Publications and presentations

  1. D. Levac, H. Dumas, and W. Meleis, Development and preliminary usability evaluation of a tablet-based interactive movement tool for pediatric rehabilitation. In JMIR Rehabilitation Assistive Technologies 2018;5(2):e1030.
  2. W. Li and W. Meleis, Similarity-Aware Kanerva Coding for On-Line Reinforcement Learning. In International Symposium of Intelligent Unmanned Systems on Artificial Intelligence (SIUSAI), Las Vegas, August 2018.
  3. W. Li, F. Zhou, K. Chowdhury, and W. Meleis, QTCP: Adaptive Congestion Control with Reinforcement Learning, IEEE Transactions on Network Science and Engineering, Vol 6, Issue 3, July-Sept 2019.
  4. W. Li and W. Meleis, Adaptive Adjacency Kanerva Coding for Memory-Constrained Reinforcement Learning. In International Conference on Machine Learning and Data Mining in Pattern Recognition (MLDM), Springer, New York, July 2018.
  5. W. Li, F. Zhou, W. Meleis and K. Chowdhury, Dynamic Generalization Kanerva Coding in Reinforcement Learning for TCP Congestion Control Design, Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Sao Paolo, Brazil, 2017.
  6. J. Radford, A. Pilny, A. Reichelmann, B. Keegan, B. Welles, J. Hoye, K. Ognyanova, W. Meleis, and D. Lazer, Volunteer Science: An Online Laboratory for Experiments in Social Psychology, Social Psychology Quarterly, Vol 79, Issue 4, 2016.
  7. L. Hayward, S. Ventura, M. Mahanna, and W. Meleis, Inter-professional Collaboration between Physical Therapy, Speech Language Pathology and Engineering Faculty and Students to Address Global Pediatric Rehabilitation Needs: A Case Report, Journal of Physical Therapy Education, Vol. 30, No. 4, Oct 2016.
  8. W. Li, F. Zhou, W. Meleis, and K. Chowdhury, Learning-Based and Data-Driven TCP Design for Memory-Constrained IoT, International Conference on Distributed Computing in Sensor Systems, Washington D.C., May, 2016.
  9. S. Guler, M. Dannhauer, B. Erem, R. Macleod, D. Tucker, S. Turovets P. Luu, W. Meleis, and D Brooks, Optimizing Stimulus Patterns for Dense Array TDCS with Fewer Sources than Electrodes Using a Branch and Bound Algorithm, International Symposium on Biomedical Imaging (ISBI'16), Prague, Czech Republic, April 13-16, 2016.
  10. C. Wu, W. Li and W. Meleis, "Rough Sets-based Prototype Optimization in Kanerva-based Function Approximation", IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT), 2015.
  11. D. Lazer, W. Meleis, B. Foucault Wells, C. Riedl, J. Radford, B. Keegan, K. Ognyanova, S. Wojcik, J. Hoye and C. Karbeyaz, "Performing Massively Open Online Social Experiments with Volunteer Science", Workshop on Crowdsourcing and Online Behavioral Experiments (COBE) at the ACM Conference on Economics and Computation, 2015.
  12. J. Radford, B. Keegan, J. Hoye, C. Karbeyaz, K. Ognyanova, B. Foucault Welles, W. Meleis, D. Lazer, "Conducting Massively Open Online Social Experiments with Volunteer Science", Intl AAAII Conference on Web and Social Media, 2015.
  13. J. Radford, B. Keegan, K. Ognyanova, B. Welles, J. Hoye, C. Karbeyaz, W. Meleis, David Lazer, Validating Massively Open Online Social Experiments with Volunteer Science, Online Experiments: Methods, Opportunities, and Challenges panel of the Conference of the International Communication Association, 2015.
  14. Volunteer Science as a Platform for Studying Team Processes and Performance, Cooperative Team Networks Workshop at the International School and Conference on Network Science (NetSci), 2014.
  15. Volunteer Science: A Crowd Sourced Platform for Studying Human Behavior, MIT Conference on Digital Experimentation (CODE), 2014.
