McFadyen, Md. Redowan Mahmud, Mahbuba Afrin, Sajib Mistry, Aneesh Krishna |
| 2025 | WWW | Reinforcement Learning Controlled Adaptive PSO for Task Offloading in IIoT Edge Computing. | Minod Perera, Sheik Mohammad Mostakim Fattah, Sajib Mistry, Aneesh Krishna |
| 2024 | AINA | Investigating BERT Layer Performance and SMOTE Through MLP-Driven Ablation on Gittercom. | Bathini Sai Akash, Vikram Singh, Aneesh Krishna, Lalita Bhanu Murthy Neti, Lov Kumar |
| 2024 | AINA | An Empirical Analysis on Leveraging User Reviews with NLP-Enhanced Word Embeddings for App Rating Prediction. | Pratyush Mishra, Vikram Singh, Aneesh Krishna, Lov Kumar |
| 2024 | DICTA | Domain Adversarial SegFormer. | Moritz Bergemann, Tanmay Singha, Duc-Son Pham, Aneesh Krishna |
| 2024 | EACL | Thesis Proposal: Detecting Empathy Using Multimodal Language Model. | Md. Rakibul Hasan, Md. Zakir Hossain, Aneesh Krishna, Jessica Sharmin Rahman, Tom Gedeon |
| 2024 | ICONIP | MedSiML: A Multilingual Approach for Simplifying Medical Texts. | Hardik A. Jain, Chirayu Patel, Riyasatali Umatiya, Sajib Mistry, Aneesh Krishna, Amin Beheshti |
| 2024 | ICONIP | A Hybrid Contextual Deep Learning Model to Predict Renewable Energy Generation. | Deepak Kanneganti, Sajib Mistry, Sumedha Rajakaruna, Aneesh Krishna, Amin Beheshti |
| 2024 | WISE | Context-Aware Selection of Machine Learning as a Service (MLaaS) in IoT Environments. | Keya Patel, Sajib Mistry, Deepak Kanneganti, Aneesh Krishna |
| 2023 | CIT | An Empirical Framework for Malware Prediction Using Multi-Layer Perceptron. | Vikram Singh, Lov Kumar, Anoop Kumar Patel, Aneesh Krishna |
| 2023 | DICTA | Semantic Segmentation for Improved Cell Nuclei Analysis. | Joren Regan, Chaki Ramesh, Saurabh Gupta, Ankur Sharma, Duc-Son Pham, Aneesh Krishna |
| 2023 | ENASE | Software Engineering Comments Sentiment Analysis Using LSTM with Various Padding Sizes. | Sanidhya Vijayvargiya, Lov Kumar, Lalita Bhanu Murthy Neti, Sanjay Misra, Aneesh Krishna, Srinivas Padmanabhuni |
| 2023 | ENASE | Empirical Analysis for Investigating the Effect of Machine Learning Techniques on Malware Prediction. | Sanidhya Vijayvargiya, Lov Kumar, Lalita Bhanu Murthy Neti, Sanjay Misra, Aneesh Krishna, Srinivas Padmanabhuni |
| 2023 | FedCSIS | An Empirical Framework for Software Aging-Related Bug Prediction using Weighted Extreme Learning Machine. | Lov Kumar, Vikram Singh, Lalita Bhanu Murthy Neti, Sanjay Misra, Aneesh Krishna |
| 2023 | ICONIP | Empirical Analysis of Multi-label Classification on GitterCom Using BERT and ML Classifiers. | Bathini Sai Akash, Lov Kumar, Vikram Singh, Anoop Kumar Patel, Aneesh Krishna |
| 2023 | ICONIP | Effi-Seg: Rethinking EfficientNet Architecture for Real-Time Semantic Segmentation. | Tanmay Singha, Duc-Son Pham, Aneesh Krishna |
| 2023 | Mobiquitous | Adaptive QoS-Aware Task Offloading in Dynamic Mobile Edge Computing Environment. | Jacob Don, Sajib Mistry, Md. Redowan Mahmud, Aneesh Krishna |
| 2023 | TrustCom | On-graph Machine Learning-based Fraud Detection in Ethereum Cryptocurrency Transactions. | Helen Milner, Md. Redowan Mahmud, Mahbuba Afrin, Sashowta G. Siddhartha, Sajib Mistry, Aneesh Krishna |
| 2022 | AINA | Predicting Cyber-Attacks on IoT Networks Using Deep-Learning and Different Variants of SMOTE. | Bathini Sai Akash, Pavan Kumar Reddy Yannam, Bokkasam Venkata Sai Ruthvik, Lov Kumar, Lalita Bhanu Murthy Neti, Aneesh Krishna |
