Publications

  • Prakash SS, Mayo JP and Ray S† (2024) Dissociation of attentional state and behavioral outcome using local field potentials. eNeuro. 11(11): ENEURO.0327-24.2024
  • Kanth and Ray S† (2024) Gamma responses to colored natural stimuli can be predicted from local low-level stimulus features. eNeuro. 11(7): ENEURO.0417-23.2024
  • Gulati D and Ray S† (2024) Auditory and visual gratings elicit distinct gamma responses. eNeuro. 11(4): ENEURO.0116-24.2024
  • Das A, Nandi N and Ray S† (2024) Alpha and SSVEP power outperforms Gamma power in capturing Attentional Modulation in Human EEG. Cerebral Cortex. 34(1), bhad412.
  • Cherian T & Arun SP (2024) What do we see behind an occluder? Amodal completion of statistical properties in complex objects, Attention Perception and Psychophysics, 86:2721–2739
  • Thoppe, G., Prashanth, L. A., & Bhat, S. P. (2024). Risk Estimation in a Markov Cost Process: Lower and Upper Bounds. In International Conference on Machine Learning (pp. 48124-48138). PMLR.
  • Eshwar, S. R., Felipe, L. L., Reiffers-Masson, A., Menasche, D. S., & Thoppe, G. (2024). Online Learning of Weakly Coupled MDP Policies for Load Balancing and Auto Scaling. In 2024 IFIP Networking Conference (IFIP Networking) (pp. 496-501). IEEE.
  • Ganesh, S., Chen, J., Thoppe, G., & Aggarwal, V. (2024) Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries. Transactions on Machine Learning Research.
  • Naskar, A., Thoppe, G., Koochakzadeh, A., & Gupta, V. (2024). Federated TD Learning in Heterogeneous Environments with Average Rewards: A Two-timescale Approach with Polyak-Ruppert Averaging. In IEEE 63rd Conference on Decision and Control (CDC) (pp. 387-393). IEEE.
  • Eshwar, S. R., Motwani, M., Roy, N., & Thoppe, G. (2024) Reinforcement Learning with Quasi-Hyperbolic Discounting. In IEEE 63rd Conference on Decision and Control (CDC) (pp. 387-393). IEEE.
  • Sengupta A, Banerjee S, Suhas G, Chandrasekaran AN & Sridharan D* (2024). The right posterior parietal cortex mediates spatial reorienting of attentional choice bias. Nature Communications, 15,6938.
  • Halder S, Raya DV & Sridharan D* (2024). Distinct neural bases of subcomponents of the attentional blink. eLife 13:RP97098.
  • Chandrasekaran AN, Vermani A, Gupta P, Steinmetz N, Moore T & Sridharan D* (2024). Dissociable components of attention exhibit distinct neuronal signatures in primate visual cortex. Science Advances 10, eadi0645.
  • Gupta P & Sridharan D* (2024). Presaccadic attention does not benefit the detection of changes in the visual field. PLOS Biology 22(1): e3002485.
  • Harshit Saurabh, Suparna Kundu, Samarth S T, Anupam Golder, KK Soundra Pandian, Chaoyun Li, Angshuman Karmakar, and Debayan Das. “Full Key Extraction of SNOW-V Using ML-assisted Power SCA.” IEEE Design & Test (2024).
  • Samarth S T, Harshit Saurabh, and Debayan Das. “TYLOR: TDC-based Low-Overhead Synthesizable Power SCA Countermeasure on FPGAs.” IEEE Design & Test (2024).
  • Harshit Saurabh, et al. “SNOW-SCA: ML-Assisted Side-Channel Attack on SNOW-V.” 2024 IEEE International Symposium on Hardware Oriented Security and Trust (HOST). IEEE, 2024.
