Siyuan Lu  Siyuan Lu photo         

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Manager and Principal Research Staff Member - Data Intensive Physical Analytics
Thomas J. Watson Research Center, Yorktown Heights, NY USA
  +1dash914dash945dash1809

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Professional Associations

Professional Associations:  American Geophysical Union  |  American Physical Society (APS)  |  Materials Research Society (MRS)


Regular Journal

  1. Hwang, S. Lu, J.-K. Kim, “Bottom-up Estimation and Top-Down Prediction: Solar Energy Prediction Combining Information from Multiple Sources”, Ann. Appl. Stat., in press (2018)
  2. Cui, J. Zhang, B.-M. Hodge, S. Lu, H. F. Hamann, "A Methodology for Quantifying Reliability Benefits from Improved Solar Power Forecasting in Multi-Timescale Power System Operations", IEEE Transactions on Smart Grid, PP, 1 (2017).
  3. Zhang, S. Chattara, S. Lu, A. Madhukar, "Mesa-top single photon emitter arrays: growth, characterization, and simulated optical response of integrated dielectric nanoantenna-waveguide systems", J. Appl. Phys., 120, 243103 (2016).
  4. Zhang, S. Lu, S. Chattara, A. Madhukar, "Triggered single photon emission up to 77K from ordered array of surface curvature-directed mesa-top GaAs/InGaAs single quantum dots", Opt. Express, 24, 29955-29962 (2016).
  5. Badr, L. J. Klein, M. Freitag, C. M. Albrecht, F. J. Marianno, S. Lu, X. Shao, N, Hinds, G. Hoogenboom, H. F. Hamann, “Toward large-scale crop production forecasts for global food security”, IBM Journal of Research and Development, 60, 5:1-11 (2016).
  6. B. Martinez-Anido, B, Botor, A. R. Florita, C. Draxl, S. Lu, H. F. Hamann, B.-M. Hodge, "The Value of Day-Ahead Solar Power Forecasting Improvement", Solar Energy, 129, 192-203 (2016).
  7. Khabibrakhmanov, S. Lu, H. F. Hamann, K. Warren, “On the usefulness of solar energy forecast in the presence of asymmetric costs of errors”, IBM Journal of Research and Development, 60, 7:1-6 (2016).
  8. Zhang, B.-M. Hodge, S. Lu, H. F. Hamann, B. Lehman, J. Simmons, E. Campos, V. Banunarayanan, J. Black,J. Tedesco, "Baseline and Target Values for Regional and Point Solar Power Forecasts: Toward Improved Solar Power Forecasting", Solar Energy, 122, 804-819 (2015).
  9. F. Hamann, S. Lu, “Situation-dependent, machine learning based multi-model blending for improved renewable energy forecasting and beyond”, SPIE Newsroom, Nov 2015.
  10. Zhang, A. Florita, B.-M. Hodge, S. Lu, H. F. Hamann. V. Banunarayanan, Anan M. Brockway, “A suite of metrics for assessing the performance of solar power forecasting”, Solar Energy, 111, 157-175 (2015).
  11. Lingley, S. Lu, A. Madhukar, “The Dynamics of energy and charge transfer in lead sulfide quantum dots solids”, J. Appl. Phys. 115, 084302 (2014).
  12. Zhang, S. Lu, Z. Lingley, A. Madhukar, “Nanotemplate-Directed InGaAs/GaAs Quantum Dots: Towards Single Photon Emitter Arrays”, J. Vac. Sci. Technol. B, 32, 02C106 (2014).
