Yu-Han Lyu, Devin Balkcom:
Optimal trajectories for planar rigid bodies with switching costs.
International Journal of Robotics Research (2015)
Weifu Wang, Devin Balkcom, Amit Chakrabarti:
A fast online spanner for roadmap construction.
International Journal of Robotics Research (2015)
Matthew P. Bell, Weifu Wang, Jordan Kunzika, Devin Balkcom:
Knot-tying with four-piece fixtures.
International Journal of Robotics Research 33(11): 1481—1489 (2014)
See Google scholar page for my publications.
Feng, Y. and Casey, M., Phrase-Level Symbolic Music Generation, AI and Music Creativity (AIMC 2024), University of Oxford, Sep. 2024.
Keating, M. and Casey, M., Jazz Guitar Voice-Leading Chord Fingerings With Long Short-Term Memory, AI and Music Creativity (AIMC 2024), University of Oxford, Sep. 2024.
Bates, K., Kanishcheva, A., Casey, M., and Jobst, B. "Music and Epilepsy: Studying the Effects of Mozart's Sonata K. 448 on the Epileptic Brain", Ch. 20 in Neurobiology of Creativity, Cambridge University Press, 2024
Paulsen, S. and Casey, M., Self-Supervised Pretraining for Improved Downstream Decoding of Audio-Evoked fMRI Sequences, 4th Workshop on Self-Supervised Learning: Theory and Practice, Neural Information Processing Systems 2023, New Orleans, December 2023
Paulsen, S. and Casey, M., Improved Decoding of Audio-Evoked fMRI Sequences with Sequential Transfer Learning, Workshop: Neurips meets Medical Imaging, Neural Information Processing Systems 2023, New Orleans, December 2023
Quon, R.J., Strýček, O., Ettinger, A.B., Casey, M.A., Rektor, I., Jobst, B.C. (2023). "Music for Epilepsy". In: Devlin, K., Kang, K., Pantelyat, A. (eds) Music Therapy and Music-Based Interventions in Neurology. Current Clinical Neurology. Humana, Cham, 2023
May, L., Halpern, A., Paulsen, S., and Casey, M. Imagined Scale Relationships Decoded from Auditory Cortex. Journal of Cognitive Neuroscience, 34(8), July 1, 2022.
Feng, Y. and Casey, M. Evoked Responses to Note Onsets and Phrase Boundaries in Mozart's K448, Scientific Reports, 10 June, 2022.
A. Chakrabarti, G. Cormode, A. McGregor, J. Thaler, and S. Venkatasubramanian. “Verifiable Stream Computation and Arthur–Merlin Communication,” (with G. Cormode, A. McGregor, J. Thaler, S. Venkatasubramanian), in Proc. 30th Ann. Conf. Comput. Complexity (CCC 2015).
A. Chakrabarti, L. K. Fleischer, C. Weibel. “When the Cut Condition is Enough: A Complete Characterization for Multiflow Problems in Series-Parallel Networks,” in Proc. 44th Ann. ACM Symp. Theory Comput. (STOC 2012) 19-26.
A. Chakrabarti and O. Regev. “An Optimal Lower Bound on the Communication Complexity of Gap-Hamming-Distance”, SIAM J. Comput., 41:5 (2012) 1299-1317.
A. Chakrabarti, G. Cormode and A. McGregor. “ A Near-Optimal Algorithm for Estimating the Entropy of a Stream,” ACM Trans. Alg., 6:3 (2010) Art. 51.
A. Chakrabarti and O. Regev. “An Optimal Randomized Cell Probe Lower Bound for Approximate Nearest Neighbor Searching,” SIAM J. Comput., 39:5 (2010) 1919–1940.
A. Chakrabarti, S. Khot, and Y. Shi. “Evasiveness of Subgraph Containment and Related Properties,” SIAM J. Comput., 31:3 (2002) 866-875.
Tightening Curves on Surfaces Monotonically with Applications,
with Arnaud de Mesmay,
in Proceedings of the 31st Annual ACM-SIAM Symposium on Discrete Algorithms (SODA'20),
pages 747-766, 2020.
Invited to special issue of the ACM Transactions on Algorithms (TALG).
Near-Optimal Distance Emulator for Planar Graphs,
with Paweł Gawrychowski, Shay Mozes, and Oren Weimann,
in Proceedings of the 26th Annual European Symposium on Algorithms (ESA'18),
pages 16:1-16:17, 2018.