  • Rastogi, S., Maini, P., & Pruthi, D. (2025). STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings. International Conference on Machine Learning (ICML 2025)
  • Bhagat, K., Vasisht, K. and Pruthi, D., 2024. Richer Output for Richer Countries: Uncovering Geographical Disparities in Generated Stories and Travel Recommendations. Findings of the Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL 2025)
  • Gupta, T. and Pruthi, D., 2025. All that glitters is not novel: Plagiarism in AI Generated Research. Association for Computational Linguistics (ACL 2025)
  • Sreebrata Goswami, R. Stanley Willaims and Sreetosh Goswami* (2023), Molecular Redox Computing Redux. Nature Materials, 2023. As the last and corresponding author.
  • Sruthi Gorantla, Anay Mehrotra, Amit Deshpande, Anand Louis (2023) “Sampling Individually Fair Rankings that are Always Group Fair.” AIES 2023
  • Sruthi Gorantla, Amit Deshpande, Anand Louis (2023) “Sampling Ex-Post Group-Fair Rankings.” IJCAI 2023
  • Sruthi Gorantla, Kishen N. Gowda, Amit Deshpande, Anand Louis (2023) “Socially Fair Center-Based and Linear Subspace Clustering.” ECML/PKDD 2023
  • Arindam Khan, Eklavya Sharma: (2023) Tight Approximation Algorithms for Geometric Bin Packing with Skewed Items. Algorithmica 85(9): 2735-2778 (2023)
  • Waldo Gálvez, Fabrizio Grandoni, Afrouz Jabal Ameli, Klaus Jansen, Arindam Khan, Malin Rau: (2023) A Tight (3/2+ε )-Approximation for Skewed Strip Packing. Algorithmica 85(10): 3088-3109 (2023)
  • Max A. Deppert, Klaus Jansen, Arindam Khan, Malin Rau, Malte Tutas: (2023) Peak Demand Minimization via Sliced Strip Packing. Algorithmica 85(12): 3649-3679 (2023)
  • Siddharth Barman, Arindam Khan, Sudarshan Shyam, K. V. N. Sreenivas: (2023) Finding Fair Allocations under Budget Constraints. AAAI 2023: 5481-5489
  • Siddharth Barman, Arindam Khan, Arnab Maiti, Ayush Sawarni: (2023) Fairness and Welfare Quantification for Regret in Multi-Armed Bandits. AAAI 2023: 6762-6769
  • Arindam Khan, Aditya Lonkar, Saladi Rahul, Aditya Subramanian, Andreas Wiese: (2023) Online and Dynamic Algorithms for Geometric Set Cover and Hitting Set. SoCG 2023: 46:1-46:17
  • Vishakha Patil, Vineet Nair, Ganesh Ghalme, Arindam Khan: (2023) Mitigating Disparity while Maximizing Reward: Tight Anytime Guarantee for Improving Bandits. IJCAI 2023: 4100-4108
  • Siddharth Barman, Arindam Khan, Sudarshan Shyam, K. V. N. Sreenivas: (2023) Guaranteeing Envy-Freeness under Generalized Assignment Constraints. EC 2023: 242-269
  • Ghanshyam Chandra, Chirag Jain. (2023) “Sequence to graph alignment using gap-sensitive co- linear chaining” International Conference on Research in Computational Molecular Biology. (RECOMB) 2023 https://doi.org/10.1007/978-3-031-29119-7_4
  • Chirag Jain. (2023) “Coverage-preserving sparsification of overlap graphs for long-read assembly” Bioinformatics 2023. https://doi.org/10.1093/bioinformatics/btad124
  • U. Banerjee, (2023) “Privacy-Preserving Edge Computing from Pairing-Based Inner Product Functional Encryption,” IEEE Global Communications Conference (GLOBECOM), pp. 2185-2190, December 2023
  • Fraiman, N., Mukherjee, S. and Thoppe, G., (2023) “The Shadow Knows: Empirical Distributions of Minimum Spanning Acycles and Persistence Diagrams of Random Complexes”, Discrete Analysis, 2023:2, 1-18
  • Ganesh, S., Deb, R., Thoppe, G. and Budhiraja, A., (2023) “Does Momentum Help in Stochastic Optimization? A Sample Complexity Analysis”, Conference on Uncertainty in Artificial Intelligence, 2023, pp. 602-612, PMLR.
