Publications

2021

  • Conferences
  • Subhapratta Datta, Sarah Masud, Sakshi Makkar, Chhavi Jain, Vikram Goyal, Amitava Das, Tanmoy Chakraborty, “Hate is the New Infodemic: Modeling and Visualizing Hate Speech Diffusion on Twitter”, In International Conference on Data Engineering (ICDE), 2021.

2020

  • Journals
  • Singhal V, Majumdar A. A domain adaptation approach to solve inverse problems in imaging via coupled deep dictionary learning. Pattern Recognition. 2020 Apr 1;100:107163.
  • Mongia A, Majumdar A. Drug-target interaction prediction using Multi Graph Regularized Nuclear Norm Minimization. Plos one. 2020 Jan 16;15(1):e0226484.
  • Singhal V, Majumdar A. Reconstructing Multi-echo Magnetic Resonance Images via Structured Deep Dictionary Learning. Neurocomputing. 2020 Mar 14.
  • Mongia A, Sengupta D, Majumdar A. deepmc: Deep matrix completion for imputation of single-cell rna-seq data. Journal of Computational Biology. 2020 Jul 1;27(7):1011-9.
  • Iyer A, Gupta K, Sharma S, Hari K, Lee YF, Ramalingam N, Yap YS, West J, Bhagat AA, Subramani BV, Sabuwala B. Integrative analysis and machine learning based characterization of single circulating tumor cells. Journal of clinical medicine. 2020 Apr;9(4):1206.
  • Gupta K, Mohanty S. K, Kalra S, Mittal A, Mishra T, Ahuja J, Sengupta D*, Ahuja, G*. The molecular basis of loss of smell in 2019-nCoV infected individuals. Briefings in Bioinformatics, 2020.
  • Kalra S, Mittal A, Bajoria M, Mishra T, Maryam S, Sengupta D, Ahuja G. Challenges and possible solutions for decoding extranasal olfactory receptors. The FEBS Journal. 2020 Oct 21.
  • Rai P, Sengupta D, Majumdar A. SelfE: Gene Selection via Self-Expression for Single-Cell Data. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2020 May 25.
  • Farswan A, Gupta A, Gupta R, Kaur G. Imputation of gene expression data in blood cancer and its significance in inferring biological pathways. Frontiers in oncology. 2020 Jan 8;9:1442.
  • Gehlot S, Gupta A, Gupta R. SDCT-AuxNetθ: DCT augmented stain deconvolutional CNN with auxiliary classifier for cancer diagnosis. Medical Image Analysis. 2020 Apr 1;61:101661.
  • Kaur G, Ruhela V, Rani L, Gupta A, Sriram K, Gogia A, Sharma A, Kumar L, Gupta R. RNA-Seq profiling of deregulated miRs in CLL and their impact on clinical outcome. Blood cancer journal. 2020 Jan 13;10(1):1-9.
  • Jain A, Goel P, Aggarwal S, Fell A, Anand S. Symmetric k-means for Deep Neural Network Compression and Hardware Acceleration on FPGAs. IEEE Journal of Selected Topics in Signal Processing. 2020 Jan 22.
  • Arora U, Dutta HS, Joshi B, Chetan A, Chakraborty T. Analyzing and Detecting Collusive Users Involved in Blackmarket Retweeting Activities. ACM Transactions on Intelligent Systems and Technology (TIST). 2020 Apr 18;11(3):1-24.
  • Dutta HS, Dutta VR, Adhikary A, Chakraborty T. HawkesEye: Detecting fake retweeters using Hawkes process and topic modeling. IEEE Transactions on Information Forensics and Security. 2020 Jan 30;15:2667-78.
  • Gupta V, Aggarwal A, Chakraborty T. Detecting and Characterizing Extremist Reviewer Groups in Online Product Reviews. IEEE Transactions on Computational Social Systems. 2020 May 4.
  • Mehra J, Kumar V, Srivastava P, Sethi T. lncRNA Mediated Hijacking of T-cell Hypoxia Response Pathway by Mycobacterium Tuberculosis Predicts Latent to Active Progression in Humans. bioRxiv. 2020 Jan 1.
  • Pandey R, Gautam V, Bhagat K, Sethi T. A machine learning application for raising wash awareness in the times of covid-19 pandemic. arXiv preprint arXiv:2003.07074. 2020 Mar 16.
  • Awasthi R, Pal R, Singh P, Nagori A, Reddy S, Gulati A, Kumaraguru P, Sethi T. CovidNLP: A Web Application for Distilling Systemic Implications of COVID-19 Pandemic with Natural Language Processing. medRxiv. 2020.
  • Itzhak N, Nagori A, Lior E, Schvetz M, Lodha R, Sethi T, Moskovitch R. Acute Hypertensive Episodes Prediction. In International Conference on Artificial Intelligence in Medicine 2020 Aug 25 (pp. 392-402). Springer, Cham.
  • Chakraborty T, Park N, Agarwal A, Subrahmanian VS. Ensemble Detection and Analysis of Communities in Complex Networks. ACM Transactions on Data Science. 2020 Mar 12;1(1):1-34.
  • Dutta S, Das D, Chakraborty T. Changing views: Persuasion modeling and argument extraction from online discussions. Information Processing & Management. 2020 Mar 1;57(2):102085.
  • Gupta A, Duggal R, Gehlot S, Gupta R, Mangal A, Kumar L, Thakkar N, Satpathy D. GCTI-SN: geometry-inspired chemical and tissue invariant stain normalization of microscopic medical images. Medical Image Analysis. 2020 Oct 1;65:101788.
  • Sareen E, Singh L, Varkey B, Achary K, Gupta A. EEG dataset of individuals with intellectual and developmental disorder and healthy controls under rest and music stimuli. Data in Brief. 2020 Apr 7:105488.