Untangling Planar Curves,
with Jeff Erickson,
Discrete & Computational Geometry, volume 58, issue 4, pages 889-920, 2017.
Special issue of invited papers from the 32nd International Symposium on Computational Geometry (SoCG'16).
Detecting Weakly Simple Polygons,
with Jeff Erickson and Chao Xu,
in Proceedings of the 26th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA'15),
pages 1655-1670, 2015.
Cormen, T H, C E Leiserson, R L Rivest, and C Stein, Introduction to Algorithms, third edition, The MIT Press, (2009).
Cormen, T H, Algorithms Unlocked, The MIT Press, (2013).
Cormen, T H, and J C Fan, "Dense Gray Codes, or Easy Ways to Generate Cyclic and Non-Cyclic Gray Codes For the First n Whole Numbers," 54th Annual Allerton Conference on Communication, Control, and Computing, October 2016.
Fan, J C, and T H Cormen, "Dense Gray Codes in Mixed Radices," 2017 IEEE Symposium on Information Theory (ISIT), June 2017.
Chaudhry, G, and T H Cormen, “Slabpose Columnsort: A New Oblivious Algorithm for Out-of Core Sorting on Distributed-memory Clusters,” Algorithmica, 45:3 (July 2006) 483-508.
Cormen, T H, and D M Nicol, "Performing Out-of-core FFTs on Parallel Disk Systems," Parallel Computing, 24:1 (January 1998) 5-20.
"Single methyl groups can act as toggle switches to specify transmembrane protein-protein interactions", L. He, H. Steinocher, A. Shelar, E. B. Cohen, E. N. Heim, B. B. Kragelund, G. Grigoryan, D. DiMaio, eLife, 6: e27701, 2017 [DOI].
"Sequence statistics of tertiary structural motifs reflect protein stability", F. Zheng, G. Grigoryan*, PLoS ONE, 12(5): e0178272, 2017 [PubMED] [DOI].
"Protein Structural Motifs in Prediction and Design", C. O. Mackenzie, G. Grigoryan, Current Opinion in Structural Biology, 44: 161-167, 2017 [PubMED] [DOI].
"Design of self-assembling transmembrane helical bundles to elucidate principles required for membrane protein folding and ion transport", N. H. Joh, G. Grigoryan, Y. Wu, W. F. DeGrado, Philosophical Transactions B, 372(1726): 20160214, 2017 [PubMED] [DOI].
"Tertiary Alphabet for the Observable Protein Structural Universe", C. O. Mackenzie, J. Zhou, G. Grigoryan, Proceedings of the National Academy of Sciences, 113(47): E7438-E7447, 2016 [PubMED] [DOI].
"Graphene Symmetry Amplified by Designed Peptide Self-Assembly", G.-M. Mustata, Y. H. Kim*, J. Zhang, W. F. DeGrado, G. Grigoryan, M. Wanunu, Biophysical Journal, 110(11): 2507-2516, 2016 [DOI].
"Protein-Directed Self-Assembly of a Fullerene Crystal", K-H. Kim, D-K. Ko, Y-T. Kim, N. H. Kim, J. Paul, S-Q. Zhang, C. B. Murray, R. Acharya, W. F. DeGrado, Y. H. Kim, G. Grigoryan, Nature Communications, 7: 11429, 2016 [DOI].
"Tertiary Structural Propensities Reveal Fundamental Sequence/Structure Relationships", F. Zheng, J. Zhang, G. Grigoryan, Structure, 23(5): 961-971, 2015 [DOI].
"Structure-based design of combinatorial mutagenesis libraries", D. Verma, G. Grigoryan, C. Bailey-Kellogg, Protein Science, 24(5): 895-908, 2015 [DOI].
"Computational Design and Experimental Characterization of Peptides Intended for pH-Dependent Membrane Insertion and Pore Formation", Y. Zhang, R. Bartz, G. Grigoryan, M. Bryant, J. Aaronson, S. Beck, N. Innocent, L. Klein, W. Procopio, T. Tucker, V. Jadhav, D. M. Tellers, William F. DeGrado, ACS Chemical Biology, 10(4): 1082-1093, 2015 [DOI].
