Tarek Zohdi

  1. Zohdi, T. I. (2003). Genetic design of solids possessing a random-particulate microstructure. Philosophical Transactions of the Royal Society: Mathematical, Physical and Engineering Sciences. Vol: 361, No: 1806, 1021-1043.
  2. Zohdi, T. I. (2003). Computational design of swarms. The International Journal of Numerical Methods in Engineering. 57, 2205-2219.
  3. Zohdi, T. I. (2009) Mechanistic modeling of swarms. Computer Methods in Applied Mechanics and Engineering. Volume 198, Issues 21-26, Pages 2039-2051.
  4. Zohdi, T. I. (2012) Modeling and simulation of the optical response rod-functionalized reflective surfaces. Computational Mechanics. Volume 50, Issue 2, pp 257-268.
  5. Zohdi, T. I. (2013) Modeling electrical power absorption and thermally-induced biological tissue damage. Biomechanics and Modeling in Mechanobiology.
  6. Zohdi, T. I. (2013). Rapid simulation of laser processing of discrete particulate materials. Archives of Computational Methods in Engineering. pages 1-17.
  7. Gutierrez, M. P. and Zohdi, T. I. Effective Reflectivity and Heat Generation in Sucrose and PMMA Mixtures. Energy and Buildings 71 (2014) 95–103
  8. Campello, E. M. B. and Zohdi, T. I. (2014). A computational framework for simulation of the delivery of substances into cells. International Journal for Numerical Methods in Biomedical Engineering. Volume 30, Issue 11, pp. 1132-1152.
  9. Zohdi, T. I. (2015). Modeling and simulation of coupled cell proliferation and regulation in heterogeneous tissue. Annals of Biomedical Engineering. 43(7):1666-79.
  10. Zohdi, T. I. (2015). On necessary pumping pressures for industrial process-driven particle-laden fluid flows. Journal of Manufacturing Science and Engineering, ASME.
  11. Zohdi, T. I. (2015). Modeling and simulation of laser processing of particulate-functionalized materials. Archives of Computational Methods in Engineering.
  12. Casas, G., Mukherjee, D., Celigueta, M. A., Zohdi, T. I. and Onate, E. (2015). A modular, partitioned, discrete element framework for industrial grain distribution systems with rotating machinery. Computational Particle Mechanics.
  13. Zohdi, T. I. (2016). An agent-based computational framework for simulation of competing hostile planet-wide populations. Computer Methods in Applied Mechanics and Engineering.
  14. Zohdi, T. I.(2017). On the dynamics and breakup of quadcopters using a discrete element
    method framework.
    Computational Methods in Applied Mechanical Engineering.
  15. Zohdi, T. I. and Krone, R. (2017) Estimates on the acoustical stimulation and heating of multiphase biotissue. Biomechanics and Modeling in Mechanobiology.
  16. Zohdi, T. I. (2018). Multiple UAVs for Mapping: a review of basic modeling, simulation and applications. Annual Review of Environment and Resources.
  17. Clemon, L. M. and Zohdi, T. I. (2018). On the tolerable limits of granulated recycled material additives to maintain structural integrity. Construction and Building Materials.
  18. Zohdi, T. I. (2018). An upper bound on the particle-laden dependency of shear stresses at solid-fluid interfaces. Proceedings of the Royal Society A.
  19. Zohdi, T. I. (2018). Modeling the spatio-thermal fire hazard distribution of incandescent material ejecta in manufacturing. Computational Mechanics.
  20. Zohdi, T. I. (2018). Electrodynamic machine-learning-enhanced fault-tolerance of robotic free-form printing of complex mixtures. Computational Mechanics.
  21. Zohdi, T. I. and Campello, E. M. B. (2019). On pressurized functionalized particle-laden fluid infiltration into porous media. Journal of Multiscale Computation.
  22. Zohdi, T. I. (2019). Rapid simulation-based uncertainty quantification of  flash-type time-of-flight and Lidar-based body-scanning processes. Computer Methods in Applied Mechanics and Engineering.
  23. B. Emek Abali and Zohdi, T. I. (2019). Multiphysics computation of thermal tissue damage as a consequence of electric power absorption. Computational Mechanics.
  24. Zohdi, T. I. (2019). The Game of Drones: rapid agent-based machine-learning models for multi-UAV path planning. Computational Mechanics.
  25. Zohdi, T., (2020) A machine-learning framework for rapid adaptive digital-twin based fire-propagation simulation in complex environments. Computer Methods in Applied Mechanics and Engineering.
  26. Zohdi, T.I. (2020) Modeling and simulation of the infection zone from a cough, Computational Mechanics.
  27. Zohdi, T.I. (2020). An agent-based computational framework for simulation of global pandemic and social response on planet X, Computational Mechanics.
  28. Zohdi, T.I. (2020) Rapid simulation of viral decontamination efficacy with UV irradiation. Computer Methods Appl. Mech. Eng.
  29. Kim, D.H., Zohdi, T.I., and Singh, R.P. (2020). Modeling, simulation and machine learning for rapid process control of multiphase flowing foods, Comput. Methods Appl. Mech. Engrg.