  • Sharma A, Anand S, Kaul SK. Intelligent Querying for Target Tracking in Camera Networks using Deep Q-Learning with n-Step Bootstrapping. arXiv preprint arXiv:2004.09632. 2020 Apr 20.
  • Jerripothula KR, Rai A, Garg K, Rautela YS. Feature-level rating system using customer reviews and review votes. IEEE Transactions on Computational Social Systems. 2020 Jul 31;7(5):1210-9.
  • Ramneek Kaur, Vikram Goyal, Venkata M. V. Gunturi, Finding The Most Navigable Path in Road Networks, accepted in Springer journal of GeoInformatica, 2020.
  • Amit Verma, Siddharth Dawar, Raman Kumar, Shamkant Navathe, Vikram Goyal, High Utility and Diverse Itemset Mining, accepted in Springer Journal of Applied Intelligence, 2020.
  • Dawman L, Mukherjee A, Sethi T, Agrawal A, Kabra SK, Lodha R. Role of impulse oscillometry in assessing asthma control in children. Indian Pediatrics. 2020 Feb;57(2):119-23.
  • Conferences

  • Shubham Goswami, Suril Mehta, Dhruv Sahrawat, Anubha Gupta, Ritu and Gupta, “Heterogeneity Loss to Handle Intersubject and Intrasubject Variability in Cancer,” ICLR workshop on Affordable AI in healthcare, 2020.
  • Neha Jain, Navneet Anand Sah, Vivek Ashok Bohara and Anubha Gupta, "Experimental Results for Energy Harvesting by exploiting inherent inadequacies of Sampling process for IoT application", IEEE International Conference on Communications (ICC), Workshop, 2020.
  • Mansi Saxena, Ekansh Sareen and Anubha Gupta, "Understanding Functional Brain Activation using Source Localization of EEG Signals in Motor Imagery Tasks," IEEE 12th International Conference on Communication Systems and Networks, 2020. (This paper also won the "Best Paper Award". )
  • Yaman Kumar, Dhruva Sahrawat, Shubham Maheshwari, Debanjan Mahata, Amanda Stent, Yifang Yin, Rajiv Ratn Shah, Roger Zimmermann, “Harnessing GANs for Zero-shot Learning of New Classes in Visual Speech Recognition.” In AAAI, 2020.
  • Syesha Girdher, Anubha Gupta, Snehlata Jaswal and Vinayak Naik, "Predicting Human Response in Feature Binding Experiment Using EEG Data," IEEE 12th International Conference on Communication Systems and Networks, 2020.
  • Ankur Pandey, Saru Brar, Inshita Mutreja, and Pushpendra Singh, “Exploring Automated Q&A Support System for Maternal and Child Health in Rural India”, Accepted to be published as a poster (2 pages) in Proceedings of the 3rd ACM SIGCAS Conference on Computing and Sustainable Societies, ACM COMPASS’ 2020.
  • S. K. Kaul and R. D. Yates, "Timely Updates By Multiple Sources: The M/M/1 Queue Revisited," 54th Annual Conference on Information Sciences and Systems (CISS), 2020.
  • Ashutosh Vaish, Anubha Gupta and Ajit Rajwade, "MSR-HARDI: Accelerated Reconstruction of HARDI using Multiple Sparsity Regularizers", IEEE International Conference on Image Processing (ICIP), 2020.
  • Shiv Gehlot, Anubha Gupta and Ritu Gupta, "EDNFC-Net: Convolutional Neural Network with Nested Feature Concatenation for Nuclei-Instance Segmentation," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020.
  • S. Agarwal, H. Arora, S. Anand, C. Arora, "Contextual Diversity for Active Learning", European Conference on Computer Vision (ECCV), 2020.
  • L. Tiwari, P. Ji, Q. Tran, B. Zhuang, S. Anand, M. Chandraker, "Pseudo RGB-D for Self-Improving Monocular SLAM and Depth Prediction", accepted, European Conference on Computer Vision (ECCV), 2020.
  • Aman Roy, Vinayak Kumar, Debdoot Mukherjee, Tanmoy Chakraborty. Learning Multigraph Node Embeddings Using Guided Levy Flights, Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2020. (Core A)
  • E. Kurnat-Thoma, …, T. Sethi, et. al, “Recent Advances in Systems and Network Medicine: Meeting Report from the First International Conference in Systems and Network Medicine,” Systems Medicine, 2020.
  • Piyush Gupta, Nikita Mehrotra, and Rahul Purandare. "JCoffee: Using Compiler Feedback to Make Partial Code Snippets Compilable." In Proceedings of the 36th IEEE International Conference on Software Maintenance and Evolution (ICSME), Tools Demo Track, 2020.
  • E. Bondi, R. Jain, P. Aggrawal, S. Anand, R. Hannaford, A. Kapoor, J. Piavis, S. Shah, L. Joppa, B. Dilkina and M. Tambe, "BIRDSAI: A Dataset for Detection and Tracking in Aerial Thermal Infrared Videos", IEEE Winter Conference on Computer Vision (WACV), 2020.
  • Dattatreya Mohapatra, Siddharth Pal, Soham De, Ponnurangam Kumaraguru, Tanmoy Chakraborty, Modeling Citation Trajectories of Scientific Papers, Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2020. (Core A)
  • Gunjan Singh, Sumit Bhatia, Raghava Mutharaju. "OWL2Bench: A Benchmark for OWL 2 Reasoners", 19th International Semantic Web Conference (ISWC), 2020.
  • A. Sharma, G. Gupta, Ranjitha Prasad, A. Chatterjee, L. Vig, and G. Shroff, “Hi-CI: Deep Causal Inference in High Dimensions”, ACM SIGKDD Causal Discovery 2020 (PMLR).