  13. Lingley, K. Mahalingam, S. Lu, G. J. Brown, A. Madhukar “Nanocrystal - Semiconductor Interface: Atomic-Resolution Cross-Sectional Transmission Electron Microscope Study of Lead Sulfide Nanocrystal Quantum Dots on Crystalline Silicon”, Nano Research, 7, 219-227 (2014).
  14. Huang, S. Lu, P. Chang, K. Banerjee, R. Hellwarth, J. Lu “Structural and Optical Verification of Residual Strain Effect in Single Crystalline CdTe Nanowires”, Nano Research, 7, 228-235 (2014).
  15. Gershon, B. Shin, T. Gokmen, S. Lu, N. Bojarczuk, and S. Guha, “Relationship between Cu2ZnSnS4 quasi donor-acceptor pair density and solar cell efficiency”, Appl. Phys. Lett. 103, 193903 (2013).
  16. Gershon, B. Shin, N. Bojarczuk, T. Gokmen, S. Lu, and S. Guha, “Photoluminescence characterization of a high-efficiency Cu2ZnSnS4 device”, J. Appl. Phys., 114, 154905 (2013).
  17. Lu, A. Madhukar, “Inducing repetitive action potential firing in neurons via synthesized photoresponsive nanoscale cellular prostheses”, Nanomedicine Nanotechnology, Biology, and Medicine, 9, 293-301 (2013).
  18. Lingley, S. Lu, A. Madhukar, “A High Quantum Efficiency Preserving Approach to Ligand Exchange on Lead Sulfide Quantum Dots and Interdot Resonant Energy Transfer”, Nano Lett. 11, 2887-2891 (2011).
  19. K. Lee (I), S. Lu (II), A. Madhukar, “Real-time Dynamics of Ca2+, Caspase-3/7, and Morphological Changes in Retinal Ganglion Cell Apoptosis under Elevated Pressure”, PLoS ONE, 5, e13437 (2010). (One of the two primary authors of equal contribution.)
  20. Lu, A. Madhukar, “Cellular Prostheses: Functional Abiotic Nanosystems to Probe, Manipulate, and Endow Function in Live Cells”, Nanomedicine Nanotechnology, Biology, and Medicine. 6, 409-418 (2010).
  21. Lu, Z. Lingley, T. Asano, D. Harris, T. Barwicz, S. Guha, A. Madhukar, “Photocurrent Induced by Nonradiative Energy Transfer from Nanocrystal Quantum Dots to Adjacent Silicon Nanowire Conducting Channels: Toward a New Solar Cell Paradigm”, Nano Lett. 9, 4548-4552 (2009).
  22. Lu, A. Madhukar, “Nonradiative Resonant Excitation Transfer from Nanocrystal Quantum Dots to Adjacent Quantum Channels”, Nano Lett., 7, 3443-3451 (2007).
  23. Lu, A. Bansal, W. Soussou, T. W. Berger, A. Madhukar, “Receptor-ligand based specific cell adhesion on solid surfaces: hippocampal neuronal cells on bilinker functionalized glass”, Nano Lett. 6, 1977-1981 (2006).
  24. Madhukar, S. Lu, A. Konkar, Y. Zhang, M. Ho, S. M. Hughes, A. P. Alivisatos, “Integrated semiconductor nanocrystal and epitaxical nanostructure systems: Structural and optical behavior”, Nano Lett. 5, 479-482 (2005).
  25. Konkar, S. Lu, A. Madhukar, “Semiconductor nanocrystal quantum dots on single crystal semiconductor substrates: High resolution transmission electron microscopy”, Nano Lett. 5, 969-973 (2005).
  26. Lu, X. Ma and Y. Shen, “Measuring rotating substrate temperature by laser”, Optical Instruments, 22, 3-7 (2000).