  • Eshwar, S.R., Kolathaya, S. and Thoppe, G., (2023) “Improving sample efficiency in evolutionary RL using off-policy ranking”, EAI International Conference on Performance Evaluation Methodologies and Tools, pp. 33-50.
  • Ganesh, S., Reiffers-Masson, A. and Thoppe, G., (2023) “Online Learning with Adversaries: A Differential-Inclusion Analysis”, Conference on Decision and Control (CDC), 2023.
  • Naskar A. and Thoppe, G., (2023) “Convergence of Momentum-based Distributed Stochastic Approximation with RL Applications,” Indian Control Conference, 2023.
  • A. Tripathi, R. R. Dani, A. Mishra, A. Chakraborty, (2023) “Multimodal query-guided object localization”, Multimedia Tools and Applications (2023): 1-25.
  • Krishnakumaran R and Ray S (2023) Temporal characteristics of gamma rhythm constrain properties of noise in an inhibition-stabilized network model. Cerebral Cortex. 33, 10108-21.
  • Kanth and Ray S (2023) Gamma responses to colored natural stimuli can be predicted from local low-level stimulus features. bioRxiv. https://doi.org/10.1101/2023.07.17.549318
  • P. Phillip, K. Jainwal, A. v. Schaik and C. S. Thakur, (2023) “Tau-cell-based Analog Silicon Retina with Spatio- Temporal Filtering and Contrast Gain Control,” in IEEE Transactions on Biomedical Circuits and Systems, doi: 10.1109/TBCAS.2023.3332117.
  • R. M. Srivatsav, S. Chakrabartty and C. S. Thakur, (2023) “Neuromorphic Computing With Address-Event-Representation Using Time-to-Event Margin Propagation,” in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 13, no. 4, pp. 1114-1124, Dec. 2023, doi: 10.1109/JETCAS.2023.3328916
  • A. Krishna et al., (2023) “A Sparsity-driven tinyML Accelerator for Decoding Hand Kinematics in Brain-Computer Interfaces,” 2023 IEEE Biomedical Circuits and Systems Conference (BioCAS), Toronto, ON, Canada, 2023, pp. 1-5, doi: 10.1109/BioCAS58349.2023.10389094
  • Suman Chatterjee, Rathin K Joshi, Tushar Sakorikar, Bhagaban Behera, Nitu Bhaskar, Shabari Girishan K V, Mahesh Jayachandra, and Hardik J Pandya, (2023) “Design and fabrication of a microelectrode array for studying epileptiform discharges from rodents.” Biomedical Microdevices, 25, 31 (2023). DOI: https://doi.org/10.1007/s10544-023-00672-0
  • Arjun B S, Varun Canamedi, Sharmila Sree Vandrangi, and Hardik J. Pandya, (2023) “Brain Biopsy Imaging using Electrical Impedance Tomography (BBI-EIT).” IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI’23)), Pittsburgh, Pennsylvania, USA, October 15 – 18, 2023.
  • Arjun B S, Ajay Krishnan A, and Hardik J. Pandya, (2023) “MRI-Compatible Patient-specific Continuum Robots using Parametric Modelling.” IEEE-EMBS International Conference on Body Sensor Networks: Sensor and Systems for Digital Health (IEEE BSN 2023), Boston, Massachusetts, USA, October 9 – 11, 2023. DOI: https://doi.org/10.1109/BSN58485.2023.10331197.
  • Arjun B S, Ajay Krishnan A, and Hardik J. Pandya, (2023) “Soft-Robotic Probe for Tissue Characterization using TinyML.” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023), Detroit, Michigan, USA, October 1 – 5, 2023.
  • Suman Chatterjee, Rathin K. Joshi, Shabari Girishan K V, Hardik J. Pandya, (2023) “Flexible Microelectrode Array for Chronic Electrocorticography Recording under Different Neurophysiological Conditions.” 11th International IEEE EMBS Conference on Neural Engineering (NER), April 25-28, 2023, Baltimore, USA. DOI: https://doi.org/10.1109/NER52421.2023.10123820.
