Devesh Jha

  • Biography

    Devesh's PhD Thesis was on decision & control of autonomous systems. He also got a Master's degree in Mathematics from Penn State. His research interests are in the areas of Machine Learning, Time Series Analytics and Robotics. He was a recipient of the best student paper award at the 1st ACM SIGKDD workshop on Machine Learning for Prognostics and Health Management at KDD 2016, San Francisco.

  • Recent News & Events

    •  NEWS   MERL Scientists Presented 5 Papers Including 2 Invited Talks at Optical Fiber Communications Conference (OFC) 2020
      Date: March 8, 2020 - March 13, 2020
      MERL Contacts: Devesh Jha; Toshiaki Koike-Akino; Keisuke Kojima; David Millar; Kieran Parsons; Ye Wang
      Research Areas: Communications, Electronic and Photonic Devices, Machine Learning, Signal Processing
      Brief
      • Due to COVID-19, MERL Optical Team scientists remotely presented 5 papers including 2 invited talks at the Optical Fiber Communications Conference (OFC) 2020, that was held in San Diego from March 8-13, 2020. Topics presented include recent advances in quantum signal processing, channel coding design, nano-optic power splitter, and deep learning-based integrated photonics. In addition, Dr. Kojima gave an invited workshop talk on deep learning-based nano-photonic device optimization.

        OFC is the largest global conference and exhibition for optical communications and networking professionals. The program is comprehensive from research to marketplace, from components to systems and networks and from technical sessions to the exhibition. For over 40 years, OFC has drawn attendees from all corners of the globe to meet and greet, teach and learn, make connections and move the industry forward. The five-day technical conference features peer reviewed presentations and more than 180 invited speakers, the thought leaders in the industry presenting the highlights of emerging technologies. Additional technical programming throughout the week includes special symposia, special sessions, in-depth tutorials, workshops, panels and the thought-provoking rump session.
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    •  NEWS   MERL Scientists Presenting 5 Papers including 2 Invited Talks at European Conference on Optical Communication (ECOC) 2019
      Date: September 22, 2019 - September 26, 2019
      MERL Contacts: Devesh Jha; Toshiaki Koike-Akino; Keisuke Kojima; David Millar; Kieran Parsons; Ye Wang
      Research Areas: Artificial Intelligence, Communications, Electronic and Photonic Devices, Optimization, Signal Processing
      Brief
      • MERL Optical Team scientists will be presenting 5 papers including 2 invited talks at the 45th European Conference on Optical Communication (ECOC) 2019, which is being held in Dublin from September 22-26, 2019. Topics to be presented include recent advances in sophisticated constellation shaping schemes, lattice coding, and deep learning-based turbo equalization to mitigate fiber nonlinearity. Dr. Kojima is giving an invited workshop talk on deep learning-based nano-photonic device optimization. Dr. Tobias Fehenberger, a former Visiting Scientist is giving an invited talk related to our joint paper "Mapping Strategies for Short-Length Probabilistic Shaping"

        ECOC is the largest optical communications event in Europe and a key meeting place for more than 1,500 scientists and researchers from institutions and companies across the world. The conference features more than 400 oral and poster presentations from various major telecoms industries and universities. As well as being one of the largest scientific conferences globally, ECOC also features Europe’s largest optical communications exhibition.
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  • Awards

    •  AWARD   MERL Researcher Devesh Jha Wins the Rudolf Kalman Best Paper Award 2019
      Date: October 10, 2019
      Awarded to: Devesh Jha, Nurali Virani, Zhenyuan Yuan, Ishana Shekhawat and Asok Ray
      MERL Contact: Devesh Jha
      Research Areas: Artificial Intelligence, Control, Data Analytics, Machine Learning, Robotics
      Brief
      • MERL researcher Devesh Jha has won the Rudolf Kalman Best Paper Award 2019 for the paper entitled "Imitation of Demonstrations Using Bayesian Filtering With Nonparametric Data-Driven Models". This paper, published in a Special Commemorative Issue for Rudolf E. Kalman in the ASME JDSMC in March 2018, uses Bayesian filtering for imitation learning in Hidden Mode Hybrid Systems. This award is given annually by the Dynamic Systems and Control Division of ASME to the authors of the best paper published in the ASME Journal of Dynamic Systems Measurement and Control during the preceding year.
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  • MERL Publications

