Suhas Lohit

Suhas Lohit
Suhas' Quick Links

  • Biography

    Before coming to MERL, Suhas worked as an intern at MERL (summer 2018), SRI International (summer 2017) and Nvidia (summer 2016). His research interests include computer vision, computational imaging and deep learning. Recently, his research focus has been on creating hybrid model- and data-driven neural architectures for various applications in imaging and vision. He won the Best Paper Award at the CVPR workshop on Computational Cameras and Displays in 2015 and the University Graduate Fellowship at ASU for 2015-16.

  • Recent News & Events


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  • Awards

    •  AWARD    Best Paper - Honorable Mention Award at WACV 2021
      Date: January 6, 2021
      Awarded to: Rushil Anirudh, Suhas Lohit, Pavan Turaga
      MERL Contact: Suhas Lohit
      Research Areas: Computational Sensing, Computer Vision, Machine Learning
      Brief
      • A team of researchers from Mitsubishi Electric Research Laboratories (MERL), Lawrence Livermore National Laboratory (LLNL) and Arizona State University (ASU) received the Best Paper Honorable Mention Award at WACV 2021 for their paper "Generative Patch Priors for Practical Compressive Image Recovery".

        The paper proposes a novel model of natural images as a composition of small patches which are obtained from a deep generative network. This is unlike prior approaches where the networks attempt to model image-level distributions and are unable to generalize outside training distributions. The key idea in this paper is that learning patch-level statistics is far easier. As the authors demonstrate, this model can then be used to efficiently solve challenging inverse problems in imaging such as compressive image recovery and inpainting even from very few measurements for diverse natural scenes.
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  • Research Highlights

  • MERL Publications

    •  Li, D., Zhang, J., Egger, B., Chatterjee, M., Lohit, S., Marks, T.K., Cherian, A., "AssemblyBench: Physics-Aware Assembly of Complex Industrial Objects", arXiv, May 2026.
      BibTeX arXiv
      • @article{Li2026may,
      • author = {Li, Danrui and Zhang, Jiahao and Egger, Bernhard and Chatterjee, Moitreya and Lohit, Suhas and Marks, Tim K. and Cherian, Anoop},
      • title = {{AssemblyBench: Physics-Aware Assembly of Complex Industrial Objects}},
      • journal = {arXiv},
      • year = 2026,
      • month = may,
      • url = {https://arxiv.org/abs/2605.12845}
      • }
    •  Shenoy, V., Lohit, S., Mansour, H., Chellappa, R., Marks, T.K., "Recovering Pulse Waves from Video Using Deep Unrolling and Deep Equilibrium Models", IEEE Transactions on Image Processing, DOI: 10.1109/​TIP.2026.3671653, Vol. 35, pp. 2755-2770, March 2026.
      BibTeX TR2026-031 PDF
      • @article{Shenoy2026mar,
      • author = {Shenoy, Vineet and Lohit, Suhas and Mansour, Hassan and Chellappa, Rama and Marks, Tim K.},
      • title = {{Recovering Pulse Waves from Video Using Deep Unrolling and Deep Equilibrium Models}},
      • journal = {IEEE Transactions on Image Processing},
      • year = 2026,
      • volume = 35,
      • pages = {2755--2770},
      • month = mar,
      • doi = {10.1109/TIP.2026.3671653},
      • issn = {1941-0042},
      • url = {https://www.merl.com/publications/TR2026-031}
      • }
    •  Moosa, I.M., Lohit, S., Wang, Y., Chatterjee, M., Yin, W., "Understanding Dynamic Compute Allocation in Recurrent Transformers", arXiv, February 2026.
      BibTeX arXiv
      • @article{Moosa2026feb,
      • author = {Moosa, Ibraheem Muhammad and Lohit, Suhas and Wang, Ye and Chatterjee, Moitreya and Yin, Wenpeng},
      • title = {{Understanding Dynamic Compute Allocation in Recurrent Transformers}},
      • journal = {arXiv},
      • year = 2026,
      • month = feb,
      • url = {https://arxiv.org/abs/2602.08864}
      • }
    •  Xiang, X., Peng, K.-C., Lohit, S., Jones, M.J., Zhang, J., "Towards Open-Vocabulary Multimodal 3D Object Detection with Attributes", British Machine Vision Conference (BMVC), November 2025.
      BibTeX TR2025-162 PDF Video Data Presentation
      • @inproceedings{Xiang2025nov,
      • author = {{{Xiang, Xinhao and Peng, Kuan-Chuan and Lohit, Suhas and Jones, Michael J. and Zhang, Jiawei}}},
      • title = {{{Towards Open-Vocabulary Multimodal 3D Object Detection with Attributes}}},
      • booktitle = {British Machine Vision Conference (BMVC)},
      • year = 2025,
      • month = nov,
      • url = {https://www.merl.com/publications/TR2025-162}
      • }
    •  Shenoy, V., Wu, S., Comas, A., Lohit, S., Mansour, H., Marks, T.K., "Time-Series U-Net with Recurrence for Noise-Robust Imaging Photoplethysmography", IEEE Access, DOI: 10.1109/​ACCESS.2025.3617284, Vol. 13, pp. 173923-173938, October 2025.
      BibTeX TR2025-145 PDF
      • @article{Shenoy2025oct,
      • author = {Shenoy, Vineet and Wu, Shaoju and Comas, Armand and Lohit, Suhas and Mansour, Hassan and Marks, Tim K.},
      • title = {{Time-Series U-Net with Recurrence for Noise-Robust Imaging Photoplethysmography}},
      • journal = {IEEE Access},
      • year = 2025,
      • volume = 13,
      • pages = {173923--173938},
      • month = oct,
      • doi = {10.1109/ACCESS.2025.3617284},
      • url = {https://www.merl.com/publications/TR2025-145}
      • }
    See All MERL Publications for Suhas