 

Conference Proceeding

  1. Hwang, S. Lu, J.-K. Kim, “Bottom-up estimation and top-down prediction: Solar energy prediction combining information from multiple sources”, Proceeding of the Pacific Rim Statistical Conference for Production Engineering, 3-14 (2018).
  2. M. Albrecht, M. Freitag, T. G. van Kessel, S. Lu, H. F. Hamann, “Event clustering & event series characterization on expected frequency”, Proceeding of 2017 IEEE International Conference on Big Data (Big Data), 4536-4541 (2017).
  3. Zhuk, T. Tchrakian, A. Akhriev, S. Lu, H. Hamann, "Dynamic cloud motion forecasting from satellite images", Proceeding of 2017 IEEE 56th Annual Conference on Decision and Control (CDC), 3107-3112 (2017).
  4. Chattaraj, J. Zhang, S. Lu, A. Madhukar, "On-chip quantum optical networks comprising co-designed spectrally uniform single photon source array and dielectric light manipulating elements", Photonics Society Summer Topical Meeting Series IEEE, 97-98, (2017).
  5. Feng, M. Cui, M. Lee, J. Zhang, B.-M. Hodge, S. Lu, H. F. Hamann, “Short-term Global Horizontal Irradiance Forecasting Based on Sky Imaging and Pattern Recognition”, IEEE Power & Energy Society General Meeting (2017).
  6. Lu, X. Shao, M. Freitag, L. J. Klein, J. Renwick, F. J. Marianno, C. Albrecht, H. F. Hamann, "IBM PAIRS Curated Big Data Service for Accelerated Geospatial Data Analytics and Discovery", Proceeding of 2017 IEEE International Conference on Big Data (Big Data), 2672-2675 (2016).
  7. Shao, S. Lu, T. G. van Kessel, H. F. Hamann, L. Daehler, J. Cwagenberg, A. Li, "Solar Irradiance Forecasting by Machine Learning for Solar Car Races", ", Proceeding of 2017 IEEE International Conference on Big Data (Big Data), 2209-2216 (2016).
  8. Li, Q. Sun, B. Lehman, S. Lu, H. F. Hamann, J. Simmons, J. Black, A machine-learning approach for regional photovoltaic power forecasting, Proceeding of Power and Energy Society General Meeting (PESGM), (2016).
  9. Zhang, S. Chattaraj, S. Lu, A. Madhukar, “On-chip Integrable Spectrally-Uniform Quantum Dot Single Photon Emitter Array with Multifunctional Dielectric Light Manipulation Elements: Towards Quantum Information Processing”, Proceeding of 2016 IEEE Photonic Society Summer Topical Meeting, MB4.2, (2016).
  10. Shao, S. Lu, H. F. Hamann, “Solar radiation forecast with machine learning”, Proceeding of the 23rd International Workshop on Active-Matrix Flatpanel Displays and Devices, 19-22 (2016).
  11. J. Klein, F. J. Marianno, C. M. Albrecht, M. Freitag, S. Lu, N. Hinds, X. Shao, S. B. Rodriguez, H. F. Hamann, “PAIRS: A scalable geo-spatial data analytics platform”, Proceeding of the IEEE International Conference on Big Data, page 1290-1298 (2015).
  12. A. Chen, A. Wishwanath, S. Sathe, S. Kalynaraman, S. Lu, "Understanding the Performance of Solar PV Systems Using Data-Driven Analytics, Smart Grid Technologies - Asia (ISGT ASIA), 2015 IEEE Innovative, page 1-6 (2015).
  13. W Y. Cheung, J. Zhang, A. Florita, B.-M. Hodge, Lu. H. Hamann, Q. Sun, B. Lehman, "Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis", Proceeding of the 5th International Workshop on Integration of Solar Power into Power Systems (2015).
  14. Lu, Y. Hwang, I. Khabibrakhmanov, F. J. Marianno, X. Shao, J. Zhang, B.-M. Hodge, H. F. Hamann, “Machine Learning Based Multi-Physical-Model Blending for Enhancing Renewable Energy Forecast – Improvement via Situation Dependent Error Correction.” Proceeding of European Control Conference 2015, pp. 283 - 290 (2015).
  15. Chen, X. Xu, P. Li, S. Lu, S. Huang, W. Lu, K. Brown “GeoMix: Scalable Geoscientific Array Data Management”, Proceedings of the Industrial Track of the 13th ACM/IFIP/USENIX International Middleware Conference, Article No. 1 (2013).
  16. Zhang, B.-M. Hodge, A. Florita , S. Lu, H. F. Hamann. V. Banunarayanan, “Metrics for Evaluating the Accuracy of Solar Power Forecasting”, Proceeding of 3rd International Workshop on Integration of Solar Power into Power Systems (2013).
  17. Konkar, S. Lu, A. Madhukar, S.M. Hughes, and A.P. Alivisatos, "Integration of Nanocrystal Quantum Dots With Crystalline Semiconductor Substrates: Structure, Stability, and Optical Response", Mater. Res. Soc. Symp. Proc.,854E, U.4.7.; (www.mrs.org, 2005).
  18. Lu, X. Ma, and Y. Shen, “Measuring rotating substrate temperature by laser”, Proc. SPIE, 4086, 860-863 (2000).

