Work with thought leaders and academic experts in Theoretical Computer Science
Companies can greatly benefit from collaborating with experts in Theoretical Computer Science. These researchers have a deep understanding of algorithms, complexity theory, and cryptography, which can be applied to various industries. They can help companies optimize their processes, develop efficient algorithms, enhance data security, and solve complex computational problems. Additionally, their expertise can drive innovation, improve decision-making, and provide valuable insights for developing cutting-edge technologies. By working with Theoretical Computer Science researchers, companies can gain a competitive edge, improve efficiency, and achieve breakthrough solutions.
Researchers on NotedSource with backgrounds in Theoretical Computer Science include Edoardo Airoldi, Dmitry Batenkov, Ph.D., Athul Prasad, Anit Kumar Sahu, Shubham Gupta, Denys Dutykh, Mark Ryan, Krzysztof Wolk, Vivek Singh, Baidurya Bhattacharya, Oguzhan Kulekci, Osaye Fadekemi, PhD, and Hector Klie.
Edoardo Airoldi
Professor of Statistics & Data Science Temple University & PI, Harvard University
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106 total publications
Scalable estimation strategies based on stochastic approximations: classical results and new insights
Statistics and Computing / Jun 11, 2015
Toulis, P., & Airoldi, E. M. (2015). Scalable estimation strategies based on stochastic approximations: classical results and new insights. Statistics and Computing, 25(4), 781–795. https://doi.org/10.1007/s11222-015-9560-y
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Dmitry Batenkov, Ph.D.
A highly experienced applied mathematician working in academia (faculty) and industry (consulting), with 15+ years of research and teaching expertise in inverse problems, signal processing, and data science.
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50 total publications
Moment inversion problem for piecewise D -finite functions
Inverse Problems / Sep 16, 2009
Batenkov, D. (2009). Moment inversion problem for piecewise D -finite functions. Inverse Problems, 25(10), 105001. https://doi.org/10.1088/0266-5611/25/10/105001
Accurate solution of near-colliding Prony systems via decimation and homotopy continuation
Theoretical Computer Science / Jun 01, 2017
Batenkov, D. (2017). Accurate solution of near-colliding Prony systems via decimation and homotopy continuation. Theoretical Computer Science, 681, 27–40. https://doi.org/10.1016/j.tcs.2017.03.026
Stable soft extrapolation of entire functions
Inverse Problems / Dec 07, 2018
Batenkov, D., Demanet, L., & Mhaskar, H. N. (2018). Stable soft extrapolation of entire functions. Inverse Problems, 35(1), 015011. https://doi.org/10.1088/1361-6420/aaedde
Open BEAGLE: a generic framework for evolutionary computations
Genetic Programming and Evolvable Machines / Mar 29, 2011
Batenkov, D. (2011). Open BEAGLE: a generic framework for evolutionary computations. Genetic Programming and Evolvable Machines, 12(3), 329–331. https://doi.org/10.1007/s10710-011-9135-4
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Athul Prasad
5G / 6G Technology and Ventures at Samsung; D.Sc. (Tech), MBA
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75 total publications
Quasi-universal k-regular sequences
Theoretical Computer Science / Nov 01, 2021
Honkala, J. (2021). Quasi-universal k-regular sequences. Theoretical Computer Science, 891, 84–89. https://doi.org/10.1016/j.tcs.2021.08.028
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Anit Kumar Sahu
PhD from CMU working in ML/AI
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59 total publications
Nonlinear Gradient Mappings and Stochastic Optimization: A General Framework with Applications to Heavy-Tail Noise
SIAM Journal on Optimization / May 16, 2023
Jakovetić, D., Bajović, D., Sahu, A. K., Kar, S., Milos̆ević, N., & Stamenković, D. (2023). Nonlinear Gradient Mappings and Stochastic Optimization: A General Framework with Applications to Heavy-Tail Noise. SIAM Journal on Optimization, 33(2), 394–423. https://doi.org/10.1137/21m145896x
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Shubham Gupta
With over seven years of extensive experience in 3GPP standards, 5G core networks, satellite communication, post-quantum cryptography, and cybersecurity, I possess profound expertise in the telecommunications and IoT sectors.