  • G. Singh, S. Bhatia, and R. Mutharaju, “A Benchmark for OWL 2 DL Reasoners,” 7th ACM IKDD CoDS and 25th COMAD (CoDS-COMAD), 2020,
  • M. Jain, P. Mirza, and R. Mutharaju, “Cardinality Extraction from Text for Ontology Learning,” 7th ACM IKDD CoDS and 25th COMAD (CoDSCOMAD), 2020.
  • Shrinidhi Hegde, Ranjitha Prasad, Ramya Hebbalaguppe, Vishwajeet Kumar, “Variational Student: Learning Compact and Sparser networks in the Knowledge Distillation Framework”,EEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020.
  • A. Sharma, G. Gupta, Ranjitha Prasad, A. Chatterjee, L. Vig, and G. Shroff, ‘MultiMBNN:Matched and Balanced Causal Inference with Neural Networks”, ESANN, 2020
  • Sachin K, G. Gupta, Ranjitha Prasad, A. Chatterjee, L. Vig, and G. Shroff, "CAMTA: Causal Attention Model for Multi-touch Attribution", DMS Workshop, In the 20th IEEE International Conference on Data Mining (ICDM), 2020.
  • Daksh Goyal, Koteswar Rao Jerripothula, and Ankush Mittal, "Detection of Gait Abnormalities caused by Neurological Disorders," in IEEE Workshop on Multimedia Signal Processing (MMSP), 2020.
  • Rupam Patir, Shubham Singhal, C. Anantram, Vikram Goyal, Interpretability of Blackbox ML Models through data-view Extraction and Shadow Model creation, In 27th International Conference on Neural Information Processing (ICONIP), 2020.

2019

  • Journals
  • Majumdar A, Gupta M. Recurrent transform learning. Neural Networks. 2019 Oct 1;118:271-9.
  • Kalra S, Mittal A, Gupta K, Singhal V, Gupta A, Mishra T, Naidu S, Sengupta D*, and Ahuja, G*, Integrative analysis of single-cell transcriptomes links cellular enrichment of olfactory receptors with cancer cell differentiation and molecular prognosis. Communications Biology.
  • Sinha D, Sinha P, Saha R, Bandyopadhyay S, Sengupta D. Improved dropClust R package with integrative analysis support for scRNA-seq data.
  • Goswami C, Poonia S, Sengupta D, Kumar L. Staging System to predict the risk of relapse in Multiple Myeloma patients undergoing autologous stem cell transplantation. Frontiers in oncology. 2019;9:633.
  • Mukherjee M, Naqvi SA, Verma A, Sengupta D, Parnami A. MenstruLoss: Sensor For Menstrual Blood Loss Monitoring. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 2019 Jun 21;3(2):1-21.
  • Poonia S, Chawla S, Kaushik S, Sengupta D. Pathway Informatics, 2019
  • Aggarwal P, Gupta A. Group-fused multivariate regression modeling for group-level brain networks. Neurocomputing. 2019 Oct 21;363:140-8.
  • Aggarwal P, Gupta A. Multivariate graph learning for detecting aberrant connectivity of dynamic brain networks in autism. Medical image analysis. 2019 Aug 1;56:11-25.
  • Ansari N, Sen Gupta A, Gupta A. Shallow water channel estimation with energy efficient transmitted signal design. The Journal of the Acoustical Society of America. 2019 May 16;145(5):2955-70.
  • Panwar S, Joshi SD, Gupta A, Agarwal P. Automated Epilepsy Diagnosis Using EEG With Test Set Evaluation. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2019 May 3;27(6):1106-16.
  • Bhavan A, Chauhan P, Shah RR. Bagged support vector machines for emotion recognition from speech. Knowledge-Based Systems. 2019 Nov 15;184:104886.
  • Dutta HS, Chakraborty T. Blackmarket-Driven Collusion Among Retweeters–Analysis, Detection, and Characterization. IEEE Transactions on Information Forensics and Security. 2019 Nov 13;15:1935-44.
  • Thukral D, Pandey A, Gupta R, Goyal V, Chakraborty T. DiffQue: Estimating Relative Difficulty of Questions in Community Question Answering Services. ACM Transactions on Intelligent Systems and Technology (TIST). 2019 Jul 24;10(4):1-27.
  • Cui Z, Park N, Chakraborty T. Incremental community discovery via latent network representation and probabilistic inference. Knowledge and Information Systems. 2019 Nov 15:1-20.
  • Solomon RS, Srinivas PY, Das A, Gamback B, Chakraborty T. Understanding the psycho-sociological facets of homophily in social network communities. IEEE Computational Intelligence Magazine. 2019 May 6;14(2):28-40.
  • A. Agarwal, R. Keshari, M. Wadhwa, M. Vijh, C. Parmar, R. Singh, M. Vatsa, Iris sensor identification in multi-camera environment, Information Fusion, Volume 45, pp. 333-345, 2019.
  • T. Chakraborty, S. Ghosh, N. Park, Ensemble-based overlapping community detection using disjoint community structures, Knowledge-Based Systems, Volume 163, pp. 241-251, 2019.
  • J. Maggu, H. K. Aggarwal, A. Majumdar, Label-Consistent Transform Learning for Hyperspectral Image Classification, IEEE Geoscience and Remote Sensing Letters, 2019.
  • M. Singh, R. Singh, M. Vatsa, N. Ratha, R. Chellappa, Recognizing Disguised Faces in the Wild, IEEE Transactions on Biometrics, Behavior, and Identity Science, 2019.