 

Issued Patents

  1. F. Hamann, S. Lu, “Multifunctional sky camera system for total sky imaging and spectral radiance measurement”, US Patent 9,781,363 (2017)
  2. B. Chang, H. F. Hamann, S. Lu, R. Muralidhar, T. G. van Kessel, “Leveraging Air/Water Current Variability for Sensor Network Verification and Source Localization”, US Patent 9,766,220 (2017).
  3. N. Chatterjee, H. F. Hamann, S. Km, S. Lu, K. V. R. M. Kota, “Scheduling cost efficient datacenter load distribution”, US Patent 9654414 (2017).
  4. F. Hamann, S. Lu, “Multifunctional sky camera system for total sky imaging and spectral radiance measurement”, US Patent 9,565,377 (2017)
  5. F. Hamann, Y. Hwang, T. G. van Kessel, I. K. Khabibrakhmanov, S. Lu, R. Muralidhar, “Multi-model blending”, US Patent 9,471,884 (2016).
  6. Lu, A. Madhukar, S. Humayun, “Functional Abiotic Nanosystems”, US Patent 8,399,751 (2013).

 

Patent Applications

  1. Guha, S. Lu, T. G. van Kessel, “Hybrid Solar Thermal and Photovoltaic Energy Collection”, US Patent Application 20180083568 (2018).
  2. Hamann, L. Klein, S. Lu, T. G. van Kessel, “Method of Solar Power Prediction”, US Patent Application 20180047170 (2018).
  3. Hamann, S. Lu, “Techniques to improve global weather forecasting using model blending and historical GPS-RO dataset”, US Patent Application 20180038994 (2018).
  4. M. Albrecht, J. B. Chang, L. Klein, S. Lu, F. J. Marianno, “Satellite-based location identification of methane-emitting sites”, US Patent Application 20180039885 (2018).
  5. Hamann, I. Khabibrakhamanov, Y. Kim, S. Lu, “Solar forecasting using machine learned cloudiness classification”, US Patent Application 20180039891 (2018).
  6. P. Cripriani, I. Khabibrakhmanov, Y. Kim, S. Lu, A. P. Praino, “Predicting solar Power Generation using Semi-Supervised Learning”, US Patent Application 20170286838 (2017).
  7. B. Chang, H. F. Hamann, L. Klein, S. Lu, “Multimodel analyte sensor network”, US Patent Application 2017241936 (2017).
  8. F. Hamann, S. Lu, “Situation-dependent Blending Method for Predicting the Progression of Diseases or their Response to Treatment”, US Patent Application 20170169180 (2017)
  9. B. Chang, H. F. Hamann, S. Lu, X. Shao “3D Micro and Nanoheater Design for Ultra-Low Power Gas Sensors”, US Patent Application 20170153198 (2017).
  10. F. Hamann, Y. Hwang, L. Klein, J. Lenchner, S. Lu, F. J. Marianno, G. J. Tesauro, T. G. van Kessel, “Parameter-dependent Model Blending with Multi-expert based Machine Learning and Proxy Sites”, US Patent Application 20170017896 (2017).
  11. J. Chey; H. F. Hamann, L. Klein, S. Lu, R. Nagy, “Reconfigurable Gas Sensor Architecture with a High Sensitivity at Low Temperature”, US Patent Application, 20170024992 (2017).
  12. Lu, Hendrik Hamann, “Machine Learning Approach for Analysis and Prediction of Cloud Particle Size and Shape Distribution”, US Patent Application 20140324352 (2014).