    •  Tang, Y., Kojima, K., Koike-Akino, T., Wang, Y., Wu, P., TaherSima, M., Jha, D., Parsons, K., Qi, M., "Deep Neural Network Inverse Design of Integrated Nanophotonic Devices", arXiv, DOI: arXiv:2003.03747, March 2020.
      BibTeX arXiv
      • @article{Tang2020mar2,
      • author = {Tang, Yingheng and Kojima, Keisuke and Koike-Akino, Toshiaki and Wang, Ye and Wu, Pengxiang and TaherSima, Mohammad and Jha, Devesh and Parsons, Kieran and Qi, Minghao},
      • title = {Deep Neural Network Inverse Design of Integrated Nanophotonic Devices},
      • journal = {arXiv},
      • year = 2020,
      • month = mar,
      • doi = {arXiv:2003.03747},
      • url = {http://arxiv.org/abs/2003.03747}
      • }
    •  Kojima, K., TaherSima, M., Koike-Akino, T., Jha, D., Tang, Y., Parsons, K., Sang, F., Klamkin, J., "Deep Neural Networks for Designing Integrated Photonics", Optical Fiber Communication Conference and Exposition (OFC), DOI: https://doi.org/10.1364/OFC.2020.Th1A.6, March 2020.
      BibTeX TR2020-057 PDF
      • @inproceedings{Kojima2020mar,
      • author = {Kojima, Keisuke and TaherSima, Mohammad and Koike-Akino, Toshiaki and Jha, Devesh and Tang, Yingheng and Parsons, Kieran and Sang, Fengqiao and Klamkin, Jonathan},
      • title = {Deep Neural Networks for Designing Integrated Photonics},
      • booktitle = {Optical Fiber Communication Conference and Exposition (OFC)},
      • year = 2020,
      • month = mar,
      • publisher = {OSA},
      • doi = {https://doi.org/10.1364/OFC.2020.Th1A.6},
      • isbn = {978-1-943580-71-2},
      • url = {https://www.merl.com/publications/TR2020-057}
      • }
    •  Tang, Y., Kojima, K., Koike-Akino, T., Wang, Y., Wu, P., TaherSima, M., Jha, D., Parsons, K., Qi, M., "Generative Deep Learning Model for a Multi-level NanoOptic Broadband Power Splitter", Optical Fiber Communication Conference and Exposition (OFC), DOI: 10.1364/OFC.2020.Th1A.1, March 2020, pp. Th1A.1.
      BibTeX TR2020-025 PDF
      • @inproceedings{Tang2020mar,
      • author = {Tang, Yingheng and Kojima, Keisuke and Koike-Akino, Toshiaki and Wang, Ye and Wu, Pengxiang and TaherSima, Mohammad and Jha, Devesh and Parsons, Kieran and Qi, Minghao},
      • title = {Generative Deep Learning Model for a Multi-level NanoOptic Broadband Power Splitter},
      • booktitle = {Optical Fiber Communication Conference and Exposition (OFC)},
      • year = 2020,
      • pages = {Th1A.1},
      • month = mar,
      • publisher = {OSA},
      • doi = {10.1364/OFC.2020.Th1A.1},
      • isbn = {978-1-943580-71-2},
      • url = {https://www.merl.com/publications/TR2020-025}
      • }
    •  Romeres, D., Dalla Libera, A., Jha, D., Yerazunis, W.S., Nikovski, D.N., "Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements", arXiv, DOI: 10.1109/LRA.2020.2977255, February 2020.
      BibTeX arXiv
      • @article{Romeres2020feb,
      • author = {Romeres, Diego and Dalla Libera, Alberto and Jha, Devesh and Yerazunis, William S. and Nikovski, Daniel N.},
      • title = {Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements},
      • journal = {arXiv},
      • year = 2020,
      • month = feb,
      • doi = {10.1109/LRA.2020.2977255},
      • issn = {2377-3766},
      • url = {http://arxiv.org/pdf/2002.10621.pdf}
      • }
    •  Jha, D., Kolaric, P., Romeres, D., Raghunathan, A., Benosman, M., Nikovski, D.N., "Robust Optimization for Trajectory-Centric Model-based Reinforcement Learning", NeurIPS Workshop on Safety and Robustness in Decision Making, December 2019.
      BibTeX TR2019-156 PDF
      • @inproceedings{Jha2019dec2,
      • author = {Jha, Devesh and Kolaric, Patrik and Romeres, Diego and Raghunathan, Arvind and Benosman, Mouhacine and Nikovski, Daniel N.},
      • title = {Robust Optimization for Trajectory-Centric Model-based Reinforcement Learning},
      • booktitle = {NeurIPS Workshop on Safety and Robustness in Decision Making},
      • year = 2019,
      • month = dec,
      • url = {https://www.merl.com/publications/TR2019-156}
      • }
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  • Software Downloads

  • MERL Issued Patents

    • Title: "Vehicle Automated Parking System and Method"
      Inventors: Wang, Yebin; Jha, Devesh
      Patent No.: 9,969,386
      Issue Date: May 15, 2018
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