Computational

Department of Geology and Environmental Science
Ph.D. Geophysics, Stanford University, 1987
Summary:

Dr. Harbert’s research focus includes the geomechanical analysis of microseismicity in organic shale, advanced seismic processing and interpretation related to subsurface imaging and analysis, and a rock physics-based determination of dynamic acoustic and mechanical properties of geologic units. He has also been involved with environmental geophysical technologies relevant to remote subsurface water quality and topology analysis.  He and his students and collaborators are actively work on the application of Deep Learning methods to seismic emissions and geophysical object detection and classification. The research of this group is the analysis of microseismic, reflection seismic, VSP and fluid and structure using advanced processing and attributes. The group works to accurately image surface geometry using geophysical techniques and advanced geophysical processing. The goal of this research is to better understand subsurface structures, subsurface pore filling phases and topologies and dynamic processes at a variety of scales, from micro computer tomography (CT) scale to log response scale, to vertical seismic profile and cross well tomography scales and surface seismic response scale.

Selected Publications: 
  1. Kirchen, K., Harbert, W., Apt, J., and Morgan, M. G., 2020, A Solar-Centric Approach to Improving Estimates of Exposure Processes for Coronal Mass Ejections, Risk Analysis, 40, 1020-1039, DOI: 10.1111/risa.13461.
  2. Kumar, A., Bear, A., Hu, H., Hammack, R., Harbert, W., Ampomah, W., Balch, R., Garcia, L, Nolte, A., Tsoflias, G., 2019, Seismic monitoring of CO2-EOR operations in the Texas Panhandle and southern Kansas using surface seismometers, SEG 2019 Annual Meeting, DVD Extended Abstracts.
  3. Larsen, Darren, J., Crump, Sarah E., Abbott, Mark B., Harbert, William, Blumm, Aria, Wattrus, Nigel J., Hebberger, John J. , 2019, Paleoseismic evidence for climatic and magmatic controls on the Teton fault, WY, Geophysical Research Letters, 46, p. 13036-13043.
  4. Shi, Z., Sun, L., Haljasmaa, I., Harbert, W., Sanguinito, S., Tkach, M., Goodman, A., Tsotsis, T. T., and Jessen, K., 2019, Impact of Brine/CO2 Exposure on the Transport and Mechanical Properties of the Mt. Simon Sandstone, Journal of Petroleum Science and Engineering, 117, p. 295-305.
  5. Zorn, Erich, Kumar, Abhash, Harbert, William and Hammack, Richard, 2019, Geomechanical Analysis of Microseismicity in Organic Shale: A West Virginia Marcellus Shale Example, Interpretation, 7, T231-T239.
Most Cited Publications

1. "Evolution of the Mongol-Okhotsk Ocean as constrained by new palaeomagnetic data from the Mongol-Okhotsk suture zone", Siberia
VA Kravchinsky, JP Cogné, WP Harbert, MI Kuzmin, Geophysical Journal International 148 (1), 34-57 (2002)
2. "Late Neogene motion of the Pacific plate" W Harbert, A Cox, Journal of Geophysical Research: Solid Earth 94 (B3), 3052-3064 (1989)
3. "Late Neogene relative motions of the Pacific and North America plates", W Harbert, Tectonics 10 (1), 1-15 (1991)
4. "Plate motions recorded in tectonostratigraphic terranes of the Franciscan Complex and evolution of the Mendocino triple junction, northwestern California", RJ McLaughlin, WV Sliter, NO Frederiksen, WP Harbert, DS McCulloch, US Geological Survey Bulletin 1997 (1994)
5. "An evaluation of fracture growth and gas/fluid migration as horizontal Marcellus Shale gas wells are hydraulically fractured in Greene County, Pennsylvania",R Hammack, W Harbert, S Sharma, B Stewart, R Capo, A Wall, National Energy Technology Laboratory: NETL-TRS-3-2014, 76 (2014)
 