  • A. Krishna, V. Ramanathan, S. S. Yadav, S. Shah, A. van Schaik, M. Mehendale, and C. S. Thakur, (2023) “A Sparsity-driven tinyML Accelerator for Decoding Hand Kinematics in Brain-Computer Interfaces,” in IEEE BIOCAS 2023, Toronto, Canada, 2023
  • Adithya K., Shankaranarayanan H., Hitesh P. O., Anand C., A. van Schaik, M. Mehendale, C. S. Thakur., (2023) “TinyML Acoustic Classification using RAMAN Accelerator and Neuromorphic Cochlea,” 2023 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS), Hyderabad, India, 2023
  • Santi Prasad Rath, Yi Suin, Navakanta Bhat, Sreebrata Goswami, R. Stanley Williams, & Sreetosh Goswami* (2022) Energy and Space Efficient Parallel Adder Using Molecular Memristors. Advanced Materials, 2022, 2206128. As the last and corresponding author
  • Santi P. Rath, Damien Thompson, Sreebrata Goswami* and Sreetosh Goswami* (2022) “Many-body molecular interactions in a memristor”, Advanced Materials, 2022, 2204551. As the last and corresponding author.
  • Chirag Jain, Daniel Gibney, Sharma Thankachan. (2022) “Co-linear chaining with overlaps and gap costs” International Conference on Research in Computational Molecular Biology (RECOMB) 2022. https://doi.org/10.1007/978-3-031-04749-7_15
  • Saurabh Kalikar, Chirag Jain, Vasimuddin Md, Sanchit Misra. (2022) “Accelerating minimap2 for long-read sequencing applications on modern CPUs” Nature Computational Science 2022. https://doi.org/10.1038/s43588-022-00201-8
  • F. Ahsan, U. Banerjee, (2022) “Embedded Software Implementation of Privacy Preserving Matrix Computation using Elliptic Curve Cryptography for IoT Applications,” IEEE International Symposium on Advanced Networks and Telecommunication Systems (ANTS), pp. 353-358, December 2022
  • U. Shreemali, A. Chakraborty, ‘Robust Gait Based Human Identification on Incomplete and Multi-view Sequences’, Multimedia Tools and Applications, Vol.80(7), pp.10141-10166, 2021.
  • A. Krishna, D. Mittal, S.G. Virupaksha, A.R. Nair, R. Narayanan, C.S. Thakur, ‘Biomimetic FPGA-based Spatial Navigation Model with Grid cells and Place cells’. Neural Networks (Elsevier), Vol.139, pp.45-63, July 2021.
  • G. Jacob, R.T. Pramod, H. Katti, and S.P. Arun, ‘Qualitative similarities and differences in visual object representations between brains and deep networks’ Nature Communications, Vol.12, 1872, 2021.
  • S. Gupta, S. Chakraborty, C.S. Thakur, ‘Neuromorphic Time-Multiplexed Reservoir Computing with On-the-fly Weight Generation for Edge Devices’, to appear in IEEE Transactions on Neural Networks and Learning Systems, 2021.
  • Siddharth Barman and Paritosh Verma, ‘Existence and Computation of Maximin Fair Allocations Under Matroid-Rank Valuations’, International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2021.
  • Siddharth Barman, Omar Fawzi, and Paul FerméTight, ‘Approximation Guarantees for Concave Coverage Problems’, Symposium on Theoretical Aspects of Computer Science (STACS), 2021.
  • Suprovat Ghoshal and Anand Louis, ‘Approximation Algorithm and Hardness for Strong Unique Games’, ACM-SIAM Symposium on Discrete Algorithms (SODA), 2021.
  • Deval Patel, Arindam Khan and Anand Louis, ‘Group Fairness for Knapsack Problems’, International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), 2021.
  • S. Gurugubelli, and S.P. Chepuri, ‘Graph Learning for Clustering Multi-view Data’, accepted for EUSIPCO 2021 (arXiv preprint arXiv:2010.12301).
