Interpretable Anomaly Detection in Space Systems Using Physics-Informed Clustering Jishy Samuel, Sahely Bhadra, Mijaz Mukundan, Sanood U and Muhammed Tharikh AIAA collection of Aerospace research central, 2026[Link]
Going Beyond Explainability: Learning Justifiable Vision Transformers Guided by Flow Matching Thomas John, Akshay Krishna, Jotipriya Das, Mrinal Das European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2026
Modeling Task Uncertainty for Neural Processes to Meta-Learn with Fewer Tasks Eva Cherian, Mrinal Das Neurocomputing journal, 2026 |
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HEIGHTS: Hierarchical graph structure learning for time series anomaly detection Vinitha M Rajan, Sahely Bhadra Neurocomputing journal, 2026 |
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Advances in Electronic Health Records Enabled by Artificial Intelligence and Natural Language Processing: A Review of Recent Developments, Limitations and Future Applications Etana Fikadu Dinsa, Mrinal Das, Teklu Urgessa Abebe Discover Applied Sciences, 2026 |
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2025
Map Wisely for Efficient Transfer Learning across Heterogeneous Data Sources Snigdhatanu Acharya and Mrinal Das Neurocomputing journal, 2025 |
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A Supervised Learning Approach for Recommending Medical Specialists in the Healthcare Sector for the Afaan Oromo Context Etana Fikadu, Mrinal Das, Teklu Urgessa, Krishnaraj Ramaswamy Springer Nature Discover Computing, Volume 28, Article 46, 2025 |
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Contrastive Loss Coupled with Occlusion Aware Training Aids in Face Recognition from Low Quality Group Photos Sam Narayana Subudhi, Mrinal Das International Conference on Microwave, Optical and Communication Engineering, 2025
MLP-SVM: A Hybrid Approach for Improving the Performance of the Classification Model for Health-Related Documents from Social Media Using Multi-Layer Perceptron and Support Vector Machine Etana Fikadu, Mrinal Das, Teklu Urgesa Springer Nature Discover Applied Sciences, 2025 |
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Efficient 3D kernels for molecular property prediction Ankit, Sahely Bhadra, and J Rousu Bioinformatics 41 (Supplement_1), i58-i67, 2025 |
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Focus On What Matters: Guiding Vision Transformers Towards Justification Thomas John, Mrinal Das Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2025 |
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News about Global North Considered Truthful! The Geo-Political Veracity Gradient in Global South News Mandava, S., P, D., and Bhadra, S Emerging Media, 3(2), 203-213, 2025 |
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Warping resilient robust anomaly detection for multivariate time series S Abilasha, Sahely Bhadra Machine Learning 114(2): 29, 2025 |
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A Topic Modeling Approach for Analyzing and Categorizing Electronic Healthcare Documents in Afaan Oromo without Label Information. Etana Fikadu, Mrinal Das, Teklu Urgesa Nature Scientific Reports 14, Article number: 32051, 2025 |
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2024
Bottlenecked Backpropagation to Train Differentially Private Deep Neural Networks Arghyadeep Ghosh and Mrinal Das 27th European Conference on Artificial Intelligence (ECAI), 2024 |
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Automatic categorization of medical documents in Afaan Oromo using ensemble machine learning techniques Etana Fikadu, Mrinal Das, Teklu Urgesa Springer Nature Discover Applied Sciences, Vol 6, 2024 |
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Understanding latent affective bias in large pre-trained neural language models Anoop Kadan, Deepak P, Sahely Bhadra, Manjary P. Gangan, and Lajish V. L. Natural Language Processing Journal, Volume 7 page 62, 2024 |
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Geo-political bias in fake news detection AI: the case of affect Deepak P., Sahely Bhadra, Anna Jurek-Loughrey, G. Santhosh Kumar, and M. Satish Kumar AI & Ethics, 2024 |
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AI-based disease category prediction model using symptoms from low-resource Ethiopian language: Afaan Oromo text Etana Fikadu, Mrinal Das, Teklu Urgesa Nature Scientific Reports, volume 14, Article number: 11233, 2024