  • G. Goswami, A. Agarwal, N. Ratha, R. Singh, M. Vatsa, Detecting and Mitigating Adversarial Perturbations for Robust Face Recognition, In International Journal of Computer Vision (IJCV), Special Issue on Deep Learning for Face Analysis, 2019.
  • N. Kohli, D. Yadav, M. Vatsa, R. Singh, A. Noore, Supervised Mixed Norm Autoencoder for Kinship Verification in Unconstrained Videos, IEEE Transactions on Image Processing, Volume 28, No. 3, pp. 1329-1341, 2019.
  • M. Singh, R. Singh, A. Ross, A Comprehensive Overview of Biometric Fusion, Information Fusion, Volume 52, pp. 187-205, 2019.
  •  
  • Conferences
  • V. Singhal, A. Majumdar, M. Vatsa and R. Singh, “Siamese Deep Dictionary Learning”, IEEE International Joint Conference on Neural Networks (IJCNN), 2019 (CORE A; Oral).
  • V. Singhal and A. Majumdar, “Age and Gender Estimation via Deep Dictionary Learning Regression”, IEEE International Joint Conference on Neural Networks (IJCNN), 2019 (CORE A; Oral).
  • J. Maggu and A. Majumdar, “Supervised Kernel Transform Learning”, IEEE International Joint Conference on Neural Networks (IJCNN), 2019 (CORE A; Oral).
  • Mongia, V. Jain, E. Chouzenoux and A. Majumdar, “Deep Latent Factor Model for Predicting Drug Target Interactions”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019 (Poster).
  • S. Singh, S. Verma and A. Majumdar, “Multi Label Restricted Boltzmann Machine for Non-Intrusive Load Monitoring”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 8345-8349, 2019 (Oral).
  • Mukherjee, M., Naqvi, S. A., Verma, A., Sengupta, D., & Parnami, A, MenstruLoss: Sensor For Menstrual Blood Loss Monitoring. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2019.
  • Garvita Bajaj and Pushpendra Singh, “Evaluating the Impact of Battery Usage Patterns on Performance of Task Allocation Algorithms in Sparse Mobile Crowdsensing”, The 22nd ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, (ACM MSWIM), 2019. (CORE RANK A).
  • Yifang Yin, Meng-Jiun Chiou, Zhenguang Liu, Harsh Shrivastava, Rajiv Ratn Shah and Roger Zimmermann, “Multi-Level Fusion based Class-aware Attention Model for Weakly Labeled Audio Tagging.” In ACM Multimedia. 2019.
  • Harsh Shrivastava, Rama Krishna P V N S, Karmanya Aggarwal, Meghna P Ayyar, Yifang Yin, Rajiv Ratn Shah, Roger Zimmermann, “Robust and Scalable Face Retrieval Framework for Large-scale Databases.” In IEEE BigMM, 2019.
  • Sharan Pai, Nikhil Sachdeva, Rajiv Ratn Shah, Roger Zimmermann, “User Input based Style Transfer while Retaining Facial Attributes.” In IEEE BigMM, 2019.
  • Maitree Leekha, Mononito Goswami, Yifang Yin, Rajiv Ratn Shah, Roger Zimmermann, “Are you paying attention? Detecting Distracted Driving in Real-time.” In IEEE BigMM, 2019.
  • Shivangi Singhal, Rajiv Shah, Tanmoy Chakraborty, Ponnurangam Kumaraguru, Shin’ichi Satoh, “SPOTFAKE: A Multimodal Framework for Fake News Detection.” In IEEE BigMM, 2019.
  • Osaid Rehman Nasir, Shailesh Kumar Jha, Manraj Singh Grover, Yi Yu, Ajit Kumar, Rajiv Ratn Shah, “Text2FaceGAN: Face Generation from Fine Grained Textual Descriptions.” In IEEE BigMM, 2019.
  • Himanshu Aggarwal, Rajiv Ratn Shah, Suhua Tang, Feida Zhu, “Supervised Generative Adversarial Cross-modal Hashing by Transferring Pairwise Similarities for Venue Discovery.” In IEEE BigMM, 2019.
  • D. Sondhi and R. Purandare. “SEGATE: Unveiling Semantic Inconsistencies between Code and Specification of String Inputs.” In Proceedings of the 34th ACM/IEEE International Conference on Automated Software Engineering (ASE), 2019.
  • Shukla, S. Uppal, S. Bhagat, S. Anand and P. Turaga, "PrOSe: Product of Orthogonal Spheres Parameterization for Disentangled Representation Learning", 30th British Machine Vision Conference (BMVC) 2019.
  • Shukla, G. S. Cheema S. Anand, Q. N. Qureshi, and Y. V. Jhala, "Primate Face Identification in the Wild", Pacific-Rim International Conference on Artificial Intelligence (PRICAI), 2019.
  • Sharma, S. Anand and S. K. Kaul, "Reinforcement Learning Based Querying in Camera Networks for Efficient Target Tracking", International Conference on Automated Planning and Scheduling (ICAPS) 2019.
  • S. Gopal, S. K. Kaul and R. Chaturvedi, "Coexistence of Age and Throughput Optimizing Networks: A Game Theoretic Approach," IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2019.
  • T. Shreedhar, S. K. Kaul and R. D. Yates, "An Age Control Transport Protocol for Delivering Fresh Updates in the Internet-of-Things," IEEE 20th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM), 2019.
  • S. Banik, S. K. Kaul and P. B. Sujit, "Minimizing Age in Gateway Based Update Systems," IEEE International Symposium on Information Theory (ISIT), 2019.
  • Sharma, A., Anand, S. and Kaul, S.K., “Reinforcement Learning Based Querying in Camera Networks for Efficient Target Tracking,” In Proceedings of the International Conference on Automated Planning and Scheduling, 2019.
