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About Me

I am an Assistant Professor in the Computer Science and Engineering Department at University of Nevada Reno, USA. Before joining UNR, I was a Postdoctoral researcher in GML, working with Prof. Pavan Turaga at Arizona State University. I defended my PhD in Oct, 2020 from IIIT-Delhi under the guidance of Dr. Saket Anand. My dissertation title is “Exploring Geometric Constraints for Learning Representations for Visual Data”. During my PhD, I also worked as a visiting research scholar with Prof. Pavan Turaga for 6 months in 2019 (Feb - Aug) as well as during the summer of 2017. I received my Master’s degree from IIIT-Delhi. I was awarded Best Thesis Award for my thesis titled “Signal Processing Techniques to Reduce Energy Consumption in EEG Acquisition and Transmission for WBAN” under the guidance of Dr. Angshul Majumdar.

My research interests lie in deep learning and machine learning approaches for visual and time series data, topological data analysis, differential geometry and geometry driven approaches for learning. From the applications point of view, I focus on AI for Science and AI for Social Good (specifically towards wildlife conservation and human health applications).

Note: I am actively looking for self-motivated graduate and undergraduate students to join my lab!

Contact Me

Reach me at ankitas@unr.edu

Updates and News

• Paper titled “Improving Shape Awareness and Interpretability in Deep Networks Using Geometric Moments” accepted at Workshop and Challenge on Deep Learning for Geometric Computing at CVPR 2023
• Paper titled “Polynomial Implicit Neural Representations For Large Diverse Datasets” accepted at CVPR 2023
• Paper titled “Understanding the Role of Mixup in Knowledge Distillation: An Empirical Study” accepted at WACV 2023.
• Paper titled “The Gradient-Boosting Method for Tackling High Computing Demand in Underwater Acoustic Propagation Modeling” accepted at Special Issue Numerical Modelling of Atmospheres and Oceans, June 2022.
• Paper titled “Machine-Learning Approach for Automatic Detection of Wild Beluga Whales from Hand-Held Camera Pictures” accepted at Special Issue Sensors and Artificial Intelligence for Wildlife Conservation, May 2022.
• Presented my work on “AI based tool for Beluga Whale Conservation and Monitoring” at Ocean Sciences Meeting 2022.
• Organizing the DiffCVML 2020 Workshop, held in conjunction with CVPR 2020.
• Recieved travel grant from WiML 2019 to present my work titled “Ignorance is Bliss: Semantic Pairing for Fine-grained Visual Recognition” in the workshop.

Publications

2023

• Polynomial Implicit Neural Representations For Large Diverse Datasets
  Rajhans Singh, Ankita Shukla, Pavan Turaga
  CVPR 2023
• Improving Shape Awareness and Interpretability in Deep Networks Using Geometric Moments
  Rajhans Singh, Ankita Shukla, Pavan Turaga
  DLGC, CVPR 2023

2022

• Learning Free Energy Pathways through Reinforcement Learning of Adaptive Steered Molecular Dynamics
  Nicholas Ho, John Kevin Cava, John Vant, Ankita Shukla, Jake Miratsky, Pavan Turaga, Ross Maciejewski, Abhishek Singharoy.
  MLSB, NeurIPS 2022
• Understanding the Role of Mixup in Knowledge Distillation: An Empirical Study
  Hongjun Choi, Eunsom Jeon, Ankita Shukla, Pavan Turaga
  WACV 2023
• The Gradient-Boosting Method for Tackling High Computing Demand in Underwater Acoustic Propagation Modeling D. Lagrois, T. R. Bonnell, A. Shukla and C. Chion
  Journal of Marine Science and Engineering
• Role of Data Augmentation Strategies in Knowledge Distillation for Wearable Sensor Data
  E. Jeon, A. Som, A. Shukla, K. Hasanaj, M. P. Buman; P. Turaga
  IEEE Internet of Things Journal, vol. 9, no. 14, pp. 12848-12860, 15 July, 2022
• Machine-Learning Approach for Automatic Detection of Wild Beluga Whales from Hand-Held Camera Pictures
  V. M. Arujo, A. Shukla, C. Chion, S. Gambs and R. Michaud
  Special Issue Sensors and Artificial Intelligence for Wildlife Conservation
• Deep Geometric Moment
  R. Singh, A. Shukla, P. Turaga

2021

• Geometric Priors for Scientific Generative Models in Inertial Confinement Fusion, Machine Learning for Physical Sciences
  Ankita Shukla, R. Anirudh, E. Kur, J. J. Thiagarajan, P. Bremer, B. K. Spears, T. Ma, P. Turaga
  Machine Learning for Physical Sciences, NeurIPS 2021.
• Towards Conditional Generation of Minimal Action Potential Pathways for Molecular Dynamics
  J. K. Cava, J. Vant, N. Ho, A. Shukla, P. Turaga, R. Maciejewski, A. Singharoy
  ELLIS Machine Learning for Molecule Discovery Workshop, 2021
• Cleaning Adversarial Perturbations with Image-Subspace Projections
  Ankita Shukla, Pavan Turaga, Saket Anand
  3rd Workshop on Adversarial Learning Methods for Machine Learning and Data Mining, KDD 2021.