"Computational Design of Selective Peptides to Discriminate Between Similar PDZ Domains in an Oncogenic Pathway", F. Zheng, H. Jewell, J. Fitzpatrick, J. Zhang, D. F. Mierke, G. Grigoryan, Journal of Molecular Biology, 427: 491-510, 2015 [DOI].
"De novo design of a transmembrane Zn2+ transporting four-helix bundle", N. H. Joh, T. Wang, M. P. Bhate, R. Acharya, Y. Wu, M. Grabe, M. Hong, G. Grigoryan, W. F. DeGrado, Science, 346(6216): 1520-1524, 2014 [DOI].
"Rapid Search for Tertiary Fragments Reveals Protein Sequence-Structure Relationships", J. Zhou, G. Grigoryan, Protein Science, [DOI] in press.
"Computational Design of Selective Peptides to Discriminate Between Similar PDZ Domains in an Oncogenic Pathway", F. Zheng, H. Jewell, J. Fitzpatrick, J. Zhang, D. F. Mierke, G. Grigoryan*, Journal of Molecular Biology, 2014 [DOI].
"Design and Designability of Protein-based Assemblies", J. Zhang, F. Zheng, G. Grigoryan*, Current Opinion in Structural Biology, 27: 79-86, 2014 [DOI].
"Absolute Free Energies of Biomolecules from Unperturbed Ensembles", G. Grigoryan,Journal of Computational Chemistry, 34: 2726–2741, 2013 [DOI].
"Mining Tertiary Structural Motifs for Assessment of Designability", J. Zhang, G. Grigoryan, Methods in Enzymology, 523: 21-40, 2013 [DOI].
"Structural Informatics, Modeling and Design with an Open Source Molecular Software Library (MSL)", D. W. Kulp, S. Subramaniam, J. E. Donald, B. T. Hannigan, B. K. Mueller, G. Grigoryan, A. Senes, Journal of Computational Chemistry, 33(20): 1645-1661, 2012 [DOI].
"Capture and Imaging of a Prehairpin Fusion Intermediate of the Paramyxovirus PIV5", Y. H. Kim, J. E. Donald, G. Grigoryan, G. P. Leser, A. Y. Fadeev , R. A. Lamb, W. F. DeGrado, Proc. Natl. Acad. Sci. USA, 108(52): 20992-20997, 2011 [DOI].
"Computational Design of Virus-like Protein Assemblies on Carbon Nanotube Surfaces", G. Grigoryan, Y. H. Kim, R. Acharya, K. Axelrod, R. M. Jain, L. Willis, M. Drndic, J. M. Kikkawa, and W. F. DeGrado, Science, 332(6033): 1071-1076, 2011 [DOI].
"Transmembrane Communication: General Principles and Lessons from the Structure and Function of the M2 Proton Channel, K+ Channels, and Integrin Receptors", G. Grigoryan, D. T. Moore, and W. F. DeGrado, Annual Review of Biochemistry, 80: 211-237, 2011 [DOI].
"Probing Designability via a Generalized Model of Helical Bundle Geometry", G. Grigoryan and W. F. DeGrado, Journal of Molecular Biology, 405(4): 1079-1100, 2011 [PubMED] [DOI].
"Identifying and Reducing Error in Cluster Expansion Approximations of Protein Energies", S. Hahn, O. Ashenberg, G. Grigoryan, and A. E. Keating, Journal of Computational Chemistry, 31(16): 2900-2914, 2010 [PubMED] [DOI].
"Identification of bZIP Interaction Partners of Viral Proteins HBZ, MEQ, BZLF1, and K-bZIP Using Coiled-Coil Arrays", A. W. Reinke, G. Grigoryan, and A. E. Keating, Biochemistry, 49(9): 1985-1997, 2010 [PubMED] [DOI].
"Design of Protein-interaction Specificity Gives Selective bZIP-binding Peptides", G. Grigoryan, A. W. Reinke, and A. E. Keating, Nature, 458: 859-864, 2009 [PubMED] [DOI].
"Cluster-Expansion Models for Flexible-Backbone Protein Energetics", J. R. Apgar, S. Hahn, G. Grigoryan, and A. E. Keating, Journal of Computational Chemistry, 30(15): 2402-2413, 2009 [PubMED] [DOI].
"Structural Specificity in Coiled-coil Interactions", G. Grigoryan and A. E. Keating, Current Opinion in Structural Biology, 18(4): 477-483, 2008 [PubMED] [DOI].