| 2022 | AINA | Software Functional and Non-function Requirement Classification Using Word-Embedding. | Lov Kumar, Siddarth Baldwa, Shreya Manish Jambavalikar, Lalita Bhanu Murthy Neti, Aneesh Krishna |
| 2022 | AINA | COVID-19 Article Classification Using Word-Embedding and Extreme Learning Machine with Various Kernels. | Sanidhya Vijayvargiya, Lov Kumar, Aruna Malapati, Lalita Bhanu Murthy Neti, Aneesh Krishna |
| 2022 | FedCSIS | Software Sentiment Analysis using Deep-learning Approach with Word-Embedding Techniques. | Venkata Krishna Chandra Mula, Lov Kumar, Lalita Bhanu Murthy Neti, Aneesh Krishna |
| 2022 | ICWS | Temporal Match Analysis and Recommending Substitutions in Live Soccer Games. | Yuval Berman, Sajib Mistry, Joby Mathew, Aneesh Krishna |
| 2021 | AINA | An Empirical Study on Predictability of Software Code Smell Using Deep Learning Models. | Himanshu Gupta, Tanmay Girish Kulkarni, Lov Kumar, Lalita Bhanu Murthy Neti, Aneesh Krishna |
| 2021 | DICTA | SCMNet: Shared Context Mining Network for Real-time Semantic Segmentation. | Tanmay Singha, Moritz Bergemann, Duc-Son Pham, Aneesh Krishna |
| 2021 | ICONIP | A Lightweight Multi-scale Feature Fusion Network for Real-Time Semantic Segmentation. | Tanmay Singha, Duc-Son Pham, Aneesh Krishna, Tom Gedeon |
| 2020 | DICTA | FANet: Feature Aggregation Network for Semantic Segmentation. | Tanmay Singha, Duc-Son Pham, Aneesh Krishna |
| 2020 | HPCC | An Empirical Analysis on the Role of WSDL Metrics in Web Service Anti-Pattern Prediction. | Sahithi Tummalapalli, Lov Kumar, Lalita Bhanu Murthy Neti, Aneesh Krishna |
| 2020 | ICONIP | Efficient Segmentation Pyramid Network. | Tanmay Singha, Duc-Son Pham, Aneesh Krishna, Joel Dunstan |
| 2020 | ICONIP | Detection of Web Service Anti-patterns Using Neural Networks with Multiple Layers. | Sahithi Tummalapalli, Lov Kumar, N. L. Bhanu Murthy, Aneesh Krishna |
| 2019 | ICONIP | Prediction of Refactoring-Prone Classes Using Ensemble Learning. | Vamsi Krishna Aribandi, Lov Kumar, Lalita Bhanu Murthy Neti, Aneesh Krishna |
| 2019 | KES | On framework development for the dynamic prosumer coalition in a smart grid and its evaluation by analytic tools. | Sreenithya Sumesh, Aneesh Krishna, Vidyasagar M. Potdar, Shastri L. Nimmagadda |
| 2018 | BIBE | An Intensive Search for Higher-Order Gene-Gene Interactions by Improving Deep Learning Model. | Suneetha Uppu, Aneesh Krishna |
| 2018 | ICONIP | Application of SMOTE and LSSVM with Various Kernels for Predicting Refactoring at Method Level. | Lov Kumar, Shashank Mouli Satapathy, Aneesh Krishna |
| 2018 | ICONIP | Convolutional Model for Predicting SNP Interactions. | Suneetha Uppu, Aneesh Krishna |
| 2017 | ICONIP | Tuning Hyperparameters for Gene Interaction Models in Genome-Wide Association Studies. | Suneetha Uppu, Aneesh Krishna |
| 2016 | ICONIP | Improving Strategy for Discovering Interacting Genetic Variants in Association Studies. | Suneetha Uppu, Aneesh Krishna |
| 2015 | APSEC | Citizen's Charter Driven Service Area Improvement. | Anna Marie Fortuito, Moshiur Bhuiyan, Farzana Haque, Luba Shabnam, Aneesh Krishna, P. W. Chandana Prasad |
| 2015 | APSEC | Optimal Reasoning of Goals in the i* Framework. | Chitra M. Subramanian, Aneesh Krishna, Arshinder Kaur |
| 2015 | EDOC | Multidimensional Cluster Sampling View on Large Databases for Approximate Query Processing. | Tomohiro Inoue, Aneesh Krishna, Raj P. Gopalan |
