2025

• Mo, Y., Lohani, S., Thornton, M.A., "Distorted Edge Feature Extraction using Quantum Convolutional Structure", IEEE DCAS 2025. (Accepted)

• Bart, M.P., Dawanse, S., Savino, N.J., Tran, V., Wang, T., Lohani, S., Nefissi, F., Bassène, P., N'Gom, M. and Glasser, R.T. Classification of Single Photons in Higher-Order Spatial Modes via Convolutional Neural Networks. Optics Letter, 50, 2820-2823 (2025).

2024

• Liang, X., Lohani, S., Lukens, J.M., Kirby, B.T., Searles, T.A. and Law, K.J., 2024. SMC Is All You Need: Parallel Strong Scaling. arXiv:2402.06173.

• Larocque, H., Vitullo, D.L., Sludds, A., Sattari, H., Christen, I., Choong, G., Prieto, I., Leo, J., Zarebidaki, H., Lohani, S. and Kirby, B.T., 2024. Photonic Crystal Cavity IQ Modulators in Thin-Film Lithium Niobate. ACS Photonics, 11(9), pp.3860-3869.

• Vitullo, D.L., Lohani, S., Larocque, H., Sludds, A., Sattari, H., Christen, I., Choong, G., Prieto, I., Leo, J., Zarebidaki, H. and Soltani, M., 2024, March. Optimized encoding for coherent communication using photonic crystal cavity IQ modulators in thin film lithium niobate. In Laser Resonators, Microresonators, and Beam Control XXVI (Vol. 12871, pp. 28-37). SPIE.

[Invited Paper]

2023

• Lohani, S., Lukens, J.M., Davis, A.A., Khannejad, A., Regmi, S., Jones, D.E., Glasser, R.T., Searles, T.A. and Kirby, B.T., 2023. Demonstration of machine-learning-enhanced Bayesian quantum state estimation. New Journal of Physics, 25(8), p.083009.

• Lohani, S., Regmi, S., Lukens, J.M., Glasser, R.T., Searles, T.A. and Kirby, B.T., 2023. Dimension-adaptive machine learning-based quantum state reconstruction. Quantum Machine Intelligence, 5(1), p.1. 

[Part of a Collection: Quantum Techniques in Machine Learning]

• Leamer, J.M., Zhang, W., Savino, N.J., Saripalli, R.K., Lohani, S., Glasser, R.T. and Bondar, D.I., 2023. Classical optical analogue of quantum discord. The European Physical Journal Special Topics, 232(20), pp.3345-3351.

• Bart, M.P., Savino, N.J., Regmi, P., Cohen, L., Safavi, H., Shaw, H.C., Lohani, S., Searles, T.A., Kirby, B.T., Lee, H. and Glasser, R.T., 2023. Deep learning for enhanced free-space optical communications. Machine Learning: Science and Technology, 4(4), p.045046.

• Lohani, S., Liu C., Chen Y., Kirby B.T., Economou S. and Searles T. A. Dec. 2023. Control variational quantum algorithm meets artificial intelligence. Workshop on Innovative Nanoscale Devices and Systems (WINDS). WINDS 2023.

• Regmi S., Davis, A., Blackwell A., Khannejad A., Jones D.E., Glasser R.T., Lukens J.M., Lohani, S., Kirby B.T., Searles T., Dec. 2023. Data-informed prior for Bayesian state tomography. Workshop on Innovative Nanoscale Devices and Systems (WINDS). WINDS 2023.

• Regmi S., Blackwell, A., Khannejad A., Lohani, S., Lukens, J.M., Glasser R., Kirby B., Searles T., 2023. Bayesian quantum state reconstruction with a learning-based tuned prior. Quantum 2.0 (pp. QM4B-3). Optica Publishing Group. ISBN: 978-1-957171-27-2.

• Leamer, J.M., Zhang, W. Savino N.J., Saripalli, R.K., Lohani, S., Glasser R.T., Bondar D.I. 2023. A classical optical testbed for quantum discord applications. Quantum and Nonlinear Optics X, Paper 12775-31, SPIE Photonics Asia. https://spie.org/spie-cos-photonics-asia.