  16. B. Keegan, K. Ognyanova, B. Welles, C. Riedl, C. Karbeyaz, W. Meleis, David Lazer, J. Radford and J. Hoye, Conducting Massively-Open Online Social Experiments with Volunteer Science, Citizen + X: Volunteer-Based Crowdsourcing in Science, Public Health, and Government, papers from the Human Computation Workshop (HCOMP), pp. 19-20, 2014.
  17. B. Keegan, C. Karbeyaz, B. Foucault Welles, J. Hoye, W. Meleis, and David Lazer, Information Navigation and Hidden Profile Experiments on the Volunteer Science Web Laboratory, International Sunbelt Social Network Conference (Sunbelt XXXIV), Florida, US, 2014.
  18. L. Sallaway, S. Magee, J. Shi, F. Quivira, K. Tgavalekos, D Brooks, S, Muftu, W. Meleis, R. Moore, D. Kopans, K-T, Wan, Detecting Solid Masses in Phantom Breast Using Mechanical Indentation, Experimental Mechanics, Vol. 54, Number 6, 2014, pp. 935-942.
  19. B. Keegan, C. Karbeyaz, J. Hoye, W. Meleis, D. Lazer, "Volunteer Science: Online Behavioral Experiments Using Facebook as a Subject Pool." International Sunbelt Social Network Conference (Sunbelt XXXIII), Hamburg, Germany, 2013.
  20. B. Keegan, C. Karbeyaz, J. Hoye, W. Meleis, D. Lazer, "Volunteer Science: Behavioral Experiments on Networks with Facebook Users." International Workshop and Conference on Network Science (NetSci). Copenhagen, Denmark, 2013.
  21. J. Tai, J. Zhang, J. Li, W. Meleis, N. Mi, ArA: Adaptive Resource Allocation for Clouds under Burst Workloads , Proceedings of the IEEE International Performance Computing and Communications Conference (IPCCC), Orlando, Florida, 2011, pp. 1-8.
  22. K. Chowdhury, R. Doost-Mohammady, W. Meleis, M. Di Felice, L. Bononi, Cooperation and Communication in Cognitive Radio Networks based on TV Spectrum Experiments, Proceedings of IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks (WoWMoM), Lucca, Italy, 2011, pp. 1-9.
  23. J. Zhang, N. Mi, J. Tai and W. Meleis, Decentralized Scheduling of Bursty Workload On Computing Grids, Proceedings of IEEE International Conference on Communications (ICC), Kyoto, Japan, 2011.
  24. M. Di Felice, K. Chowdhury, W. Meleis, and L. Bononi, To Sense or To Transmit: A Learning-based Spectrum Management Scheme for Cognitive RadioMesh Networks, Fifth IEEE Workshop on Wireless Mesh Networks (WiMesh), held in conjunction with IEEE SECON, Boston, Massachusetts, 2010
  25. M. Di Felice, K. Chowdhury, C. Wu, L. Bononi, and W. Meleis, Learning-based Spectrum Selection in Cognitive Radio Ad Hoc Networks, Proceedings of the Eight International Conference on Wired/Wireless Internet Communications (WWIC), Invited paper, Lulea, Sweden, 2010.
  26. C. Wu, K. Chowdhury, M. Di Felice, and W. Meleis, Spectrum Management of Cognitive Radio Using Multi-agent Reinforcement Learning, Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Toronto, Canada, 2010.
  27. J. Zhang and W. Meleis, Adaptive Grid Computing for MPI Applications, Proceedings of the IASTED International Conference on Parallel and Distributed Computing and Systems, Cambridge, MA, 2009.
  28. C. Wu and W. Meleis, Function Approximation Using Tile and Kanerva Coding For Multi-Agent Systems, Workshop on Adaptive Learning Agents (ALA), held in conjunction with the 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Budapest, Hungary, 2009.
  29. C. Wu and W. Meleis, Adaptive Fuzzy Function Approximation for Multi-Agent Reinforcement Learning, Proceedings of IEEE/WIC/ACM International Conference on Intelligent Agent Technology(IAT), Milan, Italy, 2009.