  • Other Publications

    •  Suhas Lohit, Qiao Wang and Pavan Turaga, "Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019, pp. 12426-12435.
      BibTeX
      • @Inproceedings{lohit2019temporal,
      • author = {Lohit, Suhas and Wang, Qiao and Turaga, Pavan},
      • title = {Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping},
      • booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
      • year = 2019,
      • pages = {12426--12435}
      • }
    •  Suhas Lohit, Kuldeep Kulkarni, Ronan Kerviche, Pavan Turaga and Amit Ashok, "Convolutional neural networks for noniterative reconstruction of compressively sensed images", IEEE Transactions on Computational Imaging, Vol. 4, No. 3, pp. 326-340, 2018.
      BibTeX
      • @Article{lohit2018convolutional,
      • author = {Lohit, Suhas and Kulkarni, Kuldeep and Kerviche, Ronan and Turaga, Pavan and Ashok, Amit},
      • title = {Convolutional neural networks for noniterative reconstruction of compressively sensed images},
      • journal = {IEEE Transactions on Computational Imaging},
      • year = 2018,
      • volume = 4,
      • number = 3,
      • pages = {326--340},
      • publisher = {IEEE}
      • }
    •  Suhas Lohit, Ankan Bansal, Nitesh Shroff, Jaishanker Pillai, Pavan Turaga and Rama Chellappa, "Predicting Dynamical Evolution of Human Activities from a Single Image", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018, pp. 383-392.
      BibTeX
      • @Inproceedings{lohit2018predicting,
      • author = {Lohit, Suhas and Bansal, Ankan and Shroff, Nitesh and Pillai, Jaishanker and Turaga, Pavan and Chellappa, Rama},
      • title = {Predicting Dynamical Evolution of Human Activities from a Single Image},
      • booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops},
      • year = 2018,
      • pages = {383--392}
      • }
    •  Suhas Lohit and Pavan Turaga, "Learning invariant Riemannian geometric representations using deep nets", Proceedings of the IEEE International Conference on Computer Vision Workshops, 2017, pp. 1329-1338.
      BibTeX
      • @Inproceedings{lohit2017learning,
      • author = {Lohit, Suhas and Turaga, Pavan},
      • title = {Learning invariant Riemannian geometric representations using deep nets},
      • booktitle = {Proceedings of the IEEE International Conference on Computer Vision Workshops},
      • year = 2017,
      • pages = {1329--1338}
      • }
    •  Kuldeep Kulkarni, Suhas Lohit, Pavan Turaga, Ronan Kerviche and Amit Ashok, "Reconnet: Non-iterative reconstruction of images from compressively sensed measurements", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 449-458.
      BibTeX
      • @Inproceedings{kulkarni2016reconnet,
      • author = {Kulkarni, Kuldeep and Lohit, Suhas and Turaga, Pavan and Kerviche, Ronan and Ashok, Amit},
      • title = {Reconnet: Non-iterative reconstruction of images from compressively sensed measurements},
      • booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
      • year = 2016,
      • pages = {449--458}
      • }
    •  Suhas Lohit, Kuldeep Kulkarni and Pavan Turaga, "Direct inference on compressive measurements using convolutional neural networks", 2016 IEEE International Conference on Image Processing (ICIP), 2016, pp. 1913-1917.