 

Abstracts (Presenting and First Author only)

  1. (Invited) M. Freitag, Lu, “Geospatial Analytics Powered by IBM Pairs Big-data Platform”, INFORMS 2017, Houston, Texax, Oct 22-25, 2017.
  2. (Invited) Lu, “IBM PAIRS - A Big Physical Data Service to Accelerate Analytics and Discovery”, The InfoAg Conference, St. Louis, July 25-27, 2017.
  3. Lu, X. Shao, M. Freitag, L. J. Klein, J. Renwick, F. J. Marianno, C. Albrecht, H. F. Hamann, "IBM PAIRS Curated Big Data Service for Accelerated Geospatial Data Analytics and Discovery", the 1st IEEE International Workshop on Big Spatial Data (BSD) in conjunction with 2016 IEEE International Conference on Big Data, Washington DC, Dec 5-9, 2016.
  4. (Invited) Lu, “Big Data and machine learning for renewable forecasting”, UVIG Forecasting Workshop, Denver, CO, Sep 27-29, 2016
  5. (Invited) Lu “Self-learning weather modeling: Application of big physical data in renewable energy forecasting”, National Renewable Energy Laboratory, Golden, CO, May 24, 2016.
  6. Lu, Y. Hwang, I. Khabibrakhmanov, X. Shao, H. F. Hamann, “A Two-Dimensional Gridded Solar Forecasting System using Situation-Dependent Blending of Multiple Weather Models”, 2015 American Geophysical Union Fall Meeting, San Francisco, December 14-18, 2015
  7. (Invited) Lu, Y. Hwang, I. Khabibrakhmanov, F. J. Marianno, X. Shao, J. Zhang, B.-M. Hodge, H. F. Hamann, “Machine Learning Based Multi-Physical-Model Blending for Enhancing Renewable Energy Forecast – Improvement via Situation Dependent Error Correction.” European Control Conference 2015, Linz, Austria, July 15-17, 2015.
  8. Lu, Y. Hwang, Xiaoyan Shao, H. Hamann, “Towards Gridded Foundational Solar Forecast of Enhanced Accuracy: Weather Situation Dependent Forecast Error and Machine-Learnt Multi-Model Blending”, 3rd International Conference Energy & Meteorology, Boulder, CO, Jun 22-26, 2015.
  9. Lu, X. Shao, Y. Hwang, I. Khabibrakhmanov, H. F. Hamann, “Improvement of Solar Irradiance Forecast using Machine Learning”, 9th Annual Machine Learning Symposium, New York City, NY, March 13, 2015.
  10. (Invited) Lu, “Situation Dependent Machine Learning based Multi-Model Blending for Enhancing Renewable Energy Forecasting”, PV America 2015, Boston, MA, March 9-10, 2015.
  11. Lu, Y. Hwang, I. Khabibrakhmanov, H. Dang, T. van Kessel, F. Marianno, X. Shao, H. Hamann, “Machine learning based multi-model blending for enhancing renewable energy forecasting”, Meteorological Society 2015 Annual Meeting, Pheonix, AZ, Jan 5-8, 2015.
  12. (Invited) Lu “Machine-learning based multi-model blending – A versatile approach to enhancing renewable energy forecasting”, SEAS Colloquium, Columbia University, New York, NY, May 29, 2014.
  13. Lu, J. Lenchner, G. J. Tesauro, C. M. Corcoran, F. J. Marianno, J. Zhang, B.-M. Hodge, E. Campos, H. F. Hamann, “A multi-scale solar energy forecast platform based on machine-learned adaptive combination of expert systems”, American Meteorological Society 2014 Annual Meeting, Atlanta, GA, Feb 2-6, 2014