| 2015 | ICONIP | A Multifactor Dimensionality Reduction Based Associative Classification for Detecting SNP Interactions. | Suneetha Uppu, Aneesh Krishna, Raj P. Gopalan |
| 2015 | SEKE | Quantitative Reasoning of Goal Satisfaction in the i*Framework. | Chitra M. Subramanian, Aneesh Krishna, Arshinder Kaur, Raj P. Gopalan |
| 2014 | BIBE | An Associative Classification Based Approach for Detecting SNP-SNP Interactions in High Dimensional Genome. | Suneetha Uppu, Aneesh Krishna, Raj P. Gopalan |
| 2014 | COMPSAC | Software-as-a-Service Solution Implementation - Data Migration Perspective. | Luba Shabnam, Farzana Haque, Moshiur Bhuiyan, Aneesh Krishna |
| 2014 | COMPSAC | Risk Measure Propagation through Organisational Network. | Luba Shabnam, Farzana Haque, Moshiur Bhuiyan, Aneesh Krishna |
| 2013 | APCCM | Optimal Selection of Operationalizations for Non-Functional Requirements. | Amy Affleck, Aneesh Krishna, Narasimaha Achuthan |
| 2013 | WACV | Using Kinect for face recognition under varying poses, expressions, illumination and disguise. | Billy Y. L. Li, Ajmal S. Mian, Wanquan Liu, Aneesh Krishna |
| 2013 | SEKE | Virtual Medical Board: A Distributed Bayesian Agent Based Approach (S). | Animesh Dutta, Sudipta Acharya, Aneesh Krishna, Swapan Bhattacharya |
| 2012 | ICPR | Tensor based robust color face recognition. | Billy Y. L. Li, Wanquan Liu, Senjian An, Aneesh Krishna |
| 2011 | ICIG | The MCF Model: Utilizing Multiple Colors for Face Recognition. | Billy Y. L. Li, Senjian An, Wanquan Liu, Aneesh Krishna |
| 2011 | SEKE | A Process Oriented Approach to Model Non-Functional Requirements Proposition Extending UML. | Aneesh Krishna |
| 2010 | SEKE | Quality Indicators in Requirements Elicitation. | Aneesh Krishna, Andreas Gregoriades, Chattrakul Sombattheera |
| 2009 | SERVICES | Ant Inspired Scalable Peer Selection in Ontology-Based Service Composition. | Shuai Yuan, Jun Shen, Aneesh Krishna |
| 2008 | BPM | Dynamic Selection of Service Peers with Multiple Property Specifications. | Jun Shen, Shuai Yuan, Aneesh Krishna |
| 2007 | COMPSAC | Integration of Agent-Oriented Conceptual Models and UML Activity Diagrams Using Effect Annotations. | Moshiur Bhuiyan, M. M. Zahidul Islam, Aneesh Krishna, Aditya Ghose |
| 2007 | COMPSAC | Managing Business Process Risk Using Rich Organizational Models. | Moshiur Bhuiyan, M. M. Zahidul Islam, George Koliadis, Aneesh Krishna, Aditya Ghose |
| 2007 | ER | Agent Based Executable Conceptual Models Using i* and CASO. | Aniruddha Dasgupta, Aneesh Krishna, Aditya K. Ghose |
| 2006 | BPM | Combining | George Koliadis, Aleksandar Vranesevic, Moshiur Bhuiyan, Aneesh Krishna, Aditya K. Ghose |
| 2006 | SEKE | Genre-based approach to Requirements Elicitation. | Aneesh Krishna, Rodney J. Clarke, Aditya K. Ghose |
| 2005 | SEKE | Combining Agent-oriented Conceptual Modelling and the UML Sequence Diagram. | Aneesh Krishna, Aditya K. Ghose |
| 2005 | SEKE | Loosely-coupled Consistency between Agent-oriented Conceptual Models and Z Specifications. | Aneesh Krishna, Aditya K. Ghose, Sergiy A. Vilkomir |
| 2005 | SEKE | Towards Executable Specification: Combining i* and AgentSpeak(L) . | Farzad Salim, Chee Fon Chang, Aneesh Krishna, Aditya Ghose |
| 2003 | SEKE | Agent-assisted Distributed Requirements Elicitation and Management. | Chee Fon Chang, Aneesh Krishna, Aditya K. Ghose |