  • Subhabrata Dutta, Dipankar Das, Tanmoy Chakraborty. Modeling Engagement Dynamics of Online Discussions using Relativistic Gravitational Theory, 19th IEEE International Conference on Data Mining (ICDM), 2019. (Core A*).
  • Subhabrata Dutta, Gunkirat Kaur, Shreyans Mongia, Arpan Mukherjee, Dipankar Das, Tanmoy Chakraborty. Into the Battlefield: Quantifying and Modeling Intra-community Conflicts in Online Discussion, 28th ACM International Conference on Information and Knowledge Management (CIKM), 2019. (Core A)
  • Shartika Dhawan, Siva Charan Reddy Gangireddy, Shiv Kumar, Tanmoy Chakraborty. Spotting Collective Behaviour of Online Frauds in Customer Reviews, International Joint Conference on Artificial Intelligence (IJCAI), 2019. (Core A*)
  • Harish Fulara, Gursimran Singh, Dheryta Jaisinghani, Mukulika Maity, Tanmoy Chakraborty, Vinayak Naik, “Use of Machine Learning to Detect Causes of Unnecessary Active Scanning in WiFi Networks,” 20th IEEE International Symposium on a World of Wireless, Mobile and Multimedia (IEEE WoWMoM), 2019. (Core A)
  • Dattatreya Mohapatra, Abhishek Maiti, Sumit Bhatia, Tanmoy Chakraborty, “Go Wide, Go Deep: Quantifying the Impact of Scientific Papers through Influence Dispersion Trees,” ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL), 2019. (Core A*) (Best student paper award)
  • T. Sethi*, S. Maheshwari, A. Mittal, S. Chugh, “Learning to Address Health Inequality in the United States with a Bayesian Decision Network”, Proceedings of the AAAI Conference on Artificial Intelligence, 2019. *Corresponding author
  • M. A. Yasvi, and R. Mutharaju, “ODPReco – A Tool to Recommend Ontology Design Patterns,” 10th Workshop on Ontology Design and Patterns (WOP), co-located with the 18th International Semantic Web Conference (ISWC), 2019.
  • R. K. Yadav, G. Singh, R. Mutharaju, and S. Bhatia, “Towards a Concurrent Approximate Description Logic Reasoner,” Poster & Demo track, 18th International Semantic Web Conference (ISWC), 2019. (Nominated for the best poster award).
  • S. Chhabra, P. Majumdar, M. Vatsa, R. Singh, Data Fine-tuning, In Proceedings of AAAI Conference on Artificial Intelligence, 2019.
  • R. Keshari, M. Vatsa, and R. Singh, Guided Dropout, In Proceedings of AAAI Conference on Artificial Intelligence, 2019.
  • T. Chowdhury, T. Chakraborty, CQASUMM: Building References for Community Question Answering Summarization Corpora, In Proceedings of the ACM India Joint International Conference on Data Science and Management of Data, 2019.
  • J. Maggu and A. Majumdar, Supervised Kernel Transform Learning, In IEEE International Joint Conference on Neural Networks (IJCNN), 2019.
  • S. Ghosh, R. Singh, M. Vatsa, On Learning Density Aware Embeddings, IEEE Conference on Computer Vision and Pattern Recognition , 2019.
  • S. Gupta, N. Gupta, S. Ghosh, M. Singh, S. Nagpal, R. Singh, M. Vatsa, FaceSurv: A Benchmark Video Dataset for Face Detection and Recognition Across Spectra and Resolutions, IEEE International Conference on Automatic Face and Gesture Recognition, 2019.
  • I. Kalra, M. Singh, S. Nagpal, R. Singh, M. Vatsa, DroneSURF: Benchmark Dataset for Drone-based Face Recognition, IEEE International Conference on Automatic Face and Gesture Recognition, 2019.
  • S. Mehta, A. Uberoi, A. Agarwal, M. Vatsa, R. Singh, Crafting A Panoptic Face Presentation Attack Detector, IAPR International Conference On Biometrics, 2019.
  • A. Agarwal, A. Sehwag, M. Vatsa, R. Singh, Deceiving the Protector: Fooling Face Presentation Attack Detection Algorithms, IAPR International Conference On Biometrics, 2019.
  • Ramya Y. S., S. Ghosh, M. Vatsa, R. Singh, Face Sketch Image Colorization via Supervised GANs, IAPR International Conference On Biometrics, 2019.
  •  
  • 2018

    •  
    • Journals
    • T. Chakraborty, Role of Interdisciplinarity in Computer Sciences: Quantification, Impact and Life Trajectory, Scientometrics, Volume 114, No. 3, pp. 1011-1029, 2018.
    • M. Thammawichai, P.B. Sujit, E.C. Kerrigan, J.B. Sousa, Optimizing communication and computation for multi-UAV information gathering applications, IEEE Transactions on Aerospace Electronic Systems, Volume 54, No. 2, pp. 601-615, 2018.
    • V. Singhal, A. Majumdar, Majorization Minimization Technique for Optimally Solving Deep Dictionary Learning, Neural Processing Letters, Volume 47, No. 3, pp. 799-814, 2018.
    • T. I. Dhamecha, M. Shah, P. Verma, M.Vatsa, R.Singh, CrowdFaceDB: Database and benchmarking for face verification in crowd, Pattern Recognition Letters, Volume 107, pp. 17-24, 2018.
    • M. Singh, S. Nagpal, M. Vatsa, R. Singh, Are you eligible? Predicting adulthood from face images via class specific mean autoencoder, Pattern Recognition Letters, 2018.
    • A. Sethi, M. Singh, R. Singh, M. Vatsa, Residual Codean Autoencoder for Facial Attribute Analysis, Pattern Recognition Letters, 2018.