R. Paul Singh

  1. Singh, R. P. (2000). Moving boundaries in food engineering. Food Technology. Vol. 54, No. 2, 44-53.
  2. Banga, J. R., Z. Pan, and R. P. Singh (2001). On the optimal control of contact-cooking processes.  Transactions IChemE (Institution of Chemical Engineers) Vol. 79(C), 145-151.
  3. Zorrilla, S. E., J. R. Banga, and R. P. Singh (2003). Dynamic optimization of double-sided cooking
    of meat patties. Journal of Food Engineering Vol. 58, 173-182.
  4. Sarkar, A., and R. P. Singh (2004). Modeling flow and heat transfer during freezing of foods in
    forced airstreams. Journal of Food Science Vol. 69, No. 9, 488-496.
  5. Erdogdu, F., A. Sarkar, and R. P. Singh (2005). Mathematical modeling of air-impingement
    cooling of finite slab shaped objects and effect of spatial variation of heat transfer coefficient.
    Journal of Food Engineering, Vol. 71, 287-294.
  6. Anderson, B. A., and R. P. Singh (2006). Modeling the thawing of frozen foods using air
    impingement technology. International Journal of Refrigeration, Vol. 29, 294-304.
  7. Voit, D. C., M. R. Santos, and R. P. Singh (2006). Development of a multipurpose fruit and
    vegetable processor for a manned mission to Mars. Journal of Food Engineering, Vol. 77, 230-
  8. Kong, F. and R.P. Singh (2008). A model stomach system to investigate disintegration
    kinetics of solid foods during gastric digestion. Journal of Food Science Vol. 73, No. 5,
  9. Kong, F. and R.P Singh (2008). Disintegration of solid foods in human stomach (Review).
    Journal of Food Science Vol. 73, No. 5, R67–R80
  10. Singh, R.P. and D.R. Heldman (2009). Introduction to Food Engineering. 4th edition. Academic
    Press, London.
  11. Kong, F. and Singh, R.P. (2010). A human gastric simulator (HGS) to study food digestion in
    human stomach. Journal of Food Science. Vol. 75, No. 9, E627-E635
  12. Ferrua, M. and R. P. Singh (2010). Modeling the fluid dynamics in a human stomach to gain
    insight of food digestion. Journal of Food Science. Vol. 75, No. 7, R151–R162.
  13. Ferrua, M. and R.P.Singh. (2011). Improved airflow method and packaging system for forced-air
    cooling of strawberries. International Journal of Refrigeration. Vol. 34, 1162-1173.
  14. Ferrua, M., F. Kong and R. P. Singh (2011). Computational modeling of gastric digestion and the
    role of food material properties. Trends in Food Science and Technology.
  15. Bornhorst, G.M. and R. P. Singh (2011). Food bolus formation and disintegration for starch-based
    foods. Comprehensive Reviews of Food Science and Food Safety. Vol. 11, No. 2, 101-118.
  16. Bornhorst G.M., R.P. Singh (2014). Gastric digestion in vivo and in vitro: How the structural
    aspects of food influence the digestion process. Annual Review of Food Science and Technology.
    Vol. 5, 111-132.
  17. Ferrua, M. J., Xue, Z., and Singh, R. P. (2014). On the kinematics and efficiency of advective
    mixing during gastric digestion – A numerical analysis. Journal of Biomechanics, Vol. 47, 3664-3673.
  18. Bornhorst, G. M., Ferrua, M. J., and Singh, R. P. (2015). A proposed food breakdown classification
    system to predict food behavior during gastric digestion. Journal of Food Science.
  19. Brodkorb, A. Egger, L., Alminger, M., Alvito P., Ballance S., Bohn T., Bourlieu-Lacanal C., Boutrou
    R., Carri`ere F., Clemente, A., Corredig M., Dupont D., Dufour C., Edwards, C., Golding M.,
    Karakaya S., Kirkhus B., Le Feunteun S., Lesmes U., Macierzanka A., Mackie A., Martins, C.,
    Marze S., McClements D. J., M´enard O., Minekus, M., Portmann, R., Santos C. N., Souchon, I.,
    Singh R. P., Vegarud. G.E., Wickham M. S. J., Weitschies W. and Recio I. (2019). INFOGEST static in
    vitro simulation of gastrointestinal food digestion. Nature Protocols. Vol 14, 991-1014.
  20. Somaratne, G., Reis, M.M., Ferrua, M.J., Ye, A., Francoise, N., Floury, J., Dupont, D., Singh, R.P.,
    Singh, J. (2019). Mapping the Spatiotemporal distribution of acid and moisture in food structures
    during gastric juice diffusion using hyperspectral imaging. J. Agric. Food Chem. Vol. 67, No. 33, 9399-
  21. Somaratne, G., Francoise, N., Ferrua, M.J., Singh, J., Ye, A., Dupont, D., Singh, R.P., Floury, J.
    (2020). In-situ disintegration of egg white gels by pepsin and kinetics of nutrient release followed
    by time-lapse confocal microscopy. Food Hydrocolloids, 98, 105258
  22. Kim, D.H., Zohdi, T.I., and Singh, R.P. (2020). Modeling, simulation and machine learning for rapid
    process control of multiphase flowing foods, Comput, Methods Appl. Mech Engrg. Vol. 371, 113286,
  23. Minekus, M., Alminger, M., Alvito, P., Ballance, S., Bohn, T. O. R. S. T. E. N., Bourlieu, C., … & Dufour, C. (2014). A standardised static in vitro digestion method suitable for food–an international consensus. Food & function, Vol. 5, No. 6, 1113-1124.
  24. Heldman, D. R. (Ed.). (2012). Food process engineering. Springer Science & Business Media.
  25. Valentas, K. J., Rotstein, E., & Singh, R. P. (1997). Handbook of food engineering practice. CRC press.