  14. A. Bermudez, S. Lu, M. A. Schappert, T. G. van Kessel, H. F. Hamann, “Improvements in short-term Solar Energy Forecasting”, American Meteorological Society 2014 Annual Meeting, Atlanta, Feb 2-6, 2014
  15. Lu, A. Madhukar, Modeling Photoactive Nanoscale Cellular Prosthesis Induced Action Potential Firing in Retinal Ganglion Cells, Biophysical Society Annual Meeting 2013, Philadelphia, NJ, February 2-6, 2013.
  16. Lu, Z. Lingley, A. Madhukar, “Energy/Charge Transfer Dynamics in Close-Packed Nanocrystal QD Thin Films and QD/Substrate System”, 7th International Conference on Quantum Dots, Santa Fe, NM, May 13-18, 2012.
  17. Lu, J. K. Lee, A. Madhukar, “Ca2+ Dynamics in Apoptosis: Real-Time Data and Mathematical Modeling”, Biophys. J. 102, 628a (2012).
  18. Lu, J. K. Lee, A. Madhukar, “Real-time Dynamics of Ca2+, Phosphatidylserine, Caspase-3/7, and Morphological Changes in Apoptosis: Retinal Ganglion Cells under Elevated Pressure”, Biophys. J. 100, S41a (2011).
  19. Lu, A. Madhukar, “Nanoscale Photovoltaic Prosthesis for Inducing Repetitive Action Potential Firing in Nerve Cells”, Biophys. J. 100, S95a (2011).
  20. Lu, Z. Lingley, T. Asano, T. Barwicz, S. Guha, A. Madhukar, “Photocurrent Induced by Non-radiative Energy Transfer from Nanocrystal Quantum Dots to Adjacent Nanowire Conducting Channels: Towards a New Solar Cell Architecture”, Materials Research Society Fall Meeting 2009, Boston, MA, November 30 – December 4, 2009.
  21. Lu, A. Madhukar, “Functional Abiotic Nanosystems: Agents to Probe, Manipulate, and Endow Function in Live Cells”, Materials Research Society Fall Meeting 2009, Boston, MA, November 30 – December 4, 2009.
  22. Lu, A. Madhukar, “Functional Abiotic Nanosystems: Agents to Probe, Manipulate, and Endow Function in Live Cells”, Inaugural Conference of the American Society for Nanomedicine (ASNM), Potomac, MD, October 22-25, 2009.
  23. (Invited) Lu, “Examining Cell-to-Cell Variation in Intracellular Biochemical Response in Live Cells under Controlled Stress: A New Paradigm”, Physics Department Colloquium, University of Southern California, Los Angles, CA, March 23, 2009.
  24. (Invited) Madhukar, S. Lu, M. Humayun, “Disease and Translational Nanoscience Platform Paradigms: A Matter of Inversely Related Times”, Translational Nanoscience Conference, Los Angeles, CA, March 20 – 21, 2008.
  25. (Invited) Lu, J. K. Lee, Z. Lingley, M. Humayun, A. Madhukar, “Optical Probing of Cell Physiological Changes under Stress”, Biomedical Engineering Society Annual Meeting 2007, Los Angeles, CA, September 27 – 29, 2007.
  26. Lu, A. Bansal, A. Madhukar, H. Lin, R. Datar, “Simultaneous AFM & NSOM studies of quantum dot labeled cancer cells”, Materials Research Society Spring Meeting 2006, San Francisco, CA, April 17 – 21, 2006.
  27. Lu, A. Madhukar, “Hot Excitation Transfer From Nanocrystals into Semiconductor Substrates”, Materials Research Society Spring Meeting 2006, San Francisco, CA, April 17 – 21, 2006.
  28. Lu, A. Madhukar, “Optical property of nanocrystals on crystalline semiconductor substrate: Evidence for energy transfer”, American Physical Society March Meeting, Los Angeles, CA, March 21 – 25, 2005.