• Lohani, S., Lukens J.M., Davis A Khannejad A., Regmi S., Jones D.E., Glasser R.T., Kirby B.T., Searles T. (Oct. 2023) Quantum state tomography: a machine learning perspective. 25th annual SQuInT Workshop.

2022

• Lohani, S., Lukens, J.M., Glasser, R.T., Searles, T.A. and Kirby, B.T., 2022. Data-centric machine learning in quantum information science. Machine Learning: Science and Technology, 3(4), p.04LT01.

• Savino, N.J., Lohani, S. and Glasser, R.T., 2022. Deep learning for eavesdropper detection in free-space optical ON-OFF keying. Optics Continuum, 1(12), pp.2416-2425.

• Lohani, S., Lukens, J.M., Jones D.E., Searles T.A., Glasser R.T. and Kirby B.T., 2022. Machine Learning and Bayesian mean estimation meet biased quantum state distributions. CLEO: Applications and Technology (pp. AW4P-2). Optica Publishing Group. DOI: 10.1364/CLEO AT.2022.AW4P.2.

• Lohani, S., Lukens J. M., Glasser R. T., Kirby B. T. and Searles T. A. 2022. Data-centric artificial intelligence in quantum information science. Workshop on Innovative Nanoscale Devices and Systems (WINDS). ISBN 978-3-9504738-4-1.

• Regmi S., Lohani, S., Lukens J., Glasser R., Kirby B and Searles T. 2022. Dimension-adaptive quantum state tomography with machine learning. Workshop on Innovative Nanoscale Devices and Systems (WINDS). ISBN 978-3-9504738-4-1.

• Lohani, S., Blackwell A., and Searles. T. 2022. Quantum Permutation and State Tomography. Poster at C2QA All-Hands Meeting, Yale University. c2qaallhandsmeeting.

• Regmi S., Lohani, S., Lukens J., Glasser R., Kirby B. and Searles T. 2022. Quantum state reconstruction for systems with different dimensions using machine learning. Prairie Section APS Fall 2022 Meeting. Abstract: F01.00007.

• Lohani, S., Lukens J.M., Jones D.E., Searles T.A., Glasser R.T. and Kirby B.T. A Hardware-aware approach to improving quantum state tomography. 2022. Poster 34. Estimation and Measurements-17th conference on The Theory of Quantum Computation, Communication and Cryptography (TQC).

• Lohani, S., Lukens J., Glasser R., Searles T., and Kirby B. 2022. Data-centric approach to machine learning in quantum state reconstruction. J. P. Dowling Memorial Conference on Quantum Science and Technology. A Celebration of the life and work of World-Renowned Professor Jonathan P. Dowling (1955-2020).

• Leamer, J.M., Zhang, W. Savino N.J., Saripalli, R.K., Lohani, S., Glasser R.T., Bondar, D.I. 2022. Classical optical analog of quantum discord. J. P. Dowling Memorial Conference on Quantum Science and Technology. A Celebration of the life and work of World-Renowned Professor Jonathan P. Dowling (1955-2020).

• Regmi S., Lohani, S., Lukens J., Glasser R., Searles T., and Kirby B. 2022. Quantum state tomography for systems with different dimension using neural network. Jonathan P. Dowling Memorial Conference on Quantum Science and Technology. A Celebration of the life and work of World-Renowned Professor Jonathan P. Dowling (1955-2020).

• Lohani, S., Lukens J.M., Jones D.E., Searles T.A., Glasser R. T. and Kirby B.T., 2022. Quantum state reconstruction with biased distributions of quantum states. Bulletin of the American Physical Society. Abstract: N35.00003.

• Blackwell A., Gomez M., Danaci O., Lohani, S., Kirby B., Glasser R., and Searles T. 2022. Demonstrating a Quantum Permutation Algorithm with Higher Qubit Near-term Intermediate Scale Quantum Processors. Bulletin of the American Physical Society. Abstract: M40.00002.