Ricardo San Martin

Francesco Borrelli

  1. Rosolia U and Borrelli F (2018). Learning Model Predictive Control for Iterative Tasks. A Data-Driven Control Framework. IEEE Transactions on Automatic Control., July, 2018. Vol. 63, No. 7, 1883-1896.
  2. Rosolia U, Zhang X and Borrelli F (2018). Data-Driven Predictive Control for Autonomous Systems. Annual Review of Control, Robotics, and Autonomous Systems. May, 2018. Vol. 1, No. 1, 259-286.
  3. Borrelli F, Bemporad A and Morari M (2017). Predictive Control. December, 2017. Cambridge Press.
  4. Robot Virtual Reality with Hardware-in-the-Loop Collaboration with Siemens

Simo Makiharju

  1. Mäkiharju, S. A., Gabillet, C., Paik, B. G., Chang, N. A., Perlin, M., & Ceccio, S. L. (2013). Time-resolved two-dimensional X-ray densitometry of a two-phase flow downstream of a ventilated cavity. Experiments in fluids, Vol. 54, No. 7, 1561.
  2. Yoon, S., Makiharju, S., Fessler, J. A., & Ceccio, S. L. (2017). Image Reconstruction for Limited Angle Electron Beam X-Ray Computed Tomography with Energy-Integrating Detectors for Multiphase Flows. IEEE Transactions on Computational Imaging.
  3. Mäkiharju, S.A., Yoon, S., Mychkovsky, A., Buchanan, J., & Ceccio, S.L. (2019). Single-Phase Mixing Through a Narrow Gap. Experimental Thermal and Fluid Science, v.107, 54-68.
  4. Ibarra, E., Wang, E.K, Farias, N., Goujon, A., & Mäkiharju, S.A. “The OpenBubble Toolbox: Open Source Algorithms for Bubble and Droplet Sizing and Velocimetry”– submitted – Measurement Science and Technology.
  5. Jason T. Parker, Eric Wang, and Simo A. Makiharju “Evaluating Tracer Particles For Use In X-ray Particle Image Velocimetry” planned submission to Measurement Science and Technology.