    • D. John Lewis, V. Singhal, A. Majumdar, Solving Inverse Problems in Imaging via Deep Dictionary Learning, IEEE Access, 2018.
    • S. Singh, A. Majumdar, Deep sparse coding for non–intrusive load monitoring, IEEE Transactions on Smart Grid, Volume 9, No. 5, pp. 4669-4678, 2018.
    • V. Singhal, J. Maggu, A. Majumdar, Simultaneous Detection of Multiple Appliances from Smart-meter Measurements via Multi-Label Consistent Deep Dictionary Learning and Deep Transform Learning, IEEE Transactions on Smart Grid, 2018.
    • S. Gopal, S. K. Kaul, S. Roy, Optimizing city-wide White-Fi networks in TV white spaces, IEEE Transactions on Cognitive Communications and Networking, Volume 4, No. 4, pp. 749-763, 2018.
    • R. D. Yates, S. K. Kaul, The age of information: Real-time status updating by multiple sources, IEEE Transactions on Information Theory, 2018.
    • A. Majumdar, Graph structured autoencoder, Neural Networks, Volume 106, pp. 271-280, 2018.
    •  
    • Conferences
    • Garvita Allabadi, Aritra Dhar, Ambreen Bashir, Rahul Purandare, METIS: Resource and Context-Aware Monitoring of Finite State Properties. Runtime Verification (RV), 167-186, 2018.
    • A. Jain, R. Singh, M. Vatsa, On Detecting Synthetic Alterations using GANs and Retouching, In Proceedings of IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), 2018.
    • S. Suri, A. Sankaran, M. Vatsa, R. Singh, On Matching Faces with Alterations due to Plastic Surgery and Disguise, In Proceedings of IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), 2018.
    • R. Garg, Y. Baweja, S. Ghosh, M. Vatsa, R. Singh, N. Ratha, Heterogeneity Aware Deep Embedding for Mobile Periocular Recognition, In Proceedings of IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), 2018.
    • A. Goel, A. Singh, A. Agarwal, M. Vatsa, R. Singh, Smartbox: Benchmarking adversarial detection and mitigation algorithms for face recognition, IEEE International Conference on Biometrics: Theory, Applications, and Systems (BTAS), 2018.
    • A. Agarwal, R. Singh, M. Vatsa, N. Ratha, Are imageagnostic universal adversarial perturbations for face recognition difficult to detect, IEEE International Conference on Biometrics: Theory, Applications, and Systems (BTAS), 2018.
    • V. Kushwaha, M. Singh, R. Singh, M. Vatsa, N. Ratha, R. Chellappa, Disguised Faces in the Wild, IEEE International Conference on Computer Vision and Pattern Recognition Workshop on Disguised Faces in the Wild, 2018.
    • S. Siddiqui, M. Vatsa, R. Singh, Face Recognition for Newborns, Toddlers, and Pre-School Children: A Deep Learning Approach, In 24th International Conference on Pattern Recognition (ICPR), 2018.
    • D. Khanna, S. Sharma, C. Rodríguez, R. Purandare, Dynamic Symbolic Verification of MPI Programs, In International Symposium on Formal Methods, Springer, Cham, 2018.
    • D. Yadav, N. Kohli, E. Kalsi, M. Vatsa, R. Singh, A. Noore, Unraveling Human Perception of Facial Aging using Eye Gaze, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018.
    • R. Keshari, M. Vatsa, R. Singh, A. Noore, Learning Structure and Strength of CNN Filters for Small Sample Size Training, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018.
    • M. Singh, S. Nagpal, M. Vatsa, R. Singh, A. Majumdar, Identity Aware Synthesis for Cross Resolution Face Recognition, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018.
    • A. Malhotra, R. Singh, M. Vatsa, V. M. Patel, Person Authentication using Head Images, In IEEE Winter Conference on Applications of Computer Vision (WACV), 2018.
    • L. Tiwari, S. Anand, DGSAC: Density Guided Sampling and Consensus, In IEEE Winter Conference on Applications of Computer Vision (WACV), 2018.
    • A. Sobti, C. Arora, M. Balakrishnan, Object Detection in Real-Time Systems: Going Beyond Precision, IEEE Winter Conference on Applications of Computer Vision (WACV), 2018.
    • S. Patra, P. Maheshwari, S. Yadav, S. Banerjee, C. Arora. A Joint 3D-2D based Method for Free Space Detection on Roads, IEEE Winter Conference on Applications of Computer Vision (WACV), 2018.
    • D. Khandelwal, C. Arora, and P. Singla. Learning Higher Order Potentials For MRFs, IEEE Winter Conference on Applications of Computer Vision (WACV), 2018.
    • C. Arora, V. Kwatra. Stabilizing First Person 360 Degree Videos, IEEE Winter Conference on Applications of Computer Vision (WACV), 2018.
    • S. Chhabra, R. Singh, M. Vatsa, G. Gupta, Anonymizing k-Facial Attributes via Adversarial Perturbations, In proceedings of International Joint Conference on Artificial Intelligence (IJCAI), 2018.
    • S. Chopra, A. Malhotra, M. Vatsa, R. Singh, Unconstrained Fingerphoto Database, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018.
    • P. Majumdar, S. Chhabra, R. Singh, M. Vatsa, On Detecting Domestic Abuse via Faces, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018.
    • S. Sinha, M. Agarwal, M. Vatsa, R. Singh, S. Anand, Exploring Bias in Primate Face Detection and Recognition, In Proceedings of European Conference on Computer Vision Workshop on Bias Estimation in Face Analytics, 2018.
    • H. S. Dutta, A. Chetan, B. Joshi, T. Chakraborty, Retweet us, we will retweet you: Spotting collusive retweeters involved in blackmarket services, In IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2018.