• Lohani, S., Lukens J.M., Jones D.E., Searles T.A., Glasser R. T. and Kirby B.T. Learning from biased distributions of quantum states. Poster 372, 25th Annual Conference of Quantum Information Processing, Pasadena, CA. QIP.

2021

• Lohani, S., Lukens, J.M., Jones, D.E., Searles, T.A., Glasser, R.T. and Kirby, B.T., 2021. Improving application performance with biased distributions of quantum states. Physical Review Research, 3(4), p.043145. 

[IBM-QISKIT Coverage]

This research has been featured in the IBM Quantum – Qiskit blog and official Twitter page. “A Hardware-Aware Approach to Improving Quantum State Tomography”, Feb 15, 2022, Qiskit.

• Lohani, S., Searles, T.A., Kirby, B.T. and Glasser, R.T., 2021. On the experimental feasibility of quantum state reconstruction via machine learning. IEEE Transactions on Quantum Engineering, 2, pp.1-10.

• Danaci, O., Lohani, S., Kirby, B.T. and Glasser, R.T., 2021. Machine learning pipeline for quantum state estimation with incomplete measurements. Machine Learning: Science and Technology, 2(3), p.035014.

• Bhusal, N., Lohani, S., You, C., Hong, M., Fabre, J., Zhao, P., Knutson, E.M., Glasser, R.T. and Magaña‐Loaiza, O.S., 2021. Spatial mode correction of single photons using machine learning. Advanced Quantum Technologies, 4(3), p.2000103.

[Editor’s Pick – Featured on the Front Cover]

This research has been selected to be featured on the front cover of the issue: Advanced Quantum Technologies, Vol. 4, No. 3, March 2021.

• Lohani, S., Kirby B.T., Glasser R. and Searles T.A., 2021. On the efficacy of classical deep learning methods on quantum information science. In Laser Science (pp. JW7A-113). OSA. DOI: 10.1364/FIO.2021.JW7A.113.

• Lohani, S., Lukens J.M., Jones D.E., Searles T.A., Glasser R. T. and Kirby B.T., 2021. Biased distributions of random quantum states for high-performance quantum state reconstruction. Workshop on Innovative Nanoscale Devices and Systems (WINDS). November 28 – December 3. ISBN 978-3-9504738-4-1.

• Savino, N.J., Bart M.P., Regmi P., Lohani, S., Cohen L., Wylie S.K., Shaw H.C., Safavi H., Lee H., Searles T.A., Kirby B.T., and Glasser R.T., 2021. Bit-Error rate reduction of free-space optical on-off keying with atmospheric effects. In Frontiers in Optics (pp. JTh5A-137). OSA. DOI: 10.1364/FIO.2021.JTh5A.137.

• Lohani, S., Kirby B. T., Glasser R. T. and Searles T. A. 2021. Scaling properties of pre-trained neural-network-based quantum state tomography, Quantum Techniques in Machine Learning (QTML), pp. 6-8. https://quantummachinelearning.org.

• Glasser R.T., Lohani, S., Kirby B.T., Brodsky, M., Danaci O. and Searles T.A., 2021, March. Machine learning for enhancing quantum state estimation. In Optical and Quantum Sensing and Precision Metrology (Vol. 11700, p. 117001D). International Society for Optics and Photonics. DOI: 10.1117/12.2586865.

2020 and Before

• Lohani, S., Kirby, B.T., Brodsky, M., Danaci, O. and Glasser, R.T., 2020. Machine learning assisted quantum state estimation. Machine Learning: Science and Technology, 1(3), p.035007. 

[General Press Coverage]

Top 5 most downloaded articles in the journal in 2020, with an Altmetric score of 69. In the top 5% of all research outputs scored by Altmetric.

• Lohani, S., Knutson, E.M. and Glasser, R.T., 2020. Generative machine learning for robust free-space communication. Communications Physics, 3(1), p.177.

• Lohani, S. and Glasser, R.T., 2020. Coherent optical communications enhanced by machine intelligence. Machine Learning: Science and Technology, 1(3), p.035006.