Koushil Sreenath

  1. Prasanth Kotaru and Koushil Sreenath (2020). Multiple quadrotors carrying a flexible hose: dynamics, differential flatness and control. International Federation of Automatic Control World Congress (IFAC).
  2. S. Chen, J. Rogers, B. Zhang, and K. Sreenath. (2019). Feedback Control for Autonomous Riding of Hovershoes by a Cassie Bipedal Robot. IEEE International Conference on Humanoid Robots (Humanoids). 375-382
  3. Jun Zheng and Koushil Sreenath (2019). Geometric Control of a Quadrotor with a Load Suspended through from an Offset. American Control Conference 2019.
  4. J. Zheng, P. Kotaru, G. Wu, and K. Sreenath (2020). Geometric Control and Differential Flatness of a Quadrotor UAV with Load Suspended from a Pulley. American Control Conference 2019.
  5. Bin Xu and Koushil Sreenath (2018). Safe Teleoperation of Dynamic UAVs through Control Barrier Functions. IEEE International Conference on Robotics and Automation (ICRA).
  6. X. Yang, A. Agrawal, K. Sreenath, and N. Michael (2018). System-Agnostic Adaptive Teleoperation for High-Dimensional Systems. Special issue on Learning for Human-Robot Collaboration, Autonomous Robotics. 1-17.
  7. P. Kotaru, G. Wu, and K. Sreenath (2018). Differential-Flatness and Control of Multiple Quadrotors with a Payload Suspended through Flexible Cables. IEEE Indian Control Conference (ICC). 352-357.
  8. S. Tang, K. Sreenath, and V. Kumar (2017). Multi-Robot Trajectory Generation for an Aerial Payload Transport System. International Symposium on Robotics Research (ISRR)