Recent Publications

1. Wang, Z., Dilmore, R. M., & Harbert, W. (2019). Machine Learning for Leakage Detection at CO 2 Sequestration Sites: Inferring CO 2 Saturation from Synthetic Surface Seismic and Downhole Monitoring Data. AGUFM2019, S31E-0579.
2. Larsen, D. J., Crump, S. E., Abbott, M. B., Harbert, W., Blumm, A., Wattrus, N. J., & Hebberger, J. J. (2019). Paleoseismic evidence for climatic and magmatic controls on the Teton fault, WY. Geophysical Research Letters46(22), 13036-13043.
3. Shi, Z., Sun, L., Haljasmaa, I., Harbert, W., Sanguinito, S., Tkach, M., ... & Jessen, K. (2019). Impact of Brine/CO2 exposure on the transport and mechanical properties of the Mt Simon sandstone. Journal of Petroleum Science and Engineering177, 295-305.
4. Kumar, A., Zorn, E., Hammack, R., & Harbert, W. (2019). Long-period, long-duration seismic events and their probable role in reservoir stimulation and stage productivity. SPE Reservoir Evaluation & Engineering22(02), 441-457.
5. Zorn, E., Kumar, A., Harbert, W., & Hammack, R. (2019). Geomechanical analysis of microseismicity in an organic shale: A West Virginia Marcellus Shale example. Interpretation7(1), T231-T239.

Department of Chemistry, Carnegie Mellon University
PhD, Theoretical Chemistry, Jackson State University
Summary:

The Isayev lab works at the interface of theoretical chemistry, pharmaceutical sciences and computer science. In particular, we are using molecular simulations and artificial intelligence (AI) to solve hard problems in chemistry. We are working towards the acceleration of molecular discovery by the combination of AI, informatics and high-throughput quantum chemistry. We also focus on both generative and predictive ML models for chemical and biological data. Details on specific projects can be found below.

Accelerating computational chemistry with deep learning: We are developing fully transferable deep learning potentials for molecular and materials systems. Such atomistic potentials are highly accurate compared to reference QM calculations at speeds 107faster. Neural network potentials are shown to accurately represent the underlying physical chemistry of molecules through various test cases including chemical reactions, kinetics, thermochemistry, structural optimization, and molecular dynamics simulations.

Materials informatics: Material informatics is a rapidly emerging data- and knowledge-driven approach for the identification of novel materials for a range of applications, including solar energy conversion. As the proliferation of high-throughput methods in chemical sciences is increasing the wealth of data in the field, the gap between accumulated-information and derived knowledge widens. We address the issue of scientific discovery in chemical and biological databases by introducing novel analytical approaches based on large-scale data mining and machine learning.

De Novo molecular design: The de novo molecular design problem involves generating novel molecular structures or focused molecular libraries with desirable properties. It solves a so-called inverse design problem. We develop artificial intelligence method that enables the design of chemical libraries with the desired physicochemical and biological properties or both.

Most Cited Publications
  1. "Machine learning for molecular and materials science," Keith T Butler, Daniel W Davies, Hugh Cartwright, Olexandr Isayev, Aron Walsh. Nature, 559, 547-555 (2018)
  2. "ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost," Justin S Smith, Olexandr Isayev, Adrian E Roitberg. Chemical science, 8, 3192-3203 (2017)
  3. "Universal fragment descriptors for predicting properties of inorganic crystals," Olexandr Isayev, Corey Oses, Cormac Toher, Eric Gossett, Stefano Curtarolo, Alexander Tropsha. Nature communications, 8, 1-12 (2017)
  4. "Materials cartography: representing and mining materials space using structural and electronic fingerprints," Olexandr Isayev, Denis Fourches, Eugene N Muratov, Corey Oses, Kevin Rasch, Alexander Tropsha, Stefano Curtarolo. Chemistry of Materials, 27, 735-743 (2015)
  5. "Deep reinforcement learning for de novo drug design," Mariya Popova, Olexandr Isayev, Alexander Tropsha. Science advances, 4, eaap7885 (2018)
Recent Publications
  1. "Crowdsourced mapping of unexplored target space of kinase inhibitors," Anna Cichonska, Balaguru Ravikumar, Robert J Allaway, Sungjoon Park, Fangping Wan, Olexandr Isayev, Shuya Li, Michael J Mason, Andrew Lamb, Minji Jeon, Sunkyu Kim, Mariya Popova, Jianyang Zeng, Kristen Dang, Gregory Koytiger, Jaewoo Kang, Carrow I Wells, Timothy M Willson, Tudor I Oprea, Avner Schlessinger, David H Drewry, Gustavo A Stolovitzky, Krister Wennerberg, Justin Guinney, Tero Aittokallio. bioRxiv, (2020)
  2. "Predicting Thermal Properties of Crystals Using Machine Learning," Sherif Abdulkader Tawfik, Olexandr Isayev, Michelle JS Spencer, David A Winkler. Advanced Theory and Simulations, 1900208, (2019)
  3. "Impressive computational acceleration by using machine learning for 2-dimensional super-lubricant materials discovery," Marco Fronzi, Mutaz Abu Ghazaleh, Olexandr Isayev, David A Winkler, Joe Shapter, Michael J Ford. arXiv preprint arXiv, 1911.11559 (2019)
  4. "The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules," Justin S Smith, Roman Zubatyuk, Benjamin T Nebgen, Nicholas Lubbers, Kipton Barros, Adrian Roitberg, Olexandr Isayev, Sergei Tretiak. ChemRxiv (2019)
  5. "Inter-Modular Linkers play a crucial role in governing the biosynthesis of non-ribosomal peptides," Sherif Farag, Rachel M Bleich, Elizabeth A Shank, Olexandr Isayev, Albert A Bowers, Alexander Tropsha. Bioinformatics, 35, 3584-3591, (2019)
Tepper School of Business, Carnegie Mellon University
PhD, Operations Research and Industrial Engineering, Cornell University
Summary:

The research of the Quantum Computing Group (QCG) at the Tepper School focuses on the creation of radically different types of algorithms to optimize complex large-scale industrial problems startlingly faster, with the ultimate desired outcome of commercialized algorithms that are easily accessible for practical application.

QCG research takes place in three parallel areas:

  • Solving practical problems using novel quantum and quantum-inspired algorithms.
  • Developing robust and efficient processes of translating a mathematical algorithm into physical instructions executed by the hardware — known as compilers — for quantum computers.
  • Understanding and enhancing quantum speedup: how and why speed is increased, and by how much.
Selected Publications: 
  • "A Novel Algebraic Geometry Compiling Framework for Adiabatic Quantum Computations." Raouf Dridi, Hedayat Alghassi, Sridhar TayurarXiv:1810.01440
  • "Graver Bases via Quantum Annealing with Application to Non-Linear Integer Programs." Hedayat Alghassi, Raouf Dridi, Sridhar Tayur. arXiv:1902.04215
  • "Quantum and Quantum-inspired Methods for de novo Discovery of Altered Cancer Pathways." Hedayat Alghassi, Raouf Dridi, A Gordon Robertson, Sridhar Tayur. bioRxiv 845719
  • "Knuth-Bendix Completion Algorithm and Shuffle Algebras For Compiling NISQ Circuits." Raouf Dridi, Hedayat Alghassi, Sridhar TayurarXiv:1905.00129
  • "Enhancing the efficiency of adiabatic quantum computations." Raouf Dridi, Hedayat Alghassi, Sridhar TayurarXiv:1903.01486
Most Cited Publications
  1. "Value of information in capacitated supply chains." Srinagesh Gavirneni, Roman Kapuscinski, Sridhar TayurManagement Science.
  2. "Quantitative models for supply chain management." Sridhar Tayur, Ram Ganeshan, Michael Magazine. Kluwer.
  3. "Models for supply chains in e-business." Jayashankar M Swaminathan, Sridhar R TayurManagement Science.
  4. "Managing broader product lines through delayed differentiation using vanilla boxes." Jayashankar M Swaminathan, Sridhar R TayurManagement Science.
  5. "Sensitivity analysis for base-stock levels in multiechelon production-inventory systems." Paul Glasserman, Sridhar Tayur. Management Science.
Recent Publications
  1. "Integer programming techniques for minor-embedding in quantum annealers." David E Bernal, Kyle EC Booth, Raouf Dridi, Hedayat Alghassi, Sridhar Tayur, Davide Venturelli. arXiv preprint arXiv:1912.08314.
  2. "The Topology of Mutated Driver Pathways." Raouf Dridi, Hedayat Alghassi, Maen Obeidat, Sridhar TayurarXiv preprint arXiv:1912.00108.
  3. "Online-to-Offline Platform Models." Joseph Xu, Hui Li, Sridhar R Tayur. SSRN 3449744.
  4. "Healthcare operations management: A snapshot of emerging research." Tinglong Dai, Sridhar TayurManufacturing & Service Operations Management.
  5. "GAMA: A Novel Algorithm for Non-Convex Integer Programs." Hedayat Alghassi, Raouf Dridi, Sridhar TayurarXiv preprint arXiv:1907.10930.
Department of Chemical & Petroleum Engineering
Ph.D. Chemical Engineering, Northwestern University, 2013
Summary:

Our group designs hypothetical materials to help address energy and environmental challenges. We are interested in creating sophisticated nanostructures; potentially as complex (and useful) as molecular machines found in Nature. Our strategy is to computationally design and study new materials and then work work with our experimental collaborators to synthesize those materials in the lab. We are active software developers, and we build new computational tools to address problems nobody has tackled before.

Most Cited Publications
  1. "Nanoscale forces and their uses in self‐assembly." Kyle JM Bishop, Christopher E Wilmer, Siowling Soh, Bartosz A Grzybowski. small.
  2. "Metal–organic framework materials with ultrahigh surface areas: is the sky the limit?." Omar K Farha, Ibrahim Eryazici, Nak Cheon Jeong, Brad G Hauser, Christopher E Wilmer, Amy A Sarjeant, Randall Q Snurr, SonBinh T Nguyen, A Özgür Yazaydın, Joseph T Hupp. Journal of the American Chemical Society.
  3. "Review and analysis of molecular simulations of methane, hydrogen, and acetylene storage in metal–organic frameworks." Rachel B Getman, Youn-Sang Bae, Christopher E Wilmer, Randall Q Snurr. Chemical reviews.
  4. "Large-scale screening of hypothetical metal–organic frameworks." Christopher E Wilmer, Michael Leaf, Chang Yeon Lee, Omar K Farha, Brad G Hauser, Joseph T Hupp, Randall Q Snurr. Nature Chemistry.
  5. "Light-harvesting and ultrafast energy migration in porphyrin-based metal–organic frameworks." Ho-Jin Son, Shengye Jin, Sameer Patwardhan, Sander J Wezenberg, Nak Cheon Jeong, Monica So, Christopher E Wilmer, Amy A Sarjeant, George C Schatz, Randall Q Snurr, Omar K Farha, Gary P Wiederrecht, Joseph T Hupp. Journal of the American Chemical Society.
Recent Publications
  1. "The role of molecular modelling and simulation in the discovery and deployment of metal-organic frameworks for gas storage and separation." Arni Sturluson, Melanie T Huynh, Alec R Kaija, Caleb Laird, Sunghyun Yoon, Feier Hou, Zhenxing Feng, Christopher E Wilmer, Yamil J Colón, Yongchul G Chung, Daniel W Siderius, Cory M Simon. Molecular Simulation.
  2. "Heat flux for many-body interactions: Corrections to LAMMPS." Paul Boone, Hasan Babaei, Christopher E Wilmer. Journal of chemical theory and computation.
  3. "Intelligent selection of metal-organic framework arrays for methane sensing via genetic algorithms." Jenna Ann Gustafson, Christopher E Wilmer. ACS sensors.
  4. "Designing a SAW Sensor Array with MOF Sensing Layers for Carbon Dioxide and Methane." Jagannath Devkota, Paul R Ohodnicki, Jenna A Gustafson, Christopher E Wilmer, David W Greve. 2019 Joint Conference of the IEEE International Frequency Control Symposium and European Frequency and Time Forum (EFTF/IFC).
  5. "High-throughput calculations of metal organic frameworks: Mixed matrix membranes for carbon capture." Jan Steckel, Samir Budhathoki, Paul Boone, Christopher Wilmer. ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY.
Pittsburgh Supercomputing Center and Dept. of Physics, Carnegie Mellon University
Ph.D. in Chemistry, University of Pittsburgh, 1992
Summary:

Dr. Nicholas A. (Nick) Nystrom is the chief scientist of the Pittsburgh Supercomputing Center (PSC), a national computing center founded 1986 that is a joint effort of Carnegie Mellon University and the University of Pittsburgh. He joined PSC in 1992 as scientific programmer. He most recently served as interim director and senior research director. He has held the position of research physicist at Carnegie Mellon University since 2004. He received his Ph.D. in chemistry in 1992 from the University of Pittsburgh.