• Lohani, S., Knutson, E.M., Zhang, W. and Glasser, R.T., 2019. Dispersion characterization and pulse prediction with machine learning. OSA Continuum, 2(12), pp.3438-3445.

• Lohani, S., Knutson, E.M., O’Donnell, M., Huver, S.D. and Glasser, R.T., 2018. On the use of deep neural networks in optical communications. Applied optics, 57(15), pp.4180-4190.

• Reilly, A.M., Cooper, R.I., Adjiman, C.S., Bhattacharya, S., Boese, A.D., Brandenburg, J.G., Bygrave, … Lohani, S., … P.J., Bylsma, R., Campbell, J.E., Car, R. and Case, D.H., 2016. Report on the sixth blind test of organic crystal structure prediction methods. Acta Crystallographica Section B: Structural Science, Crystal Engineering and Materials, 72(4), pp.439-459.

• Savino N.J., Lohani, S., and Glasser R.T., 2020, September. Simulated Eavesdropper Detection in Free-Space Optics ON-OFF Keying with Deep Learning. In Frontiers in Optics (pp. FTh5E-6). OSA. DOI: 10.1364/FIO.2020.FTh5E.6.

• Lohani, S., Savino N.J. and Glasser R.T., 2020, September. Free-space optical ON-OFF keying communications with deep learning. In Frontiers in Optics (pp. FTh5E-4). OSA. DOI: 10.1364/FIO.2020.FTh5E.4.

• Danaci O., Lohani, S., Kirby B.T., Brodsky M. and Glasser R.T., 2020, September. Quantum State Estimation from Partial Tomography Data Using a Stack of Machine Learning Models and Imputation. In Frontiers in Optics (pp. FTu8D-5). OSA. DOI: 10.1364/FIO.2020.FTu8D.5.

• Lohani, S. and Glasser R.T., 2019, September. Robust free space oam communications with unsupervised machine learning. In Frontiers in Optics (pp. FTu5B-3). OSA. DOI: 10.1364/FIO.2019.FTu5B.3.

[Incubic-Milton Chang Award] [Emil Wolf Outstanding Finalist Award]  

• Bhusal, N., Lohani, S., You C., Lambert A., Knutson E.M., Dowling J.P., Glasser R.T. and Magaña-Loaiza, O.S., 2019, September. Artificial Neural Networks for Turbulence Correction of Structured Light. In Frontiers in Optics (pp. FTu5B-2). OSA. DOI: 10.1364/FIO.2019.FTu5B.2.

• Knutson E.M., Lohani, S., Danaci O., Huver S.D. and Glasser R.T., 2016, September. Deep learning as a tool to distinguish between high orbital angular momentum optical modes. In Optics and Photonics for Information Processing X (Vol. 9970, p. 997013). International Society for Optics and Photonics. DOI: 10.1117/12.2242115.

• Lohani, S., Knutson E., Tkach, S., Huver, S., Glasser R. and Deep Science AI Collaboration, 2017, March. Enhancing optical communication with deep neural networks. In APS March Meeting Abstracts (Vol. 2017, pp. H27-002). Abstract: H27.00002.

Acknowledged:

• Haldar, S., Barge, P.J., Cheng, X., Chang, K.C., Kirby, B.T., Khatri, S., Wong, C.W. and Lee, H., 2024. Policies for multiplexed quantum repeaters: theory and practical performance analysis. arXiv:2401.13168.

• Greenwood, A.C., Wu, L.T., Zhu, E.Y., Kirby, B.T. and Qian, L., 2023. Machine-Learning-Derived Entanglement Witnesses. Physical Review Applied, 19(3), p.034058. DOI: 10.1103/PhysRevApplied.19.034058.

• Ghimire, S.N. and Neupane, S., 2022. Narratives in Kailash Satyarthi’s Nobel Peace Prize lecture: an analysis of rhetorical agency. Humanities and Social Sciences Communications, 9(1), pp.1-10. DOI: 10.1057/s41599-022-01376-1.