Khalid Mosalam

  1. Mosalam, K.M., R.N. White, and G. Ayala, “Response of Infilled Frames Using Pseudo-Dynamic Experimentation,” Earthquake Engineering and Structural Dynamics, 1998, Vol. 27, No. 6, 589-608.
  2. Gliniorz, K.-U., K.M. Mosalam and J. Natterer, “Modeling of Layered Timber Beams and Ribbed Shell Frameworks,” Composites Part B: Engineering, 2002, Vol. 33, No. 5, 367-381.
  3. Arici, Y. and K.M. Mosalam, “Modal Identification of Bridge Systems Using State-Space Methods,” Journal of Structural Control and Health Monitoring, July 2005, Vol. 12, No. 3-4, 381-404.
  4. Arici, Y. and K.M. Mosalam, “Statistical Significance of Modal Parameters of Bridge Systems Identified from Strong Motion Data,” Earthquake Engineering and Structural Dynamics, August 2005, Vol. 34, No. 10, 1323-1341.
  5. Beall, F.C., J. Li, T.A. Breiner, J. Wai, C. Machado, G. Oberdorfer and K.M. Mosalam, “Small Scale Rack Testing of Wood-Frame Shear Walls,” Wood and Fiber Science, April 2006, Vol. 38, No. 2, 300-313.
  6. Pan, P., H. Tomofuji, T. Wang, M. Nakashima, M. Ohsaki and K.M. Mosalam, “Development of Peer-to-Peer (P2P) Internet Online Hybrid Test System,” Earthquake Engineering and Structural Dynamics, June 2006, Vol. 35, No. 7, 867-890.
  7. Elkhoraibi, T. and K.M. Mosalam, “Towards Error-Free Hybrid Simulation Using Mixed Variables,” Earthquake Engineering and Structural Dynamics, May 2007, Vol. 36, No. 11, 1497-1522, doi: 10.1002/eqe.691.
  8. Mosalam, K.M. and Y. Arici, “Health Monitoring of a Bridge System Using Strong Motion Data,” Smart Structures and Systems, July 2009, Vol. 5, No. 4, 427-442.
  9. Mosalam, K.M, S. Takhirov and A. Hashemi, “Seismic Evaluation of 1940s Asymmetric Wood-Frame Building Using Conventional Measurements and High-Definition Laser Scanning,” Earthquake Engineering and Structural Dynamics, 2009, Vol. 38, No. 10, 1175-1197, doi: 10.1002/eqe.888.
  10. Yang, Y., H. Liu, K.M. Mosalam and X. Huang, “An Improved Direct Stiffness Calculation Method for Damage Detection of Beam Structures,” Structural Control and Health Monitoring, May 2013, Vol. 20, No. 5, 835-851, doi: 10.1002/stc.1503.
  11. Mosalam, K.M., M. Hube, S.M. Takhirov and S. Günay, “Teaching Innovation through Hands-on-Experience Case Studies Combined with Hybrid Simulation,” ASCE, Journal of Professional Issues in Engineering Education and Practice, July 2013, Vol. 139, No. 3, 177-186, doi: 10.1061/(ASCE)EI.1943-5541.0000146.
  12. Mosalam, K.M., S.M. Takhirov and S. Park, “Applications of Laser Scanning to Structures in Laboratory Tests and Field Surveys,” Structural Control and Health Monitoring, January 2014, Vol. 21, No. 1, 115-134, doi: 10.1002/stc.1565.
  13. Günay, M.S. and K.M. Mosalam, “Enhancement of Real-time Hybrid Simulation on a Shaking Table Configuration with an Advanced Control Method,” Earthquake Engineering and Structural Dynamics, April 2015, Vol. 44, No. 5, 657-675, doi: 10.1002/eqe.2477.
  14. Drazin, P.L., S. Govindjee and K.M. Mosalam, “Hybrid Simulation Theory for Continuous Beams,” ASCE, Journal of Engineering Mechanics, July 2015, Vol. 141, No. 7, Article Number: 04015005, doi: 10.1061/(ASCE)EM.1943-7889.0000909.
  15. Yang, Y., K.M. Mosalam, G. Liu, H. Liu and X. Wang, “Damage Detection Using Improved Direct Stiffness Calculations –A Case Study,” International Journal of Structural Stability and Dynamics, January 2016, Vol. 16, No. 1, Article Number: 1640002, doi: 10.1142/S0219455416400022.
  16. Moustafa, M. and K.M. Mosalam, “Substructured Dynamic Testing of Substation Disconnect Switches,” Earthquake Spectra, February 2016, Vol. 32, No. 1, 567-589, doi: 10.1193/031314EQS037M.
  17. Liang, X. and K.M. Mosalam, “Lyapunov Stability and Accuracy of Direct Integration Algorithms Applied to Nonlinear Dynamic Problems,” Journal of Engineering Mechanics, May 2016, Vol. 142, No. 5, Article Number: 04016022, doi: 10.1061/(ASCE)EM.1943-7889.0001073.
  18. Moustafa, M.A. and K.M. Mosalam, “Structural Performance of Porcelain and Polymer Post Insulators in High Voltage Electrical Switches,” Journal of Performance of Constructed Facilities, October 2016, Vol. 30, No. 5, Article Number: 04016002, doi: 10.1061/(ASCE)CF.1943-5509.0000848.
  19. Liang, X. and K.M. Mosalam, “Lyapunov Stability Analysis of Explicit Direct Integration Algorithms Considering Strictly Positive Real Lemma,” Journal of Engineering Mechanics, October 2016, Vol. 142, No. 10, Article Number: 04016079, doi: 10.1061/(ASCE)EM.1943-7889.0001143.
  20. Mosalam, K.M., S. Günay and S. Takhirov, “Response Evaluation of Interconnected Electrical Substation Equipment Using Real-Time Hybrid Simulation on Multiple Shaking Tables,” Earthquake Engineering and Structural Dynamics, November 2016, Vol. 45, No. 14, 2389-2404, doi: 10.1002/eqe.2767.
  21. Liang, X. and K.M. Mosalam, “Lyapunov Stability Analysis of Explicit Direct Integration Algorithms Applied to Multi-Degree-of-Freedom Nonlinear Dynamic Problems,” Journal of Engineering Mechanics, December 2016, Vol. 142, No. 12, Article Number: 04016098, doi: 10.1061/(ASCE)EM.1943-7889.0001162.