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32 total publications
ICT – a surviving tool for economy in the phase of social distancing: a systematic literature review
Kybernetes / Feb 25, 2022
Gupta, S., Gupta, S., Kataria, S., & Gupta, S. (2022). ICT – a surviving tool for economy in the phase of social distancing: a systematic literature review. Kybernetes, 52(9), 3136–3160. https://doi.org/10.1108/k-05-2021-0374
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Denys Dutykh
Professional Applied Mathematician, Modeller, and Advisor
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186 total publications
On the Galerkin/Finite-Element Method for the Serre Equations
Journal of Scientific Computing / Feb 05, 2014
Mitsotakis, D., Ilan, B., & Dutykh, D. (2014). On the Galerkin/Finite-Element Method for the Serre Equations. Journal of Scientific Computing, 61(1), 166–195. https://doi.org/10.1007/s10915-014-9823-3
Derivation of dissipative Boussinesq equations using the Dirichlet-to-Neumann operator approach
Mathematics and Computers in Simulation / Sep 01, 2016
Dutykh, D., & Goubet, O. (2016). Derivation of dissipative Boussinesq equations using the Dirichlet-to-Neumann operator approach. Mathematics and Computers in Simulation, 127, 80–93. https://doi.org/10.1016/j.matcom.2013.12.008
Tsunami generation by dynamic displacement of sea bed due to dip-slip faulting
Mathematics and Computers in Simulation / Dec 01, 2009
Dutykh, D., & Dias, F. (2009). Tsunami generation by dynamic displacement of sea bed due to dip-slip faulting. Mathematics and Computers in Simulation, 80(4), 837–848. https://doi.org/10.1016/j.matcom.2009.08.036
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Mark Ryan
Digital Ethics Researcher at Wageningen Economic Research
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39 total publications
In defence of digital contact-tracing: human rights, South Korea and Covid-19
International Journal of Pervasive Computing and Communications / Aug 06, 2020
Ryan, M. (2020). In defence of digital contact-tracing: human rights, South Korea and Covid-19. International Journal of Pervasive Computing and Communications, 16(4), 383–407. https://doi.org/10.1108/ijpcc-07-2020-0081
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Krzysztof Wolk
Professor
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59 total publications
Advanced social media sentiment analysis for short‐term cryptocurrency price prediction
Expert Systems / Nov 21, 2019
Wołk, K. (2019). Advanced social media sentiment analysis for short‐term cryptocurrency price prediction. Expert Systems, 37(2). Portico. https://doi.org/10.1111/exsy.12493
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Vivek Singh
Rutgers Professor, MIT alum, CS PhD, AI expert
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95 total publications
Social Bridges in Urban Purchase Behavior
ACM Transactions on Intelligent Systems and Technology / Dec 11, 2017
Dong, X., Suhara, Y., Bozkaya, B., Singh, V. K., Lepri, B., & Pentland, A. ‘Sandy.’ (2017). Social Bridges in Urban Purchase Behavior. ACM Transactions on Intelligent Systems and Technology, 9(3), 1–29. https://doi.org/10.1145/3149409
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Baidurya Bhattacharya
Computational mechanics, probabilistic risk analysis, statistical inference, Monte Carlo simulations
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91 total publications
Performance metrics in a hybrid MPI–OpenMP based molecular dynamics simulation with short-range interactions
Journal of Parallel and Distributed Computing / Mar 01, 2014
Pal, A., Agarwala, A., Raha, S., & Bhattacharya, B. (2014). Performance metrics in a hybrid MPI–OpenMP based molecular dynamics simulation with short-range interactions. Journal of Parallel and Distributed Computing, 74(3), 2203–2214. https://doi.org/10.1016/j.jpdc.2013.12.008
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Oguzhan Kulekci
Algorithm Engineer, Security/Privacy Researcher, Combinatorial Problem Solver
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61 total publications
I/O-efficient data structures for non-overlapping indexing