    • M. Gupta, A Majumdar, Robust Supervised Sparse Coding for Non-Intrusive Load Monitoring, In IEEE International Joint Conference on Neural Networks (IJCNN), 2018.
    • S. Maheshwari, A. Majumdar, Hierarchical Autoencoder for Collaborative Filtering, In IEEE International Joint Conference on Neural Networks (IJCNN), 2018.
    • S. Jain, A. Majumdar, Doubly Label Consistent Autoencoder: Accounting User and Item Metadata in Recommender Systems, In IEEE International Joint Conference on Neural Networks (IJCNN), 2018.
    • V. Singhal, A. Majumdar, Supervised Deep Dictionary Learning for Single Label and Multi-Label Classification, In IEEE International Joint Conference on Neural Networks (IJCNN), 2018.
    • S. K. Kaul, R. D. Yates, R. D, Age of information: Updates with priority, In IEEE International Symposium on Information Theory (ISIT), 2018.
    • S. Gopal, S. K. Kaul, A game theoretic approach to DSRC and WiFi coexistence, In IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 2018.
    • T. Shreedhar, S. K. Kaul, R. D. Yates, ACP: Age Control Protocol for Minimizing Age of Information over the Internet, In Proceedings of the 24th ACM Annual International Conference on Mobile Computing and Networking (MobiCom), 2018.
    • M. K. Pal, R. Bhati, A. Sharma, A., S. K. Kaul, S. Anand, P. B. Sujit, A Reinforcement Learning Approach to Jointly Adapt Vehicular Communications and Planning for Optimized Driving, In IEEE 21st International Conference on Intelligent Transportation Systems (ITSC), 2018.
    • S. Sikdar, T.Chakraborty, S. Sarkar, N. Ganguly, A. Mukherjee. ComPAS: Community Preserving Sampling for Streaming Graphs, International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2018.
    • S. Gupta, A. Khattar, A. Gogia, P. Kumaraguru and T. Chakraborty, Collective Classification of Spam Campaigners on Twitter: A Hierarchical Meta-Path Based Approach, In Proceedings of the World Wide Web Conference on World Wide Web, 2018.
    • P.B. Sujit, UAV coalition formation with increased decision-making autonomy, AIAA Information Systems-AIAA Infotech @ Aerospace, AIAA SciTech and Technology Forum and Exposition, 2018.
    • H. Rashid, P. Singh, Monitor: An abnormality detection approach in buildings energy consumption, In IEEE 4th International Conference on Collaboration and Internet Computing (CIC) 2018.
    •  
    • Technical Reports
    • M. Singh, S. Nagpal, M. Vatsa, R. Singh, A. Noore, Supervised COSMOS Autoencoder: Learning Beyond the Euclidean Loss, arXiv preprint arXiv:1810.06221, 2018.
    • M. Singh, S. Nagpal, R. Singh, M.Vatsa, A. Noore, Learning A Shared Transform Model for Skull to Digital Face Image Matching, arXiv preprint arXiv:1808.04571, 2018.
    • G. Goswami, N. Ratha, A. Agarwal, R. Singh, M. Vatsa, Unravelling robustness of deep learning based face recognition against adversarial attacks, arXiv preprint arXiv:1803.00401, 2018.
    • A. Tripathi, A. Mohan, S. Anand, and M. Singh, Adversarial Learning of Raw Speech Features for Domain Invariant Speech Recognition, arXiv preprint arXiv:1805.08615, 2018.
    • D. Gupta, T. Chakraborty, S. Chakrabarti, GIRNet: Interleaved Multi-Task Recurrent State Sequence Models, arXiv preprint arXiv:1811.11456, 2018.
    • J. Chakraborty, D. Pradhan, H. S. Dutta, S. Nandi, T. Chakraborty, On Good and Bad Intentions behind Anomalous Citation Patterns among Journals in Computer Sciences, arXiv preprint arXiv:1807.10804, 2018.
    • T. Shreedhar, N. Mohan, S. K. Kaul, J. Kangasharju, QAware: A Cross-Layer Approach to MPTCP Scheduling, arXiv preprint arXiv:1808.04390, 2018.
    • R Chaturvedi, S Gopal, SK Kaul, Welfare Analysis of Network Neutrality Regulation, arXiv preprint arXiv:1811.10094, 2018.
    • A. Sharma, P. Kumar, S. Anand, S. K. Kaul, A Reinforcement Learning Approach to Target Tracking in a Camera Network. arXiv preprint arXiv:1807.10336, 2018.
    • D. Jaisinghani, V. Naik, S. K. Kaul, R. Balan, S. Roy, Improving the Performance of WLANs by Reducing Unnecessary Active Scans, arXiv preprint arXiv:1807.05523, 2018.
    • T. Shreedhar, S. K. Kaul, R. D. Yates, ACP: An end-to-end transport protocol for delivering fresh updates in the Internet-of-Things, arXiv preprint arXiv:1811.03353, 2018.
    •  

    2017

    •  
    • Journals
    • I. Manjani, S. Tariyal, M. Vatsa, R. Singh, A. Majumdar, Detecting silicone mask-based presentation attack via deep dictionary learning, IEEE Transactions on Information Forensics and Security, Volume 12, No. 7, pp. 1713-1723, 2017.
    • G. Goswami, M. Vatsa, and R. Singh, Face Verification via Learned Representation on Feature-Rich Video Frames, IEEE Transactions on Information Forensics and Security, Volume 12, No. 7, pp. 1686-1698, 2017.
    • S. Dawar, V. Goyal, D. Bera, A hybrid framework for mining high-utility itemsets in a sparse transaction database, Applied Intelligence, Volume 47, No. 3, pp. 809-827, 2017.