"Modest Membrane Hydrogen Bonds Deliver Rich Results", G. Grigoryan and W. F. DeGrado, Nature Chemical Biology, 4: 393-394, 2008 [PubMED] [DOI].
"Computing van der Waals Energies in the Context of the Rotamer Approximation", G. Grigoryan, A. Ochoa, and A. E. Keating, Proteins: Structure, Function, and Bioinformatics, 68(4): 863-878, 2007 [PubMED] [DOI].
"Ultra-fast Evaluation of Protein Conformational Energies Directly from Sequence", G. Grigoryan, F. Zhou, S. R. Lustig, G. Ceder, D. Morgan and A. E. Keating, PLoS Computational Biology, 2(6): e63, 2006 [PubMED] [DOI].
"Structure-based Prediction of bZIP Partnering Specificity", G. Grigoryan and A. E. Keating, Journal of Molecular Biology, 355(5): 1125-1142, 2006 [PubMED] [DOI].
Please see my Google Scholar: https://scholar.google.com/citations?user=SMRa4pEAAAAJ&hl=en
Houlihan, S. D., Kleiman-Weiner, M., Hewitt, L. B., Tenenbaum, J. B., & Saxe, R. (2023). Emotion prediction as computation over a generative theory of mind. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 381(2251), 20220047. https://doi.org/10.1098/rsta.2022.0047.
Houlihan, S. D., Ong, D., Cusimano, M., & Saxe, R. (2022). Reasoning about the antecedents of emotions: Bayesian causal inference over an intuitive theory of mind. Proceedings of the Annual Meeting of the Cognitive Science Society, 44, 854–861. https://escholarship.org/uc/item/7sn3w3n2.
Houlihan, S. D., Tenenbaum, J. B., & Saxe, R. (2021). Linking Models of Theory of Mind and Measures of Human Brain Activity. In M. Gilead & K. N. Ochsner (Eds.), The Neural Basis of Mentalizing (pp. 209–235). Springer International Publishing. https://doi.org/10.1007/978-3-030-51890-5_11.
Saxe, R., & Houlihan, S. D. (2017). Formalizing emotion concepts within a Bayesian model of theory of mind. Current Opinion in Psychology, 17, 15–21. https://doi.org/10.1016/j.copsyc.2017.04.019.
Weijia He, Nathan Reitinger, Atheer Almogbil, Yi-Shyuan Chiang, Timothy J. Pierson, and David Kotz. Contextualizing Interpersonal Data Sharing in Smart Homes. Proceedings of the Privacy Enhancing Technologies Symposium (PETS). July 2024. Accepted for publication. [Details]
Taylor Hardin and David Kotz. Amanuensis: provenance, privacy, and permission in TEE-enabled blockchain data systems. Proceedings of the IEEE International Conference on Distributed Computing Systems, pages 144–156. IEEE, July 2022. doi:10.1109/ICDCS54860.2022.00023. [Details]
Shengjie Bi and David Kotz. Eating detection with a head-mounted video camera. Proceedings of the IEEE International Conference on Healthcare Informatics, pages 60–66. IEEE, June 2022. doi:10.1109/ICHI54592.2022.00021. [Details]
Varun Mishra, Florian Künzler, Jan-Niklas Kramer, Elgar Fleisch, Tobias Kowatsch, and David Kotz. Detecting Receptivity for mHealth Interventions in the Natural Environment. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT/UbiComp), volume 5, number 2, article 74, 24 pages. ACM, June 2021. doi:10.1145/3463492. IMWUT Distinguished Paper Award (DPA). [Details]
George Boateng, Vivian Genaro Motti, Varun Mishra, John A. Batsis, Josiah Hester, and David Kotz. Experience: Design, Development and Evaluation of a Wearable Device for mHealth Applications. Proceedings of the International Conference on Mobile Computing and Networking (MobiCom), article 31, 14 pages. ACM, October 2019. doi:10.1145/3300061.3345432. [Details]
Timothy J. Pierson, Travis Peters, Ronald Peterson, and David Kotz. Proximity Detection with Single-Antenna IoT Devices. Proceedings of the ACM International Conference on Mobile Computing and Networking (MobiCom), article 21, 15 pages. ACM, October 2019. doi:10.1145/3300061.3300120. [Details]