Catch them Unattentive: An Orientation Aware Face Recognition Mode Muhammed Favaz, Mrinal Das IEEE International Conference on Image Processing (ICIP) 2024
Human Guided Multi-Proportions Topic Model for Rare Event Detection without using Labels Mrinal Das, Gaurav Jain Intelligent Systems Conference (IntelliSys) 2024
2023 & before
CDGCN: Conditional de novo Drug Generative Model Using Graph Convolution Networks Shikha Mallick, and Sahely Bhadra Research in Computational Molecular Biology - 27th Annual International Conference, {RECOMB} Lecture Notes in Computer Science, volume 13976, Pages 104-119 |
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Learning with Domain Knowledge to Develop Justifiable Convolution Networks Rimmon Bhosale, Mrinal Das Asian Conference on Machine Learning (ACML), 2022 |
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Warping resilient scalable anomaly detection in time series S. Abilasha, Sahely Bhadra, P. Deepak and Anish Mathew Neurocomputing,Volume 511,Pages 22-33 (2022) |
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Deep Extreme Mixture Model for Time Series Forecasting Abilasha S., Sahely Bhadra, Ahmed Zaheer Dadarkar and Deepak P The 31st ACM International Conference on Information and Knowledge Management (CIKM ’22) (2022)
Understanding the limitations of network online learning. Timothy LaRock, Timothy Sakharov, Sahely Bhadra, Tina Eliassi-Rad Applied Network Science 5 (1) 60 (2020) |
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Large-Scale Sparse Kernel Canonical Correlation Analysis Viivi Uurtio , Sahely Bhadra and Juho Rousu Proceedings of the 36th International Conference on Machine Learning(ICML) 6383–6391 (2019) |
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Warping Resilient Time Series Embeddings Anish Mathew, Deepak P and Sahely Bhadra ICML 2019 Time Series Workshop (2019) |
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Book Chapter: Multi-View Data Completion Sahely Bhadra P D., Jurek-Loughrey A. (eds) Linking and Mining Heterogeneous and Multi-view Data. Unsupervised and Semi-Supervised Learning. Springer, Cham 1-25 (2019) |
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Sparse Non-Linear CCA through Hilbert-Schmidt Independence Criterion Viivi Uurtio, Sahely Bhadra, Juho Rusu IEEE International Conference on Data Mining (ICDM’18) (2018) |
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Limits of Learning in Incomplete Networks Timothy Larock, Timothy Sakhrov, Sahely Bhadra and Tina Eliassi - Rad. International School and Conference of Network Science (NetSci) (2018) |
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Reducing Network Incompleteness Through Online Learning: A Feasibility Study Timothy LaRock, Timothy Sakharov, Sahely Bhadra and Tina Eliassi-Rad Accepted for 14th International Workshop on Mining and Learning with Graphs (MLG) (2018) |
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Book Chapter: Analysis of Fluxomic Experiments with Principal Metabolic Flux Mode Analysis Sahely Bhadra and Juho Rousu Springer Book : Data Mining for Systems Biology (2018) |
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Principal Metabolic Flux Mode Analysis Sahely Bhadra, Peter Blomberg, Sandra Castillo, and Juho Rousu. Bioinformatics 34 (14) 2409–2417 (2018) |
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Weight-Agnostic Hierarchical Stick-Breaking Process. Mrinal Das, Chiranjib Bhattacharyya. IEEE International Conference on Big Knowledge (ICBK), 2018. |
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Efficient differentially private learning improves drug sensitivity prediction. Antti Honkela, Mrinal Das, Arttu Nieminen, Onur Dikmen, Samuel Kaski. Biology Direct, 2018 |
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Multi-view Kernel Completion. Sahely Bhadra, Samuel Kaski and Juho Rousu. Machine Learning 106 (5), 713-739, 2017 |
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SOPER: Discovering the influence of fashion and the many faces of User from Session logs using Stick Breaking Process. Lucky Dhakad, Mrinal Das, Chiranjib Bhattacharyya, Samik Datta, Mihir Kale, Vivek Mehta. International Conference on Information and Knowledge Management (CIKM), 2017. |
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SemEval 2017 Task 10: ScienceIE - Extracting Keyphrases and Relations from Scientific Publications. Isabelle Augenstein, Mrinal Das, Sebastian Riedel, Lakshmi Vikraman, Andrew McCallum. International Workshop on Semantic Evaluation, 2017. |