2020

• GraCIAS: Grassmannian of Corrupted Images for Adversarial Security
  A. Shukla, P. Turaga, S. Anand
• Semi-supervised Clustering with Neural Networks
  A. Shukla, G.S. Cheema, Saket Anand
  BigMM 2020.

  2019

• A Hybrid Approach for Tiger Re-Identification
  Ankita Shukla, C. Anderson, G. S. Cheema, P. Guo, S. Onda, D. Anshumaan, S. Anand, R. Farrell
  (Workshop and Challenge on CVWC, ICCV 2019)
• PrOSe: Product of Orthogonal Spheres Parameterization for Disentangled Representation Learning
  Ankita Shukla, Shagun Uppal, Sarthak Bhagat, Saket Anand, Pavan Turaga
  (BMVC 2019)
• Primate Face Identification in the Wild Pages 387-401
  Ankita Shukla*, Gullal Singh Cheema*, Saket Anand, Qamar Qureshi, Yadvendradev Jhala
  (PRICAI 2019) (*Equal Contribution)

2018

• Geometry of Deep Generative Models for Disentangled Representations
  Ankita Shukla, Shagun Uppal, Sarthak Bhagat, Saket Anand, Pavan Turaga
  (ICVGIP 2018)

• Perturbation Robust Representations of Topological Persistence Diagrams
  Anirudh Som, Kowshik Thopalli, K. N. Ramamurthy, V. Venkataraman, Ankita Shukla, Pavan Turaga
  (ECCV 2018)

2017

• Metric Learning on Biological Sequence Embeddings
  Dhananjay Kimothi, Ankita Shukla, Pravesh Biyani, Saket Anand, James M. Hogan
  IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2017)

• Energy efficient EEG acquisition and reconstruction for a Wireless Body Area Network
  Wazir Singh, Ankita Shukla, Sujay Deb, Angshul Majumdar
  Integration, the VLSI Journal 2017

2016

• Metric Learning based Automatic Segmentation of Patterned Species
  Ankita Shukla, Saket Anand
  International Conference on Image Processing (ICIP 2016)

2015

• Distance Metric Learning by Optimization on the Stiefel Manifold (Best Student Paper)
  Ankita Shukla, Saket Anand
  Differential Geometry in Computer Vision (in conjunction with BMVC 2015)

• Combining Sparsity with Rank Deficiency for Energy Efficient EEG Sensing and Transmission over Wireless Body Area Network
  Angshul Majumdar, Ankita Shukla, Rabab Ward
  International Conference on Acoustics, Speech and Signal Processing (ICASSP 2015)

• Exploiting Inter-channel Correlation in EEG Signal Reconstruction
  Ankita Shukla, Angshul Majumdar
  Biomedical Signal Processing and Control 2015

• A Kronecker Compressed Sensing formulation for energy efficient EEG sensing
  Ankita Shukla, Angshul Majumdar, Rabab Ward
  (ICAPR 2015)

• Row-sparse blind compressed sensing for reconstructing multi-channel EEG signals
  Ankita Shukla, Angshul Majumdar
  Biomedical Signal Processing and Control 2015

2014

• Split Bregman Algorithms for Sparse/Joint-sparse and Low rank Signal Recovery: Application in Compressive Hyperspectral Imaging
  Anupriya Gogna, Ankita Shukla, Hemant Kumar Aggarwal, Angshul Majumdar
  IEEE International Conference on Image Processing (ICIP 2014)

• Energy Efficient Acquisition and Reconstruction of EEG Signals
  Wazir Singh, Ankita Shukla, Sujay Deb, Angshul Majumdar
  IEEE Engineering in Machine and Biology Conference (EMBC 2014)

• Matrix Recovery using Split Bregman
  Anupriya Gogna, Ankita Shukla, Angshul Majumdar
  22nd International Conference on Pattern Recognition (ICPR 2014)

2013

• Real-Time Dynamic MRI Reconstruction: Accelerating Compressed Sensing on Graphical Processor Unit
  Ankita Shukla, Anghsul Majumdar, Rabab Ward
  IASTED Signal and Image Processing 2013

arXiv Pre-prints

• GraCIAS: Grassmannian of Corrupted Images for Adversarial Security
  Ankita Shukla, Pavan Turaga, Saket Anand (2020)

• Unique Identification of Macaques for Population Monitoring and Control
  Ankita Shukla*, Gullal Singh Cheema*, Saket Anand, Qamar Qureshi, Yadvendradev Jhala
  arXiv preprint arXiv:1811.00743 (2018) (*Equal Contribution)

• Semi-Supervised Clustering with Neural Networks
  Ankita Shukla*, Gullal Singh Cheema*, Saket Anand
  arXiv preprint arXiv:1806.01547 (2018) (*Equal Contribution)