  30. C. Wu and W. Meleis, Fuzzy Kanerva-based Function Approximation for Reinforcement Learning, Proceedings of the 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Budapest, Hungary, 2009.
  31. C. Wu and W. Meleis, Optimized Kanerva-based Function Approximation for Multi-Agent Systems, Proceedings of the 7th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Estoril, Portugal, 2008.
  32. M. Fayyazi, D. Kaeli and W. Meleis, An adjustable linear-time parallel algorithm for maximum weight bipartite matching, Information Processing Letters, Vol. 97, No. 5, March 2006, pp. 186-190.
  33. J. Zhang, W. Meleis, D. Kaeli and T. Wu, Acceleration of Maximum Likelihood Estimation for Tomosynthesis Mamography, The 12th International Conference on Parallel and Distributed Systems, pp. 291-299, Minneapolis, MN, 2006.
  34. F. Karimi, Z. Navabi, W. Meleis, and F. Lombardi, Using Data Compression in Automatic Test Equipment for System-on-Chip Testing, IEEE Transactions on Instrumentation and Measurement, Vol. 53, No. 2, April 2004, pp. 308-317.
  35. M. Fayyazi, D. Kaeli and W. Meleis, A Polylogarithmic Time Parallel Maximum Weight Bipartite Matching Algorithm for Scheduling in Input-Queued Switches, Proceedings of International Parallel and Distributed Processing Symposium (IPDPS), Santa Fe NM, 2004.
  36. T. Wu, R. Moore, J. Zhang, E. Rafferty, D. Kopans, W. Meleis and D. Kaeli, Digital tomosynthesis mammography using a parallel maximum likelihood reconstruction method, Proceedings of SPIE: Medical Imaging, pp. 1-4, San Diego CA, 2004.
  37. H. Quinn, L. A. S. King, M. Leeser, and W. Meleis, Runtime Assignment of Reconfigurable Hardware Components for Image Processing Pipelines, IEEE Symposium on FPGAs for Custom Computing Machines, Napa CA, 2003, p. 173.
  38. I. Baev, W. Meleis, S. Abraham, Backtracking-based Instruction Scheduling To Fill Branch Delay Slots, International Journal on Parallel Programming, Vol. 30, December 2002, pp. 397-418.
  39. I. Baev, W. Meleis, and A. Eichenberger, Lower Bounds on Precedence-Constrained Scheduling for Parallel Processors, Information Processing Letters, Vol. 83, No. 1, July 2002, pp. 27-32.
  40. I. Baev, W. Meleis, and A. Eichenberger, An Experimental Study of Algorithms for Total Weighted Completion Time Scheduling, Algorithmica, Vol. 33, No. 1, May 2002, pp. 34-51.
  41. M. Ashouei, D. Jiang, W. Meleis, D. Kaeli, M. El-Shenawee, E. Mizan, Y. Wang and C. Rappaport, Profile-based Characterization and Tuning for Subsurface Sensing and Imaging Applications, International Journal of SIMULATION: Systems, Science and Technology, Vol. 3, No. 1-2, June 2002, pp. 40-55.
  42. M. El-Shenawee, C. Rappaport, D. Jiang, and W. Meleis, Electromagnetics Computations Using the MPI Parallel Implementation of the Steepest Descent Fast Multipole Method (SDFMM), Applied Computational Electromagnetics Society Journal, Vol. 17, 2002, pp. 112-122.
  43. D. Jiang, W. Meleis, M. El-Shenawee, E. Mizan, M. Ashouei, and C. Rappaport, Parallel Implementation of the Steepest Descent Fast Multipole Method (SDFMM) On a Beowulf Cluster for Subsurface Sensing Applications, IEEE Microwave and Wireless Components Letters, Vol. 12, No. 1, January 2002, pp. 24-26.
  44. F. Karimi, W. Meleis, Z. Navabi, and F. Lombardi, Data Compression for System-On-Chip Testing using ATE, 17th IEEE Intl. Symposium on Defect and Fault Tolerance in VLSI Systems, Vancouver, Canada, 2002, pp. 166-174.