David Kotz and Travis Peters. Challenges to ensuring human safety throughout the life-cycle of Smart Environments. Proceedings of the ACM Workshop on the Internet of Safe Things (SafeThings), pages 1–7. ACM, November 2017. doi:10.1145/3137003.3137012. [Details]
P. Belsare, A. Bartolome, C. Stanger, T. Prioleau, Understanding temporal changes and seasonal variations in glycemic trends using wearable data. Science Advances, vol. 9, issue 38, 2023. DOI:10.1126/sciadv.adg2132
T. Prioleau, A. Bartolome, R. Comi, C. Stanger. DiaTrend: A dataset from advanced diabetes technology to enable development of novel analytic solutions. Scientific Data 10, 556 (2023). https://doi.org/10.1038/s41597-023-02469-5
A. Bartolome and T. Prioleau, "A Computational Framework for Discovering Digital Biomarkers of Glycemic Control," npj Digital Medicine, vol. 5, no. 111, 2022. DOI: https://www.nature.com/articles/s41746-022-00656-z
A. Bartolome, S. Shah, T. Prioleau, "GlucoMine: A Case for Improving the Use of Wearable Device Data in Diabetes Management," Proc. ACM on Interactive, Mobile, Wearable, and Ubiquitous Technologies (IMWUT), vol. 5, no. 3, 2021. DOI: https://doi.org/10.1145/3478109
K. Gu, S. Vosoughi, T. Prioleau, "SymptomID: A Framework for Rapid Identification of Pandemics using News Reports," ACM Transactions on Management Information Systems (TMIS), vol. 12, no. 4, 2021. DOI: https://doi.org/10.1145/3462441
S. Morton, R. Li, S. Dibbo, T. Prioleau, "Data-driven Insights on Behavioral Factors that Affect Diabetes Management," IEEE Engineering in Medicine and Biology Conference (EMBC), 2020. DOI: 10.1109/EMBC44109.2020.9176414
T. Prioleau, A. Sabharwal, M. Vasudevan, "Understanding Reflection Needs for Personal Health Data in Diabetes." Int. Conf. on Pervasive Computing for Healthcare (PervasiveHealth), 2020. DOI: https://doi.org/10.1145/3421937.3421972
Bedri, R. Li, M. Haynes, R. Kosaraju, I. Grover, T. Prioleau, M. Beh, M. Goel, T. Starner, G. Abowd, "EarBit: Using Wearable Sensors to Detect Eating Episodes in Unconstrained Environments," Proc. ACM on Interactive, Mobile, Wearable, and Ubiquitous Technologies (IMWUT), vol. 1, no. 3, 2017. DOI: 10.1145/3130902
T. Prioleau, E. Moore, M. Ghovanloo, "Unobtrusive and Wearable Systems for Automatic Dietary Monitoring," IEEE Trans. of Biomedical Engineering (TBME), vol. 64, no. 9, 2017. DOI: 10.1109/TBME.2016.2631246.
S. Lensgraf, D. Balkcom, and A. Quattrini Li, "Buoyancy enabled autonomous underwater construction with cement blocks," in IEEE International Conference on Robotics and Automation (ICRA), 2023
S. Rahman, A. Quattrini Li, and I. Rekleitis, "SVIn2: A multi-sensor fusion-based underwater SLAM system," The International Journal of Robotics Research, vol. 41, no. 11-12, pp. 1022–1042, 2022.
M. Roznere and A. Quattrini Li, "Underwater monocular depth estimation using single-beam echo sounder," in Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), 2020.
M. Jeong and A. Quattrini Li, "Risk Vector-based Near miss and Real-time Obstacle Avoidance for Autonomous Surface Vehicles," in Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), 2020.
A. Quattrini Li, P. K. Penumarthi, J. Banfi, N. Basilico, J. O'Kane, I. Rekleitis, S. Nelakuditi, and F. Amigoni, "Multi-robot Online Sensing Strategies for the Construction of Communication Maps," Autonomous Robots,1–21. 2019.
J. Banfi, A. Quattrini Li, I. Rekleitis, F. Amigoni, and N. Basilico, "Strategies for coordinated multirobot exploration with recurrent connectivity constraints," Autonomous Robots, vol. 42, pp. 875–894, 2018.
S. Manjanna, A. Quattrini Li, R. N. Smith, I. Rekleitis, and G. Dudek, "Heterogeneous multirobot system for exploration and strategic water sampling," in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2018.