    • S. Dawar, V. Sharma,V. Goyal, Mining top-k high-utility itemsets from a data stream under sliding window model, Applied Intelligence, Volume 47, No. 4, pp. 1240-1255, 2017.
    • V. M. V. Gunturi, S. Shekhar, K. Joseph, K. M. Carley, Scalable computational techniques for centrality metrics on temporally detailed social network, Machine Learning, Volume 106, No. 8, pp. 1133-1169, 2017.
    •  
    • Conferences
    • P. Basak, S. De, M. Agarwal, A. Malhotra, M. Vatsa, R. Singh, Multimodal biometric recognition for toddlers and pre-school children, In IEEE International Joint Conference on Biometrics (IJCB), 2017.
    • M. Singh, S. Nagpal, M. Vatsa, R. Singh, A.Noore, A. Majumdar, Gender and ethnicity classification of Iris images using deep class-encoder, In IEEE International Joint Conference Biometrics (IJCB), 2017.
    • S. Nagpal, M. Singh, A. Jain, R. Singh, M. Vatsa, and A. Noore, On Matching Skulls to Digital Face Images: A Preliminary Approach, In Proceedings of IEEE International Joint Conference on Biometrics (IJCB), 2017.
    • V. Vinayakarao, A. Sarma, R. Purandare, S. Jain, S. Jain, Anne: Improving source code search using entity retrieval approach, In ACM International Conference on Web Search and Data Mining (WSDM), 2017.
    • R. Tiwari, P. Jain, S. Butail, S. P. Baliyarasimhuni, M. A. Goodrich, Effect of leader placement on robotic swarm control, In Proceedings of the 16th Conference on Autonomous Agents and Multi-agent Systems (AAMAS), 2017.
    • G. Goswami, R. Singh, M. Vatsa, A. Majumdar, Kernel group sparse representation based classifier for multimodal biometrics, In IEEE International Joint Conference Neural Networks (IJCNN), 2017.
    • V. Singhal, A. Majumdar, Noisy Deep Dictionary Learning: Application to Alzheimer's Disease Classification, In IEEE International Joint Conference on Neural Networks (IJCNN), 2017.
    • V. Singhal, P. Khurana, A. Majumdar, Class-wise Deep Dictionary Learning, In IEEE International Joint Conference on Neural Networks (IJCNN), 2017.
    • A. Tripathi, A. Majumdar, Asymmetric Stacked Autoencoder, In International Joint Conference on Neural Networks (IJCNN), 2017.
    • M. Singh, S. Nagpal, R. Singh and M. Vatsa, Class Representative Autoencoder for Low Resolution Multi-Spectral Gender Classification, In International Joint Conference on Neural Networks (IJCNN), 2017.
    • R. D. Yates, S. K. Kaul, Status updates over unreliable multiaccess channels, In IEEE International Symposium on Information Theory (ISIT), 2017.
    • D. Jaisinghani, V. Naik, S. K. Kaul, S. Roy, Sniffer-based inference of the causes of active scanning in WiFi networks, In IEEE 23rd National Conference on Communications (NCC), 2017.
    • S. Nagpal, M. Singh, R. Singh, M. Vatsa, A. Noore, and A. Majumdar, Face Sketch Matching via Coupled Deep Transform Learning, In IEEE International Conference on Computer Vision, 2017.
    • P. Maini, S. Rathinam, P. B. Sujit, Curvature Constrained Trajectory Planning for a UAV through a Sequence of Points: A Perturbation Approach, 11th Asian Control Conference (ASCC), 2017.
    • G. Bajaj, P. Singh, Mew: A Plug-n-Play Framework for Task Allocation in Mobile Crowdsensing, In Proceedings of the 1st ACM Workshop on Mobile Crowdsensing Systems and Applications, 2017.
    • H. Rashid, P. Singh, Poster: Energy Disaggregation for identifying anomalous appliance, In Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments, 2017.
    • H. Rashid, P. Singh, K. Ramamritham, Revisiting selection of residential consumers for demand response programs, In Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments, 2017.
    • H. Rashid, P. M. Mammen, S. Singh, K. Ramamritham, P. Singh, P. Shenoy, Want to reduce Energy Consumption? Don’t depend on the Customers!, In Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments, 2017.
    • B. Bhatnagar, S. Singh, C. Arora, C.V. Jawahar, Unsupervised Learning of Deep Feature Representation for Clustering Egocentric Actions, International Joint Conference on Artificial Intelligence (IJCAI), 2017.
    • A. Gautam, P.B Sujit, S. Saripalli, Autonomous Quadrotor Landing Using Vision and Pursuit Guidance, 20th IFAC World Congress, 2017.
    • H. Oliveira, P.B. Sujit, J.B. Sousa, Robust detection and tracking of ground vehicles using UAV, AIAA Guidance, Navigation, and Control Conference, 2017.
    •  
    • Technical Reports
    • T. Shreedhar, N. Mohan, S. K. Kaul, J. Kangasharju, More Than The Sum Of Its Parts: Exploiting Cross-Layer and Joint-Flow Information in MPTCP, arXiv preprint arXiv:1711.07565, 2017.
    • V. Mittal, S. K. Kaul, S. Roy, Optimizing Networks for Internet Access Using Tethering, arXiv preprint arXiv:1709.00844, 2017.
    •  

    2016

    •  
    • Conferences
    • P. Agarwal, R. Verma, V. M. V. Gunturi, Discovering Spatial Regions of High Correlation, In 16th IEEE International Conference on Data Mining (ICDM), 2016.
    •  
    • Dissertations
    • V.Sharma, V. Goyal, Mining top-K high utility itemsets in streaming data: a comparative study, PhD diss., 2016.
    • S. Kochanthara, R. Purandare, REVERT: runtime verification for real-time systems, PhD diss., 2016.