Dr. Nystorm is the architect, principal investigator (PI), and project director (PD) for “Bridges”, PSC’s flagship platform that was the first to successfully converge HPC, AI, and Big Data. He is also PI for the Data Exacell, a research pilot for enabling high performance data analytics on novel storage; co-PI for Open Compass, which brings emerging AI technologies to important problems in research; co-I for the Center for Causal Discovery, an NIH Big Data to Knowledge (BD2K) Center of Excellence; and co-I for Big Data for Better Health, which applies machine learning to lung and breast cancer research.

Dr. Nystorm's research interest includes data analytics, Big Data, causal modeling, graph algorithms, genomics, machine learning / deep learning, extreme scalability, hardware and software architecture, software engineering for HPC, performance modeling and prediction, impacts of programming models and languages on productivity and efficiency, information visualization, and quantum chemistry. Recent work has focused on enabling data-intensive research in domains new to HPC, scaling diverse computational science codes and workflows to extreme-scale systems, deep hierarchies of parallelism, advanced filesystems, and architectural innovations in processors and interconnects.

Most Cited Publications
  • "Identifying driver genomic alterations in cancers by searching minimum-weight, mutually exclusive sets," Lu, S., Lu, K., Cheng, S.-Y., (...), Nystrom, N., Lu, X., BIBM (2015).
  • "Bridges: A uniquely flexible HPC resource for new communities and data analytics," Nystrom, N.A., Levine, M.J., Roskies, R.Z., Scott, J.R., International Conference Proceeding Series (2015).
  • "Porting third-party applications packages to the Cray T3D: Programming issues and scalability results," Wimberly, F.C., Lambert, M.H., Nystrom, N.A., Ropelewski, A., Young, W., Parallel Computing (1996).
Recent Publications
  • "Identifying driver genomic alterations in cancers by searching minimum-weight, mutually exclusive sets," Lu, S., Lu, K., Cheng, S.-Y., (...), Nystrom, N., Lu, X., BIBM (2015).
  • "Bridges: A uniquely flexible HPC resource for new communities and data analytics," Nystrom, N.A., Levine, M.J., Roskies, R.Z., Scott, J.R., International Conference Proceeding Series (2015).
  • "Porting third-party applications packages to the Cray T3D: Programming issues and scalability results," Wimberly, F.C., Lambert, M.H., Nystrom, N.A., Ropelewski, A., Young, W., Parallel Computing (1996).
School of Computing and Information, University of Pittsburgh
Ph.D. Computer Science, University of Maryland, College Park, 1993
Summary:

Daniel's main research interest is in the allocation of resources (computing and network resources) in the realm of real-time, with main concerns being power management, security, and fault tolerance. He bridges the gap between the operating systems and networking research fields, between practice and theory.

Lately, he has also been focusing on how to increase diversity in computing and how to promote reproducible research in computing.