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Efficient differentially private learning. Antti Honkela, Mrinal Das, Onur Dikmen, Samuel Kaski. Theory and Practice of Differential Privacy WS at ICML 2016. |
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Correction of Noisy Labels via Mutual Consistency Check. Sahely Bhadra, Matthias Hein. Neurocomputing (160): 34-52, 2015. |
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Ordered Stick-Breaking Prior for Sequential MCMC Inference of Bayesian Nonparametric Models. Mrinal Das, Trapit Bansal, Chiranjib Bhattacharyya. International Conference on Machine Learning (ICML), 2015. |
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Content Driven User Profiling for Comment-Worthy Recommendations of News and Blog Articles. Trapit Bansal, Mrinal Das, Chiranjib Bhattacharyya. The ACM Conference Series on Recommender Systems (RecSys), 2015. |
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Relating Romanized Comments to News Articles by Inferring Multi-glyphic Topical Correspondence. Goutham Tholpadi, Mrinal Das, Trapit Bansal, Chiranjib Bhattacharyya. Association for the Advancement of Artificial Intelligence Conference (AAAI), 2015. |
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Going beyond Corr-LDA for Detecting Specific Comments on News & Blogs. Mrinal Das, Trapit Bansal, Chiranjib Bhattacharyya. ACM Conference on Web Search and Data Mining (WSDM), 2014. |
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Subtle Topic Models and Discovering Subtly Manifested Software Concerns Automatically. Mrinal Das, Suparna Bhattacharya, Chiranjib Bhattacharyya, K. Gopinath. International Conference on Machine Learning (ICML), 2013. |
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Efficient Methods for Robust Classification Under Uncertainty in Kernel Matrices. Aharon Ben-Tal, Sahely Bhadra, Chiranjib Bhattacharyya and Arkadi Nemirovski. Journal of Machine Learning Research 13 (Oct):2923.2954, 2012. |
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Cluster Labeling for Multilingual Scatter/Gather in Resource-scarce Languages. Goutham Tholpadi, Mrinal Das, Chiranjib Bhattacharyya, Shirish Shevade. European Conference on Information Retrieval (ECIR), 2012 |
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Web Information Extraction Using Markov Logic Networks (pdf). Sandeepkumar Satpal, Sahely Bhadra, S Sundararajan, Rajeev Rastogi, Prithviraj Sen. 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)2011. |
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Web Information Extraction Using Markov Logic Networks (Poster). Sandeepkumar Satpal, Sahely Bhadra, S Sundararajan, Rajeev Rastogi, Prithviraj Sen. International World Wide Web Conferences (WWW) 2011. |
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Chance constrained uncertain classification via robust optimization. Aharon Ben-Tal, Sahely Bhadra, Chiranjib Bhattacharyya and J. Saketha Nath. Mathematical Programming Series B, 2011. |
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Learning Dirichlet Processes from Partially Observed Groups. Avinava Dubey, Indrajit Bhattacharya, Mrinal Das, Tanveer Faruquie, Chiranjib Bhattacharyya. International Conference on Data Mining (ICDM), 2011 |
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Robust Formulations for Handling Uncertainty in Kernel Matrices(paper,demo). Sahely Bhadra, Sourangshu Bhattacharrya , Chiranjib Bhattacharyya and Aharon Ben-Tal. International Conference on Machine Learning (ICML) 2010. |
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Interval Data Classification under Partial Information: A Chance-Constraint Approach (pdf). Sahely Bhadra, J. Saketha Nath, Aharon Ben-Tal and Chiranjib Bhattacharyya. Achieved Best Runner-up certificate in PAKDD-2009. |
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A Linear Programming Approach for Estimating the Structure of a Sparse Linear Genetic Network from Transcript Profiling Data. S. Bhadra , C. Bhattacharyya , N. Chandra , I.S. Mian. Accepted for Journal of Algorithms for Molecular Biology, 2009. |
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Non-dominated Rank based Sorting Genetic Algorithms. Ashish Ghosh, Mrinal Kanti Das. Journal of Fundamenta Informaticae, volume 83, number 3, pages 231-252, 2008. |
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