A. Quattrini Li, R. Fioratto, F. Amigoni, and V. Isler, "A search-based approach to solve pursuit-evasion games with limited visibility in polygonal environments," in Proceedings of the International Conference on Autonomous & Multiagent Systems (AAMAS), 2018.
A. Quattrini Li, R. Cipolleschi, M. Giusto, and F. Amigoni, "A semantically-informed multirobot system for exploration of relevant areas in search and rescue settings," Autonomous Robots, vol. 40, no. 4, pp. 581–597, 2016.
A. Quattrini Li, M. Xanthidis, J. M. O'Kane, and I. Rekleitis, "Active localization with dynamic obstacles," in Proceedings of the IEEE/RSJ International Conference on Intelligent Robotics Systems (IROS), 2016, pp. 1902–1909.
D. Rockmore (ed.). (2017). What are the Arts and Sciences? A Guide for the Curious. UPNE.
C. Fang, N. Foti, D. Krakauer, and T. Ginsburg, D. Rockmore, The Cultural Evolution of National Constitutions, Journal of the Association for Information Science and Technology. To appear, 2017. Online https://papers.ssrn.com/sol3/papers.cfm?abstract id=2739824.
D. Maslen, D. N. Rockmore, and S. Wolff. (2016). The Efficient Computation of Fourier Transforms on Semisimple Algebras. Journal of Fourier Analysis and Applications. DOI: 10.1007/s00041-017-9555-5.
S. Brocklebank, S. Pauls, D. Rockmore, and T. Bates. (2015). A Spectral Clustering Approach to the Structure of Personality: Contrasting the FFM and HEXACO Models, Journal of Research in Personality, 57, 100109.
F. Caccioli, D. Farmer, N. Foti, and D. Rockmore. (2015).Overlapping Portfolios, Contagion, and Financial Stability. J. Econ. Dynamics and Control, Volume 51, pp. 50–63.
Rockmore, D, J D Van Horn, S T Grafton, and M S Gazzaniga, "Sharing Neuroimaging Studies of Human Cognition," Nature Neuroscience , 7 (2004) 473-481.
D. Rockmore, S. Lyu and H. Farid. (2004). A Digital Technique for Art Authentication. PNAS, Proceedings of the National Academy of Sciences, 101:49 (2004) 17006-17010.
Sean W. Smith.
The Internet of Risky Things: Trusting the Devices that Surround Us.
O'Reilly. 2017.
P. Anantharaman, K. Palani, D. Nicol, S.W. Smith.
"I am Joe's Fridge: Scalable Identity in the Internet of Things"
IEEE International Conference on Internet of Things.
December 2016.
S. Bratus, M. Patterson, A. Crain, S. Hallberg, S.W. Smith.
"Implementing a Vertically Hardened DNP3 Control Stack for Power Applications."
ACSAC Industrial Control System Security Workshop.
December 2016.
S.W. Smith, R. Koppel, J. Blythe, V. Kothari.
"Mismorphism: a Semiotic Model of Computer Security Circumvention"
International Symposium on Human Aspects of Information Security and Assurance (HAISA 2015).
July 2015
V. Kothari, J. Blythe, S.W. Smith, R. Koppel.
"Measuring the Security Impacts of Password Policies Using Cognitive Behavioral Agent-Based Modeling."
ACM Symposium and Bootcamp on the Science of Security (HotSoS).
April 2015.
P. Johnson, S. Bratus, S.W. Smith.
"Protecting Against Malicious Bits On the Wire: Automatically Generating a USB Protocol Parser for a Production Kernel."
Annual Computer Security Applications Conference (ACSAC)
December 2017
S.W. Smith.
"Security and Cognitive Bias: Exploring the Role of the Mind."
IEEE Security and Privacy.
September/October 2012. 10 (5): 75--78. September/October 2012.
Sean W. Smith, John C. Marchesini.
The Craft of System Security.
Addison-Wesley. 2007.
Please check my Google Scholar:
https://scholar.google.com/citations?user=nFhLmFkAAAAJ&hl=en
G. Bertasius, H. Wang, and L. Torresani. "Is space-time attention all you need for video understanding?" International Conference on Machine Learning, ICML, 2021.
G. Bertasius, and L. Torresani. "Classifying, Segmenting, and Tracking Object Instances in Video with Mask Propagation," IEEE Conference On Computer Vision and Pattern Recognition, CVPR, 2020.