Most Cited Publications
  1. Jejurikar, R., Pereira, C., & Gupta, R. (2004, June). Leakage aware dynamic voltage scaling for real-time embedded systems. In Proceedings of the 41st annual Design Automation Conference (pp. 275-280). ACM.
  2. Aydin, H., Melhem, R., Mossé, D., & Mejía-Alvarez, P. (2004). Power-aware scheduling for periodic real-time tasks. IEEE Transactions on Computers53(5), 584-600.
  3. Zhu, D., Melhem, R., & Mossé, D. (2004, November). The effects of energy management on reliability in real-time embedded systems. In Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design (pp. 35-40). IEEE Computer Society.
  4. Aydin, H., Melhem, R., Mossé, D., & Mejía-Alvarez, P. (2001, June). Determining optimal processor speeds for periodic real-time tasks with different power characteristics. In Proceedings 13th Euromicro Conference on Real-Time Systems (pp. 225-232). IEEE.
  5. Aydin, H., Melhem, R., Mosse, D., & Mejía-Alvarez, P. (2001). Optimal reward-based scheduling for periodic real-time tasks. IEEE Transactions on Computers50(2), 111-130.
Recent Publications
  1. Zacarias, F. V., Petrucci, V., Nishtala, R., Carpenter, P., & Mossé, D. (2019, October). Intelligent Colocation of Workloads for Enhanced Server Efficiency. In 2019 31st International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) (pp. 120-127). IEEE.
  2. Wang, W., Mosse, D., & Papadopoulos, A. V. (2019, May). Packet Priority Assignment for Wireless Control Systems of Multiple Physical Systems. In 2019 IEEE 22nd International Symposium on Real-Time Distributed Computing (ISORC) (pp. 143-150). IEEE.
  3. Petrov, D., Alseghayer, R., Mossé, D., & Chrysanthis, P. K. (2018, October). Data-Driven User-Aware HVAC Scheduling. In 2018 Ninth International Green and Sustainable Computing Conference (IGSC) (pp. 1-8). IEEE.
  4. Mofrad, M. H., & Mosse, D. (2018, October). Speech recognition and voice separation for the internet of things. In Proceedings of the 8th International Conference on the Internet of Things (p. 8). ACM.
  5. Oliveira, L., Wilkinson, D., Mossé, D., & Childers, B. R. (2018, October). Occam: Software environment for creating reproducible research. In 2018 IEEE 14th International Conference on e-Science (e-Science) (pp. 394-395). IEEE.

 

Department of Information Culture and Data Stewardship, University of Pittsburgh
Ph.D. Computer Science, University of Virginia, 2000
Summary:

Dr. Bruce Childers is the Senior Associate Dean in the School of Computing and Information, Chair of the Department of Information Culture and Data Stewardship, and a Professor in the Computer Science (CS) Department at the University of Pittsburgh. He also serves as Special Assistant to the Provost for Data Science. Previously, he served as the Associate Dean for Strategic Initiatives in SCI and led faculty recruitment and development in this role. Childers has also served as the Co-director of the Graduate Computer Engineering program and the Director of Graduate Studies for Computer Science. He graduated from the University of Virginia with a PhD (CS, 2000) and from the College of William and Mary with a BS (CS, 1991). His most recent work focuses on technology and cultural changes to advance transparency, reuse, and reproducibility in computationally-driven science. Childers is a passionate advocate of increasing accountability in computer systems research for more reproducible and open experimentation. His research focuses on the intersection of the software-hardware boundary for improved energy, performance, and reliability in computer systems design, with an emphasis on embedded systems. He has developed techniques at both the software layer (dynamic binary translation, compiler optimization, debugging and software testing) and the hardware layer (GPU resource management, asynchronous custom processors, speed scaling, reliable cache design, and storage class memory). Childers participates in numerous international and national activities, including past steering committee chair of the ACM SIGPLAN and SIGBED Conference on Languages, Compilers, and Tools for Embedded Systems (2012-2015), program chair for LCTES (2010) and PPPJ (2014), member of the Editorial Advisory Board for the Computer Languages, Systems and Structures Journal, member of the organizing commmittee for the Workshop on Modeling and Simulation of Systems and Applications, member of the steering committee for the Managed Programming Languages and Runtimes conference, and Associate Editor for IEEE Transactions on Computers. He participates in ACM task forces on issues about scientific reproducibility in computer science research.