  22. Bakhaty, A.A., S. Govindjee and K.M. Mosalam, “Theoretical Evaluation of Hybrid Simulation Applied to Continuous Plate Structures,” Journal of Engineering Mechanics, December 2016, Vol. 142, No. 12, Article Number: 04016093, doi: 10.1061/(ASCE)EM.1943-7889.0001157.
  23. Huang, H., W. Chang and K.M. Mosalam, “Feasibility of Shape Memory Alloy in a Tuneable Mass Damper to Reduce Excessive In‐Service Vibration,” Structural Control and Health Monitoring, February 2017, Vol. 24, No. 2, Article Number: e1858, doi: 10.1002/stc.1858.
  24. Muin, S. and K.M. Mosalam, “Cumulative Absolute Velocity as a Local Damage Indicator of Instrumented Structures,” Earthquake Spectra, May 2017, Vol. 33, No. 2, 641-664, doi: 10.1193/090416EQS142M.
  25. Collins, A., H. Tatano, W. James, C. Wannous, K. Takara, V. Murray, C. Scawthorn, J. Mori, S. Aziz, K.M. Mosalam, S. Hochrainer-Stigler, I. Alcantara-Ayala, E. Krausmann, W. Li, A.M. Cruz, S. Samaddar, T. De Groeve, Y. Ono, K. Berryman, K. Suzuki, M.A. Parry, P. McGowran and J.G. Rees, “The 3rd Global Summit of Research Institutes for Disaster Risk Reduction: Expanding the Platform for Bridging Science and Policy Making,” International Journal of Disaster Risk Science, June 2017, Vol. 8, No. 2, 224-230, doi: 10.1007/s13753-017-0123-z.
  26. Alibrandi, U. and K.M. Mosalam, “Equivalent Linearization Methods for Stochastic Dynamic Analysis Using Linear Response Surfaces,” Journal of Engineering Mechanics, August 2017, Vol. 143, No. 8, Article Number: 04017055, doi: 10.1061/(ASCE)EM.1943-7889.0001264.
  27. Mead, A.R. and K.M. Mosalam, “Ubiquitous Luminance Sensing Using the Raspberry Pi and Camera Module System,” Lighting Research and Technology, November 2017, Vol. 49, No. 7, 904-921, doi: 10.1177/1477153516649229.
  28. Alibrandi, U. and K.M. Mosalam, “Kernel Density Maximum Entropy Method with Generalized Moments for Evaluating Probability Distributions, Including Tails, from a Small Sample of Data,” International Journal for Numerical Methods in Engineering, March 2018, Vol. 113, No. 13, 1904-1092, doi: 10.1002/nme.5725.
  29. Gong, C., W. Ding, K. Soga, K.M. Mosalam and Y. Tuo, “Sealant Behavior of Gasketed Segmental Joints in Shield Tunnels: An Experimental and Numerical Study,” Tunnelling and Underground Space Technology, July 2018, Vol. 77, 127-141, doi: 10.1016/j.tust.2018.03.029.
  30. Mosalam, K.M., U. Alibrandi, H. Lee and J. Armengou, “Performance-Based Engineering and Multi-Criteria Decision Analysis for Sustainable and Resilient Building Design,” Structural Safety, September 2018, Vol. 74, 1-13, doi: 10.1016/j.strusafe.2018.03.005.
  31. Gao, Y. and K.M. Mosalam, “Deep Transfer Learning for Image‐Based Structural Damage Recognition,” Computer-Aided Civil and Infrastructure Engineering, September 2018, Vol. 33, 748-768, doi: 10.1111/mice.12363.
  32. Liang, X. and K.M. Mosalam, “Lyapunov-Based Nonlinear Solution Algorithm for Structural Analysis,” Journal of Engineering Mechanics, September 2018, Vol. 84, Article Number: 04018082, doi: 10.1061/(ASCE)EM.1943-7889.0001501.
  33. Gong, C., W. Ding, K. Soga and K.M. Mosalam, “Failure Mechanism of Joint Waterproofing in Precast Segmental Tunnel Linings,” Tunnelling and Underground Space Technology, February 2019, Vol. 84, 334-352.
  34. Mosalam, K.M., S. Muin and Y. Gao, “New Directions in Structural Health Monitoring,” NED University Journal of Research, Issue: Special Issue on First South Asia Conference on Earthquake Engineering (SACEE’19), July 2019, Vol. 2, 77-112.
  35. Gao, Y., B. Kong and K.M. Mosalam, “Deep Leaf‐Bootstrapping Generative Adversarial Network for Structural Image Data Augmentation,” Computer‐Aided Civil and Infrastructure Engineering, July 2019, Vol. 34, No. 9, 755-773.
  36. He, M., W. Gu, Y. Kong, L. Zhang, C.J. Spanos and K.M. Mosalam, “CausalBG: Causal Recurrent Neural Network for the Blood Glucose Inference with IoT Platform,” IEEE Internet of Things Journal, January 2020, Vol. 7, No. 1, 598-610, DOI: 1109/JIOT.2019.2946693.
  37. Gong, C., W. Ding and K.M. Mosalam, “Performance-based Design of Joint Waterproofing of Segmental Tunnel Linings using Hybrid Computational/Experimental Procedures,” Tunnelling and Underground Space Technology, February 2020, Vol. 96, 103172.
  38. Schulthess, P., Neuenschwander, M., Mosalam, K.M. and Knobloch, M., “A Computationally Rigorous Approach to Hybrid Fire Testing,” Computers and Structures, October 2020, Vol. 238, Paper: 106301,
  39. Gao, Y. and Mosalam, K.M., “PEER Hub ImageNet: A Large-Scale Multiattribute Benchmark Data Set of Structural Images,”Journal of Structural Engineering – ASCE, October 2020, Vol. 146, No. 10, 04020198, DOI: 10.1061/(ASCE)ST.1943-541X.0002745.
  40. Huang, H., Mosalam, K.M. and Chang, W.-S., “Adaptive Tuned Mass Damper with Shape Memory Alloy for Seismic Application,” Engineering Structures, November 2020, Vol. 223, Paper 111171, DOI: 10.1016/j.engstruct.2020.111171.