  • Aravind Illa, and Prasanta Kumar Ghosh. ‘Closed-set speaker conditioned acoustic-to-articulatory inversion using bi-directional long short term memory network. ‘ The Journal of the Acoustical Society of America Vol.147(2), EL171-EL176, 2020.
  • Aravind Illa and P. K. Ghosh, ‘The impact of speaking rate on acoustic-to-articulatory inversion ‘, Computer Speech & Language, Volume 59, pp.75-90, January 2020.
  • Siddharth Barman and Sanath Kumar Krishnamurthy, ‘Approximation Algorithms for Maximin Fair Division ‘, ACM Transactions on Economics and Computation (TEAC), 2020
  • S.A. Ajmera, H. Jain, M. Sundaresan, and D. Sridharan, ‘Decoding task-specific cognitive states with slow, directed functional networks in the human brain ‘ eNeuro, 7 April, 2020.
  • S. Rudresh, A. J. Kamath, and C. S. Seelamantula, ‘A time-based sampling framework for finite-rate-of-innovation signals, ‘ Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 4-8, 2020.
  • A. Sravanti, N. Gaurav, C. Anirban, and R. Venkatesh Babu, ‘DeGAN : Data-enriching GAN for retrieving Representative Samples from a Trained Classifier ‘, Conference of the American Association for Artificial Intelligence (AAAI) 2020.
  • A. Tripathi, R. R. Dani, A. Mishra, A. Chakraborty, ‘Sketch-Guided Object Localization in Natural Images ‘, European Conference on Computer Vision (ECCV), 2020.
  • S. Aggarwal, J. N. Kundu, R. Venkatesh Babu, A. Chakraborty, ‘WAMDA: Weighted Alignment of Sources for Multi-source Domain Adaptation ‘, British Machine Vision Conference (BMVC), 2020.
  • S. Aggarwal, R. Venkatesh Babu, A. Chakraborty, ‘Text-based Person Search via Attribute-aided Matching ‘, Winter Conference on Applications of Computer Vision (WACV), 2020.
  • J. N. Kundu, S. Seth, R. M. Venkatesh, R. Mugalodi, R. Venkatesh Babu, A. Chakraborty, ‘Kinematic-Structure-Preserved Representation for Unsupervised 3D Human Pose Estimation ‘, Conference of the American Association for Artificial Intelligence (AAAI), 2020.
  • Siddharth Barman, Umang Bhaskar, and Nisarg Shah, ‘Settling the Price of Fairness for Indivisible Goods ‘, Conference on Web and Internet Economics (WINE), 2020.
  • Siddharth Barman, Umang Bhaskar, Anand Krishna, and Ranjani Sundaram, ‘Tight Approximation Algorithms for p-Mean Welfare Under Subadditive Valuation ‘, European Symposium on Algorithms (ESA), 2020.
  • Siddharth Barman and Nidhi Rathi, ‘Fair Cake Division Under Monotone Likelihood Ratios ‘, ACM Conference on Economics and Computation (EC), 2020.
  • Siddharth Barman and Federico Echenique, ‘The Edgeworth Conjecture with Small Coalitions and Approximate Equilibria in Large Economies ‘, ACM Conference on Economics and Computation (EC), 2020.
  • Siddharth Barman and Ranjani Sundaram, ‘Uniform Welfare Guarantees Under Identical Subadditive Valuations ‘, International Joint Conference on Artificial Intelligence (IJCAI), 2020.
  • Siddharth Barman, Omar Fawzi, Suprovat Ghoshal, and Emirhan Gurpinar, ‘Tight Approximation Bounds for Maximum Multi-Coverage ‘, Conference on Integer Programming and Combinatorial Optimization (IPCO), 2020.
  • Arpita Biswas, Siddharth Barman, Amit Deshpande, and Amit Sharma ‘Inframarginality Audit of Group-Fairness ‘, Symposium on Foundations of Responsible Computing (FORC), 2020.