B. Korbar, D. Tran, and L. Torresani. "Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization," Advances in Neural Information Processing Systems, NeurIPS, 2018.
D. Tran, H. Wang, L. Torresani, J. Ray, Y. LeCun, and M. Paluri. "A Closer Look at Spatiotemporal Convolutions for Action Recognition," IEEE Conference On Computer Vision and Pattern Recognition, CVPR, 2018.
G. Bertasius, J. Shi, and L. Torresani. "DeepEdge: A Multi-Scale Bifurcated Deep Network for Top- Down Contour Detection," IEEE Conference On Computer Vision and Pattern Recognition, CVPR, 2015.
D. Tran, L. Bourdev, R. Fergus, L. Torresani, and M. Paluri. "Learning Spatiotemporal Features with 3D Convolutional Networks," IEEE International Conference On Computer Vision, ICCV, 2015.
A. Bergamo, and L. Torresani. "Exploiting weakly-labeled Web images to improve object classification: a domain adaptation approach," Advances in Neural Information Processing Systems, NIPS, 2010.
L. Torresani, M. Szummer, and A. Fitzgibbon. "Efficient Object Category Recognition Using Classemes," European Conference On Computer Vision, ECCV, 2010.
L. Torresani, V. Kolmogorov, and C. Rother. "Feature Correspondence via Graph Matching: Models and Global Optimization," European Conference On Computer Vision, ECCV, 2008.
L. Torresani, A. Hertzmann, and C. Bregler. "Non-Rigid Structure-From-Motion: Estimating Shape and Motion with Hierarchical Priors." IEEE Transactions on Pattern Analysis and Machine Intelligence, TPAMI, 30(5):878-892, May 2008.
The sleeping beauty controversy, American Mathematical Monthly 124 #7 (Aug-Sept 2017), 579-587.
Cop vs. gambler (with N. Komarov), Discrete Mathematics 339 #6 (June 2016), 1677-1681.
Hunter, Cauchy rabbit and optimal Kakeya sets (with Y. Babichenko, Y. Peres, R. Peretz, and P. Sousi), Transactions of the AMS 366 #10 (Oct. 2014), 5567-5586.
The phase transition for dyadic tilings (with O. Angel, A. Holroyd, G. Kozma, and J. Wastlund), Transactions of the AMS 366 #2 (Feb. 2014), 1029-1046.
Can extra updates delay mixing? (with Y. Peres), Communications in Mathematical Physics 323 (2013), 1007-1016.
Proof of the Squashed Cube Conjecture, Combinatorica 3 #1 (1983), 135-139.
Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks. Yujun Yan, Milad Hashemi, Kevin Swersky, Yaoqing Yang, Danai Koutra. The IEEE International Conference on Data Mining (ICDM) 2022.
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs. Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra. Conference on Neural Information Processing Systems (NeurIPS) 2020.
Neural Execution Engines: Learning to Execute Subroutines. Yujun Yan, Kevin Swersky, Danai Koutra, Parthasarathy Ranganathan, Milad Hashemi. Conference on Neural Information Processing Systems (NeurIPS) 2020.
Da-Yuan Huang, Ruizhen Guo, Jun Gong, Jingxian Wang, John Graham, De-Nian Yang & Xing-Dong Yang. (2017). RetroShape: Leveraging Rear-Surface Shape Displays for 2.5D Interaction on Smartwatches. Proceedings of the ACM Symposium on User Interface Software &Technology (UIST'17), 539-551.
Teng Han, Qian Han, Michelle Annett, Fraser Anderson, Da-Yuan Huang & Xing-Dong Yang. (2017). Frictio: Passive Kinesthetic Force Feedback for Smart Ring Output. Proceedings of the ACM Symposium on User Interface Software &Technology (UIST'17), 131-142 .
Jun Gong, Yang Zhang, Xia Zhou & Xing-Dong Yang. (2017). Pyro: Thumb-Tip Gesture Recognition Using Pyroelectric Infrared Sensing. Proceedings of the ACM Symposium on User Interface Software &Technology (UIST'17), 553-563.
Teddy Seyed, Xing-Dong Yang & Daniel Vogel. (2017). A Modular Smartphone for Lending. Proceedings of the ACM Symposium on User Interface Software &Technology (UIST'17), 205-215
Jun Gong, Lan Li, Daniel Vogel & Xing-Dong Yang. (2017). Cito: An Actuated Smartwatch for Extended Interactions. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI'17), 5331-5345.