Mark Mueller

  1. Jaeseung Byun, Simo A. Mäkiharju, and Mark W. Mueller: A flow disturbance estimation and rejection strategy of multirotors with round trip trajectories, submitted to IROS 2020.
  2. Xiangyu Wu and Mark W. Mueller: Using multiple short hops for multicopter navigation with only inertial sensors, ICRA 2020.
  3. Mark W. Mueller, Markus Hehn, Raffaello D’Andrea: A computationally efficient motion primitive for quadrocopter trajectory generationIEEE Transactions on Robotics, Volume 31, no.8, 1294-1310, 2015.

Rebecca Abergel

Lee Fleming

  1. Balsmeier, B., Assaf, M., Chesebro, T., Fierro, G., Johnson, K., Johnson, S., … & Zang, G. (2018). Machine learning and natural language processing on the patent corpus: Data, tools, and new measures. Journal of Economics & Management Strategy, Vol. 27 No. 3, 535-553.
  2. Fleming, L., & Sorenson, O. (2004). Science as a map in technological search. Strategic management journal, Vol. 25 No. 8‐9, 909-928.

Ana Claudia Arias

  1. L. L. Lavery, G. L. Whiting, and A. C. Arias (2011). All ink-jet printed polyfluorene photosensor for high illuminance detection. Organic Electronics. Vol. 12, 682-685.
  2. Ostfeld, A. E., & Arias, A. C. (2017). Flexible photovoltaic power systems: integration opportunities, challenges and advances. Flexible and Printed Electronics. Vol. 2, No. 1, 013001.
  3. Ostfeld, A. E., Deckman, I., Gaikwad, A. M., Lochner, C. M., & Arias, A. C. (2015). Screen printed passive components for flexible power electronicsScientific reports. Vol. 5, 15959.

Ethan A. Ligon

  1. Ligon, E. (2012). Supply and Effects of Specialty Crop Insurance. National Bureau of Economic Research.
  2. Ligon, E. (2002). Quality and Grading Risk. In A Comprehensive Assessment of the Role of Risk in US Agriculture 353-369. Springer, Boston, MA.
  3. Hueth, B. and Ligon, E. (1999). Producer Price Risk and Quality Measurement. American Journal of Agricultural Economics. Vol. 81, No. 3, 512-524.
  4. Hueth, B. and Ligon, E. (1999). Agricultural Supply Response Under Contract. American Journal of Agricultural Economics. Vol. 81, No. 3, 610-615.
  5. B. Hueth, E. Ligon, S. Wolf, and S. Wu (1999). Incentive Instruments in Fruit and Vegetable Contracts: Input Control, Monitoring, Measuring, and Price Risk. Review of Agricultural Economics. Vol. 21, No. 2.