  • Navaneet, K. L., Ansu Mathew, Shashank Kashyap, Wei-Chih Hung, Varun Jampani, and R. Venkatesh Babu, ‘From image collections to point clouds with self-supervised shape and pose networks ‘, In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 1132-1140. 2020.
  • G. Gurusamy, V. Sreenivasan, R.G. Ramesh, S. Purokayastha, M. Javali, N.P. Rao, and D. Sridharan, ‘Diffusion MRI-based structural connectivity robustly predicts ‘brain-age ‘, NeurIPS Workshop on Medical Imaging (Med-NeurIPS), 2020.
  • Anusuya, P. K., Aravind Illa, and Prasanta Kumar Ghosh ‘A Data-Driven Phoneme-Specific Analysis of Articulatory Importance ‘, International Seminar on Speech Production (ISSP), 2020.
  • Renuka Mannem, Himajyothi Rajamahendravarapu, Aravind Illa, Prasanta Kumar Ghosh, ‘peech rate estimation using representations learned from speech with convolutional neural network ‘ , SPCOM 2020.
  • Siddharth Subramani, Achuth Rao M V, Divya Giridhar, Prasanna Suresh Hegde, Prasanta Kumar Ghosh,”Automatic Classification of Volumes of Water using Swallow Sounds from Cervical Auscultation”, In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, 2020.
  • Abhayjeet Singh, Aravind Illa, Prasanta Kumar Ghosh, “A Comparative Study of Estimating Articulatory Movements from Phoneme Sequences and Acoustic Features”, In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, 2020. Aravind Illa and Prasanta Kumar Ghosh, “Complexity-Performance Trade-off In Acoustic-to-Articulatory Inversion”, International Seminar on Speech Production (ISSP) 2020.
  • A. Krishna, S. Rudresh, V. Shaw, H. R. Sabbella, C. S. Seelamantula, and C. S. Thakur, ‘Unlimited dynamic range analog-to-digital conversion,’ arXiv:1911.09371, 2019.
  • Gupta S, Kumar P, Paul T, van Schaik A, Ghosh A, Thakur C S, ‘Low Power, CMOS-MoS2 Memtransistor based Neuromorphic Hybrid Architecture for Wake-Up Systems ‘, Scientific Reports (Nature Group), Vol.9, 15604, 2019.
  • Achuth Rao MV and P. K. Ghosh, ‘Glottal Inverse Filtering Using Probabilistic Weighted Linear Prediction’ IEEE/ACM Transactions on Audio, Speech, and Language Processing 27.1 (2019): 114-124.
  • Aravind Illa and Prasanta Kumar Ghosh. “The impact of speaking rate on acoustic-to-articulatory inversion”, Computer Speech & Language, 2019.
  • Sreenivasan VÂ and Sridharan D, ‘Subcortical connectivity correlates selectively with attention ‘s effects on spatial choice bias ‘, Proceedings of the National Academy of Sciences USA, Vol.116 (39), pp.19711-19716, 2019.
  • Sagar V, Sengupta R and Sridharan D*, ‘Dissociable sensitivity and bias mechanisms mediate behavioral effects of exogenous attention ‘, Scientific Reports, Vol.9(1), 12657, 2019.
  • Banerjee S, Grover S, Ganesh S and Sridharan D, ‘Sensory and decisional components of endogenous attention are dissociable ‘, Journal of Neurophysiology, Vol.122(4), pp.1538-1554, 2019.
  • Navaneet, K.L., Sarvadevabhatla, R.K., Shekhar, S., Babu, R.V. and Chakraborty, A., ‘Operator-in-the-Loop Deep Sequential Multi-camera Feature Fusion for Person Re-identification ‘, IEEE Transactions on Information Forensics and Security, 2019.
  • P. Agrawal and S. Ganapathy, ‘Modulation Filter Learning Using Deep Variational Networks for Robust Speech Recognition ‘, IEEE Journal of Selected Topics in Signal Processing (J-STSP), Special Issue on Data Science: Machine Learning for Audio Signal Processing, April 2019.