Roman Kogay, Sonja Koppenhöfer, J Thomas Beatty, Jens H Kuhn, Andrew S Lang, Olga Zhaxybayeva (2022): "Formal recognition and classification of gene transfer agents as viriforms." Virus Evolution, 8: veac100.
Roman Kogay and Olga Zhaxybayeva (2022): "Selection for Translational Efficiency in Genes Associated with Alphaproteobacterial Gene Transfer Agents." mSystems, 7: e0089222.
Zhengshuang Hua, Matthew Ouellette, Andrea M. Makkay, R. Thane Papke, and Olga Zhaxybayeva (2021): "Nutrient supplementation experiments with saltern microbial communities implicate utilization of DNA as a source of phosphorus", ISME Journal, 15: 2843-2864
Emma S. Esterman, Yuri I. Wolf, Roman Kogay, Eugene V. Koonin, and Olga Zhaxybayeva (2021): "Evolution of DNA packaging in gene transfer agents", Virus Evolution, 7: veab015.
Roman Kogay, Yuri I Wolf, Eugene V Koonin, and Olga Zhaxybayeva (2020): "Selection for Reducing Energy Cost of Protein Production Drives the GC Content and Amino Acid Composition Bias in Gene Transfer Agents", mBio, 11:e01206-20.
Chase WR, Zhaxybayeva O, Rocha J, Cosgrove DJ, Shapiro LR. (2020) "Global cellulose biomass, horizontal gene transfers and domain fusions drive microbial expansin evolution." New Phytol., 226:921-938.
Kogay R, Neely TB, Birnbaum DP, Hankel CR, Shakya M, Zhaxybayeva O. (2019): "Machine-learning classification suggests that many alphaproteobacterial prophages may instead be gene transfer agents", Genome Biol Evol., evz206.
Bauer KM, Dicovitsky R, Pellegrini M, Zhaxybayeva O, Ragusa MJ. (2019): "The structure of a highly-conserved picocyanobacterial protein reveals a Tudor domain with an RNA-binding function", J Biol Chem., 294:14333-14344.
Stephen M. J. Pollo, Abigail A. Adebusuy, Timothy J. Straub, Julia M. Foght, Olga Zhaxybayeva, Camilla L. Nesbo (2017) "Genomic insights and temperature-dependent transcriptional responses of Kosmotoga olearia, a deep-biosphere bacterium that can grow from 20C to 79C", Extremophiles, 21:963-979.
Complete list of publications is available at https://labofoz.host.dartmouth.edu/2.0/publications-2/
Shiying Xiong, Yunjin Tong, Xingzhe He, Cheng Yang, Shuqi Yang, Bo Zhu. Nonseparable Symplectic Neural Networks. International Conference on Learning Representations (ICLR 2021).
Yitong Deng, Yaorui Zhang, Xingzhe He, Shuqi Yang, Yunjin Tong, Michael Zhang, Daniel M. DiPietro, Bo Zhu. Soft Multicopter Control using Neural Dynamics Identification. Conference on Robot Learning (CoRL 2020).
Shuqi Yang, Xingzhe He, Bo Zhu. Learning Physical Constraints with Neural Projections. Neural Information Processing Systems (NeurIPS 2020).
Daniel M. DiPietro, Shiying Xiong, Bo Zhu. Sparse Symplectically Integrated Neural Networks, Neural Information Processing Systems (NeurIPS 2020).
Hui Wang, Yongxu Jin, Anqi Luo, Xubo Yang, Bo Zhu. Codimensional Surface Tension Flow using Moving-Least-Squares Particles. ACM Transactions on Graphics (SIGGRAPH 2020).
Xingyu Ni, Bo Zhu, Bin Wang, Baoquan Chen. A Level-Set Method for Magnetic Substance Simulation. ACM Transactions on Graphics (SIGGRAPH 2020).
Desai Chen, Melina Skouras, Bo Zhu, Wojciech Matusik. 2018. Computational Discovery of Extremal Microstructure Families. Science Advances 4(1), 2018.
Bo Zhu, Melina Skouras, Desai Chen, Wojciech Matusik. Two-scale Topology Optimization with Microstructures. ACM Transactions on Graphics, 36(5):164, 2017.