  45. W. Meleis, A. Eichenberger, and I. Baev, Scheduling Superblocks with Bound-based Branch Tradeoffs, IEEE Trans. on Computers, Vol. 50, No. 8, August 2001, pp. 784-797.
  46. W. Meleis, Dual-Issue Scheduling for Binary Trees with Spills and Pipelined Loads, SIAM Journal on Computing, Vol. 30, No. 6, 2001, pp. 1921-1941.
  47. A. Eichenberger, W. Meleis, and S. Maradani, An Integrated Approach to Accelerate Data and Predicate Computations in Hyperblocks, 33rd Annual Intl. Conf. on Microarchitecture (IEEE/ACM), Monterey CA, Dec. 2000, pp. 101-111.
  48. S. Abraham, W. Meleis, and I. Baev, Efficient backtracking instruction schedulers, Intl. Conf. on Parallel Architectures and Compilation Techniques (IEEE/ACM), Philadelphia, PA, 2000, pp. 301-308.
  49. I. Baev, W. Meleis and A. Eichenberger, Lower Bounds on Precedence-constrained Scheduling for Parallel Processors, Intl. Conf. on Parallel Processing, Toronto, Canada, 2000, 549-553.
  50. J. Kalamatianos, A. Khalafi, D. Kaeli, and W. Meleis, Temporal-based Cache Interaction for Improved Program Layout, IEEE Trans. on Computers, Special Issue on Cache Memory, 1999, pp. 168-175.
  51. J. Kalamatianos, A. Khalafi, D. Kaeli, B. Calder, and W. Meleis, Program Reordering Using Estimated Call Graphs, DEC Technical Journal, Special Issue on Programming Languages and Tools, accepted 1999.
  52. A. Eichenberger and W. Meleis, Balance Scheduling: Weighing Branch Tradeoffs in Superblocks, 32nd Annual Intl. Conf. on Microarchitecture (IEEE/ACM), 1999, pp. 272.
  53. I. Baev, W. Meleis, and A. Eichenberger, Algorithms for Total Weighted Completion Time Scheduling, ACM-SIAM Symp. on Discrete Algorithms, January 1999.
  54. W. Meleis and E. Davidson, Optimal Dual-Issue Instruction Scheduling With Spills for Binary Expression Trees, ACM-SIAM Symp. on Discrete Algorithms, January 1999.
  55. M. Leeser, W. Meleis, M. Vai, S. Chiricescu, W. Xu, and P. Zavracky, Rothko: A Three Dimensional FPGA, IEEE Design and Test Magazine, Spring 1998, pp. 16-23.
  56. J. Casmira, J. Fraser, D. Kaeli, and W. Meleis, Operating System Impact on Trace-Driven Simulation, 31st Annual Simulation Symp., April 1998.
  57. I. Baev and W. Meleis, Total Weighted Completion Time Scheduling for Superblocks, SIAM Conference on Discrete Mathematics, January 1998.
  58. J. Kalamatanos, A. Khalafi, D. Kaeli, and W. Meleis, Memory Performance Tuning Using Graph-based Analysis, Workshop on Pre-Hardware Performance Analysis Techniques, June 1998.
  59. K. Bowers, D. Kaeli, and W. Meleis, Performance Optimization of the Forth Interpreter, Northeastern University Technical Report ECE-CEG-98-022, 1998.
  60. S. Sair, D. Kaeli, and W. Meleis, A Study of Loop Unrolling for VLIW-Based DSP Processors, IEEE Workshop on Signal Processing Systems, 1998, pp. 519 -527.
  61. W. Meleis, M. Leeser, P. Zavracky, and M. Vai, Architectural Design of a Three-Dimensional FPGA, Workshop on Field-Programmable Logic and Applications (FPL), 1997.
  62. M. Leeser, W. Meleis, M. Vai, and P. Zavracky, Rothko: a Three Dimensional FPGA Architecture, its Fabrication, and Design Tools, IEEE Conf. on Advanced Research in VLSI (ARVLSI), 1997.
  63. W. Meleis and E. Davidson, Optimal Local Register Allocation for a Multiple-Issue Machine, ACM Intl. Conf. on Supercomputing, pp 107-116, July 1994.