  • A. Soman, C.R. Madhavan, K. Sarkar, and S. Ganapathy, ‘An EEG Study On The Brain Representations in Language Learning ‘, IOP Journal on Biomedical Physics and Engineering Express, Vol.5(2), pp.25-41, 2019.
  • S. Ramoji and S. Ganapathy, ‘Supervised I-vector Modeling for Language and Accent Recognition ‘, Elsevier Journal on Computer, Speech and Language, Oct. 2019.
  • B. R. Pradhan, Y. Bethi, S. Narayanan, A. Chakraborty, and C.S. Thakur, ‘n-HAR: A Neuromorphic Event-Based Human Activity Recognition System Using Memory Surfaces ‘, IEEE International Symposium on Circuits and Systems (ISCAS), 2019.
  • R. Sharma, S. Gupta, K. Kumar, P. Kumar, and C.S. Thakur, ‘Real-Time Image Segmentation Using Neuromorphic Pixel Array ‘, IEEE International Symposium on Circuits and Systems (ISCAS), 2019.
  • S.Gupta, P. Kumar, K. Kumar, S. Chakraborty, and C.S. Thakur, ‘Low Power Neuromorphic Analog System based on Sub-Threshold Current Mode Circuits ‘, IEEE International Symposium on Circuits and Systems (ISCAS), 2019.
  • A. Tripathi, M. Arabizadeh, S. Khandelwal, and C.S. Thakur, ‘Analog Neuromorphic System based on Multi Input Floating Gate MOS Neuron Model ‘, IEEE International Symposium on Circuits and Systems (ISCAS), 2019.
  • Vidyadhar Upadhya and P.S. sastry, ‘Efficient Learning of Restricted Boltzmann Machines Using Covariance estimates ‘, Asian Conference on Machine Learning (ACML), Nagoya, Japan, 2019.
  • B.N. Suhas, Deep Patel, Nithin Rao, Yamini Belur, Pradeep Reddy, Nalini Atchayaram, Ravi Yadav, Dipanjan Gope and P. K. Ghosh, ‘Comparison of Speech Tasks and Recording Devices for Voice Based Automatic Classification of Healthy Subjects and Patients with Amyotrophic Lateral Sclerosis ‘, Interspeech 2019, Graz, Austria.
  • Manoj Kumar Ramanathi, Chiranjeevi Yarra and P. K. Ghosh, ‘ASR inspired syllable stress detection for pronunciation evaluation without using a supervised classifier and syllable level features ‘, Interspeech 2019, Graz, Austria.
  • Abinay Reddy Naini, Achuth Rao MV and P. K. Ghosh, ‘Whisper to neutral mapping using cosine similarity maximization in i-vector space for speaker verification ‘, Interspeech 2019, Graz, Austria.
  • Renuka Mannem, Jhansi Mallela, Aravind Illa and P. K. Ghosh, ‘Acoustic and articulatory feature based speech rate estimation using a convolutional dense neural network ‘, Interspeech 2019, Graz, Austria.
  • Atreyee Saha, Chiranjeevi Yarra and P. K. Ghosh, ‘Low resource automatic intonation classification using gated recurrent unit (GRU) networks pre-trained with synthesized pitch patterns ‘, Interspeech 2019, Graz, Austria.
  • Sweekar Sudhakara, Manoj Kumar Ramanathi, Chiranjeevi Yarra and P. K. Ghosh, ‘An improved goodness of pronunciation (GoP) measure for pronunciation evaluation with DNN-HMM system considering HMM transition probabilities ‘, Interspeech 2019, Graz, Austria.
  • Aravind Illa and P. K. Ghosh, ‘An investigation on speaker specific articulatory synthesis with speaker independent articulatory inversion ‘, Interspeech 2019, Graz, Austria.
  • Chiranjeevi Yarra, Aparna Srinivasan, Sravani Gottimukkala and P. K. Ghosh, ‘SPIRE-fluent: A self-learning app for tutoring oral fluency to second language English learners ‘, Interspeech 2019, Graz, Austria
  • Aravind Illa and P. K. Ghosh, ‘Representation learning using convolution neural network for acoustic-to-articulatory inversion ‘, Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, pp. 5931-5935, 2019.