Most Cited Publications
  1. Zhu, D., Melhem, R., & Childers, B. R. (2003). Scheduling with dynamic voltage/speed adjustment using slack reclamation in multiprocessor real-time systems. IEEE transactions on parallel and distributed systems14(7), 686-700.
  2. Scott, K., Kumar, N., Velusamy, S., Childers, B., Davidson, J. W., & Soffa, M. L. (2003, March). Retargetable and reconfigurable software dynamic translation. In International Symposium on Code Generation and Optimization, 2003. CGO 2003. (pp. 36-47). IEEE.
  3. Ferreira, A. P., Zhou, M., Bock, S., Childers, B., Melhem, R., & Mossé, D. (2010, March). Increasing PCM main memory lifetime. In Proceedings of the conference on design, automation and test in Europe (pp. 914-919). European Design and Automation Association.
  4. Jiang, L., Zhao, B., Zhang, Y., Yang, J., & Childers, B. R. (2012, February). Improving write operations in MLC phase change memory. In IEEE International Symposium on High-Performance Comp Architecture (pp. 1-10). IEEE.
  5. Zhu, D., Melhem, R., & Childers, B. R. (2003). Scheduling with dynamic voltage/speed adjustment using slack reclamation in multiprocessor real-time systems. IEEE transactions on parallel and distributed systems14(7), 686-700.
Recent Publications
  1. Yu, Q., Childers, B., Huang, L., Qian, C., & Wang, Z. (2019, March). Hierarchical Page Eviction Policy for Unified Memory in GPUs. In 2019 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) (pp. 149-150). IEEE.
  2. Yu, Q., Childers, B., Huang, L., Qian, C., & Wang, Z. (2019). A quantitative evaluation of unified memory in GPUs. The Journal of Supercomputing, 1-28.
  3. Qian, C., Childers, B., Huang, L., Guo, H., & Wang, Z. (2018). CGAcc: A Compressed Sparse Row Representation-Based BFS Graph Traversal Accelerator on Hybrid Memory Cube. Electronics7(11), 307.
  4. Childers, B. R., & Chrysanthis, P. K. (2018, April). Artifact Evaluation: FAD or Real News?. In 2018 IEEE 34th International Conference on Data Engineering (ICDE) (pp. 1664-1665). IEEE.
  5. Wilkinson, D., Oliveira, L., Mossé, D., & Childers, B. (2018, June). Software Provenance: Track the Reality Not the Virtual Machine. In Proceedings of the First International Workshop on Practical Reproducible Evaluation of Computer Systems (p. 5). ACM.
Phone: 
Mechanical Engineering & Materials Science, University of Pittsburgh
PhD, Ohio State University, 2003
Summary:

The overarching goals of our research is to develop and use multiscale simulation tools to understand, predict, and design novel materials for applications in energy conversion and storage, surfaces and interfaces, spectroscopy, and nanoparticles. Our group has extensive expertise in different levels of theories in computational materials design that span a wide range of accuracy levels and length scales, including force-field, density-functional theory, quantum Monte Carlo and quantum chemistry methods.

Specific Research Directions:

  1. Solar Cells
  2. Novel two Dimensional Materials: Graphene and Beyond
  3. Innovative Materials for Electrocatalysis
  4. Metal Oxidation
  5. Surfaces and Interfaces
  6. Ferroelectric Materials
  7. Raman Spectroscopy
  8. Van der Waals interactions
Most Cited Publications
  1. "Adsorption of polyvinylpyrrolidone on Ag surfaces: insight into a structure-directing agent." WA Al-Saidi, Haijun Feng, Kristen A Fichthorn. Nano letters.
  2. "Oxygen reduction electrocatalysis using N-doped graphene quantum-dots." Wissam A Saidi. The Journal of Physical Chemistry Letters.
  3. "CO2 adsorption on TiO2(101) anatase: A dispersion-corrected density functional theory study." Dan C Sorescu, Wissam A Al-Saidi, Kenneth D Jordan. The Journal of chemical physics.
  4. "An assessment of the vdW-TS method for extended systems." WA Al-Saidi, Vamsee K Voora, Kenneth D Jordan. Journal of chemical theory and computation.
  5. "Temperature dependent energy levels of methylammonium lead iodide perovskite." Benjamin J Foley, Daniel L Marlowe, Keye Sun, Wissam A Saidi, Louis Scudiero, Mool C Gupta, Joshua J Choi. Applied Physics Letters.
Recent Publications
  1. "Developing a Fingerprinting and Machine Learning Framework Linking Structural Disorder to Oxidation Behavior in Metal Grain Boundaries for CO2 Electrocatalysis." Matthew Curnan, Wissam A Saidi, Judith Yang, Jeong Woo Han. 2019 AIChE Annual Meeting.
  2. "Evaluating the Accuracy of Common γ-Al2O3 Structure Models by Selected Area Electron Diffraction from High-Quality Crystalline γ-Al2O3." Henry O Ayoola, Stephen D House, Cecile S Bonifacio, Kim Kisslinger, Wissam A Saidi, Judith C Yang. Acta Materialia.
  3. "Atomic Scale Dynamic Process of Cu Oxidation Revealed By Correlated in situ Environmental TEM and DFT Simulations." Meng Li, Matthew T Curnan, Michael A Cresh-Sill, Stephen D House, Wissam A Saidi, Judith C Yang. Microscopy and Microanalysis.
  4. "Determination of the Crystal Structure of Gamma-Alumina by Electron Diffraction and Electron Energy-Loss Spectroscopy." Henry O Ayoola, Cecile S Bonifacio, Matthew T Curnan, Stephen D House, Meng Li, Joshua Kas, John J Rehr, Eric A Stach, Wissam A Saidi, Judith C Yang. Microscopy and Microanalysis.
  5. "In situ Atomic Scale Observation of Cu2O Reduction Under Methanol." Meng Li, Hao Chi, Matthew T Curnan, Michael A Cresh-Sill, Stephen D House, Wissam A Saidi, Götz Veser, Judith C Yang. Microscopy and Microanalysis.
Civil and Environmental Engineering, Carnegie Mellon University
PhD, California Institute of Technology, 2007
Summary:

Our research interest is focused on developing analytical and computational multiscale techniques, and applying these techniques to engineering and biomedicine. Some current application topics include (i) response of charged defects to electric fields in solid oxides and ferroelectrics for energy applications; (ii) mechanics of drug transport across biological membranes; (iii) electron transport in deformed biomolecules under stress; (iv) response of nanostructured materials under dynamic loading for impact and blast protection; (v) composite functional materials for high-temperature sensors and actuators for hypersonic aircraft; (vi) quantum mechanical calculation of electromechanical properties of nanomaterials (graphene, nanotubes, chalcogenides)

Most Cited Publications
  1. "Challenges and Opportunities for Multi-functional Oxide Thin films for Voltage Tunable RF / Microwave Components," Guru Subramanyam, Melanie W. Cole, Nian X. Sun, Thottam S. Kalkur, Nick M. Sbrockey, Gary S. Tompa, Xiaomei Guo, Chonglin Chen, S. Pamir Alpay, George A. Rossetti Jr., Kaushik Dayal, Long-Qing Chen, Darrell Schlom, Journal of Applied Physics 114, 191301 (2013)
  2. "Kinetics of phase transformations in the peridynamic formulation of continuum mechanics," Kaushik Dayal, Kaushik Bhattacharya, Journal of the Mechanics and Physics of Solids 54,1811 (2006)
  3. "A real-space non-local phase-field model of ferroelectric domain patterns in complex geometries," Kaushik Dayal, Kaushik Bhattacharya, Acta materialia, 55, 1907 (2007)
  4. "Graded ferroelectric capacitors with robust temperature characteristics," Mohamed Y El-Naggar, Kaushik Dayal, David G Goodwin, Kaushik Bhattacharya, Journal of applied physics 100, 114115 (2006)
  5. "Nonequilibrium molecular dynamics for bulk materials and nanostructures," Kaushik Dayal, Richard D James, Journal of the Mechanics and Physics of Solids 58, 145 (2010)
Recent Publications
  1. "A 3D phase field dislocation dynamics model for body-centered cubic crystals," Peng, Xiaoyao, Nithin Mathew, Irene J. Beyerlein, Kaushik Dayal, and Abigail Hunter. Computational Materials Science 171 (2020): 109217.
  2. "Effects of Polydispersity on Structuring and Rheology in Flowing Suspensions,"  E Rosenbaum, M Massoudi, and K DayalJournal of Applied Mechanics 86.8 (2019)
  3. "Designing soft pyroelectric and electrocaloric materials using electrets" F Darbaniyan, K Dayal, L Liu, P Sharma Soft matter 15 (2), 262-277
  4. "Disclinations without gradients: A nonlocal model for topological defects in liquid crystals." de Macedo, R.B., Pourmatin, H., Breitzman, T., Dayal, K.     Extreme Mechanics Letters 23, pp. 29-40. (2018).
  5. "Bond-level deformation gradients and energy averaging in peridynamics," Timothy Breitzmana, Kaushik Dayal, J. Mech. Phys. Solids 110,192, (2018).

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