      BibTeX
      • @Inproceedings{lohit2016direct,
      • author = {Lohit, Suhas and Kulkarni, Kuldeep and Turaga, Pavan},
      • title = {Direct inference on compressive measurements using convolutional neural networks},
      • booktitle = {2016 IEEE International Conference on Image Processing (ICIP)},
      • year = 2016,
      • pages = {1913--1917},
      • organization = {IEEE}
      • }
    •  Qiao Wang, Suhas Lohit, Meynard John Toledo, Matthew P Buman and Pavan Turaga, "A statistical estimation framework for energy expenditure of physical activities from a wrist-worn accelerometer", 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2016, pp. 2631-2635.
      BibTeX
      • @Inproceedings{wang2016statistical,
      • author = {Wang, Qiao and Lohit, Suhas and Toledo, Meynard John and Buman, Matthew P and Turaga, Pavan},
      • title = {A statistical estimation framework for energy expenditure of physical activities from a wrist-worn accelerometer},
      • booktitle = {2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
      • year = 2016,
      • pages = {2631--2635},
      • organization = {IEEE}
      • }
    •  Suhas Lohit, Kuldeep Kulkarni, Pavan Turaga, Jian Wang and Aswin C Sankaranarayanan, "Reconstruction-free inference on compressive measurements", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2015, pp. 16-24.
      BibTeX
      • @Inproceedings{lohit2015reconstruction,
      • author = {Lohit, Suhas and Kulkarni, Kuldeep and Turaga, Pavan and Wang, Jian and Sankaranarayanan, Aswin C},
      • title = {Reconstruction-free inference on compressive measurements},
      • booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops},
      • year = 2015,
      • pages = {16--24}
      • }

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  • MERL Issued Patents

    • Title: "SYSTEMS AND METHODS FOR INTERPRETABLE CLASSIFICATION OF IMAGES USING INHERENTLY EXPLAINABLE NEURAL NETWORKS"
      Inventors: Jones, Michael J.; Lohit, Suhas; Cherian, Anoop; Carmichael, Zacharias
      Patent No.: 12,633,103
      Issue Date: May 19, 2026
    • Title: "System and Method for Cross-Modal Knowledge Transfer Without Task-Relevant Source Data"
      Inventors: Lohit, Suhas; Ahmed, Sk Miraj; Peng, Kuan-Chuan; Jones, Michael J.
      Patent No.: 12,511,549
      Issue Date: Dec 30, 2025
    • Title: "Rendering Two-Dimensional Image of a Dynamic Three-Dimensional Scene"
      Inventors: Chatterjee, Moitreya; Lohit, Suhas; Miraldo, Pedro
      Patent No.: 12,475,636
      Issue Date: Nov 18, 2025
    • Title: "System and Method for Generating a Radar Image of a Scene"
      Inventors: Mansour, Hassan; Lohit, Suhas; Boufounos, Petros T.
      Patent No.: 12,287,398
      Issue Date: Apr 29, 2025
    • Title: "Systems and Methods for Multi-Spectral Image Fusion Using Unrolled Projected Gradient Descent and Convolutinoal Neural Network"
      Inventors: Liu, Dehong; Lohit, Suhas; Mansour, Hassan; Boufounos, Petros T.
      Patent No.: 10,891,527
      Issue Date: Jan 12, 2021
    See All Patents for MERL