  • Gokul Srinivasan, Aravind Illa and P. K. Ghosh, ‘A study on robustness of articulatory features for automatic speech recognition of neutral and whispered speech ‘, Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, pp.5936-5940, 2019.
  • C.A. Valliappan, Avinash Kumar, Renuka Mannem, Karthik Girija Ramesan, P. K. Ghosh, ‘An improved air tissue boundary segmentation technique for real time magnetic resonance imaging video using segnet ‘, Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, pp.5921-5925, 2019.
  • Renuka Mannem and P. K. Ghosh, ‘Air-tissue boundary segmentation in real time magnetic resonance imaging video using a convolutional encoder-decoder network ‘, Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , Brighton, UK, pp.5941-5945, 2019.
  • Abinay Reddy Naini, Achuth Rao M V and P. K. Ghosh, ‘Formant-gaps features for speaker verification using whispered speech ‘, Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , Brighton, UK, pp.6231-6235, 2019.
  • Ajmera SA, Rajagopal S, Rehman R and Sridharan D, ‘Infra-slow brain dynamics as a marker for cognitive function and decline ‘, Advances in Neural Information Processing Systems (NeurIPS), 2019.
  • Kumar S, Sreenivasan V, Talukdar P, Pestilli, F and Sridharan D, ‘ReAl-LiFE: Accelerating the discovery of individualized brain connectomes on GPUs ‘, AAAI Conference on Artificial Intelligence Proceedings, 33(01), pp.630-638, 2019.
  • Eshwar Arunachaleswaran, Siddharth Barman, and Nidhi Rathi, ‘Fully Polynomial-Time Approximation Schemes for Fair Rent Division ‘, ACM-SIAM Symposium on Discrete Algorithms (SODA), 2019.
  • Eshwar Arunachaleswaran, Siddharth Barman, and Nidhi Rathi, ‘Fair Division with a Secretive Agent ‘, AAAI Conference on Artificial Intelligence, 2019.
  • Siddharth Barman and Sanath Krishnamurthy, ‘On the Proximity of Markets with Integral Equilibria ‘, AAAI Conference on Artificial Intelligence, 2019.
  • Siddharth Barman, Ganesh Ghalme, Shweta Jain, Pooja Kulkarni, and Shivika Narang, ‘Fair Division of Indivisible Goods Among Strategic Agents ‘, International Conference on Autonomous Agents and Multiagent Systems (Extended Abstract), 2019.
  • Eshwar Arunachaleswaran, Siddharth Barman, Rachitesh Kumar, and Nidhi Rathi, ‘Fair and Efficient Cake Division with Connected Pieces ‘, Conference on Web and Internet Economics(WINE), 2019.
  • K.L. Navaneet, P. Mandikal, M. Agarwal, and R.V. Babu, ‘CAPNet: Continuous approximation projection for 3D point cloud reconstruction using 2D supervision ‘, In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 33, pp. 8819-8826), 2019.
  • K. Praveen, A. Gupta, A. Soman and S. Ganapathy ‘Second Language Transfer Learning in Humans and Machines Using Image Supervision ‘, IEEE ASRU, Dec. 2019.
  • P. Agrawal and S. Ganapathy, ‘Unsupervised Raw Waveform Representation Learning for ASR ‘, INTERSPEECH, 2019.
  • N. Sharma, S. Ganesh, S. Ganapathy and L. Holt, ‘Analyzing human reaction time for talker change detection ‘, ICASSP, 2019.
  • P. Agrawal and S. Ganapathy, ‘Deep variational filter learning models for speech recognition ‘, ICASSP, 2019. A. Mishra, S. Shekhar, A. K. Singh, A. Chakraborty, ‘OCR-VQA: Visual Question Answering by Reading Text in Images ‘, International Conference on Document Analysis and Recognition (ICDAR), 2019.

(*The above publication list is not exhaustive and is not sorted in any particular order)

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