Theoretical Computer Science / Feb 01, 2021
Hooshmand, S., Abedin, P., Oğuzhan Külekci, M., & Thankachan, S. V. (2021). I/O-efficient data structures for non-overlapping indexing. Theoretical Computer Science, 857, 1–7. https://doi.org/10.1016/j.tcs.2020.12.006
A Survey on Shortest Unique Substring Queries
Algorithms / Sep 06, 2020
Abedin, P., Külekci, M., & Thankachan, S. (2020). A Survey on Shortest Unique Substring Queries. Algorithms, 13(9), 224. https://doi.org/10.3390/a13090224
Applications of Non-Uniquely Decodable Codes to Privacy-Preserving High-Entropy Data Representation
Algorithms / Apr 17, 2019
Külekci, M. O., & Öztürk, Y. (2019). Applications of Non-Uniquely Decodable Codes to Privacy-Preserving High-Entropy Data Representation. Algorithms, 12(4), 78. https://doi.org/10.3390/a12040078
Range selection and predecessor queries in data aware space and time
Journal of Discrete Algorithms / Mar 01, 2017
Külekci, M. O., & Thankachan, S. V. (2017). Range selection and predecessor queries in data aware space and time. Journal of Discrete Algorithms, 43, 18–25. https://doi.org/10.1016/j.jda.2017.01.002
A simple yet time-optimal and linear-space algorithm for shortest unique substring queries
Theoretical Computer Science / Jan 01, 2015
İleri, A. M., Külekci, M. O., & Xu, B. (2015). A simple yet time-optimal and linear-space algorithm for shortest unique substring queries. Theoretical Computer Science, 562, 621–633. https://doi.org/10.1016/j.tcs.2014.11.004
Fast and flexible packed string matching
Journal of Discrete Algorithms / Sep 01, 2014
Faro, S., & Külekci, M. O. (2014). Fast and flexible packed string matching. Journal of Discrete Algorithms, 28, 61–72. https://doi.org/10.1016/j.jda.2014.07.003
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Osaye Fadekemi, PhD
Assistant Professor of Mathematics at Alabama State University with expertise in Graph Theory and Network Modeling
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6 total publications
Average eccentricity,k -packing andk -domination in graphs
Discrete Mathematics / May 01, 2019
Dankelmann, P., & Osaye, F. J. (2019). Average eccentricity,<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll" id="d1e86" altimg="si36.gif"><mml:mi>k</mml:mi></mml:math>-packing and<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll" id="d1e91" altimg="si36.gif"><mml:mi>k</mml:mi></mml:math>-domination in graphs. Discrete Mathematics, 342(5), 1261–1274. https://doi.org/10.1016/j.disc.2019.01.004
The average eccentricity of a graph with prescribed girth
Discrete Mathematics / Dec 01, 2022
Osaye, F. J. (2022). The average eccentricity of a graph with prescribed girth. Discrete Mathematics, 345(12), 113066. https://doi.org/10.1016/j.disc.2022.113066
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Hector Klie
CEO @ DeepCast.ai | AI-driven Industrial Solutions, Technical Innovation
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81 total publications
Towards a rigorously justified algebraic preconditioner for high-contrast diffusion problems
Computing and Visualization in Science / Mar 27, 2008
Aksoylu, B., Graham, I. G., Klie, H., & Scheichl, R. (2008). Towards a rigorously justified algebraic preconditioner for high-contrast diffusion problems. Computing and Visualization in Science, 11(4–6), 319–331. https://doi.org/10.1007/s00791-008-0105-1
A neural stochastic multiscale optimization framework for sensor-based parameter estimation
Integrated Computer-Aided Engineering / May 13, 2007
Banchs, R. E., Klie, H., Rodriguez, A., Thomas, S. G., & Wheeler, M. F. (2007). A neural stochastic multiscale optimization framework for sensor-based parameter estimation. Integrated Computer-Aided Engineering, 14(3), 213–223. https://doi.org/10.3233/ica-2007-14302
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Example Theoretical Computer Science projects
How can companies collaborate more effectively with researchers, experts, and thought leaders to make progress on Theoretical Computer Science?
Optimizing Supply Chain Management
A Theoretical Computer Science expert can develop algorithms to optimize supply chain management, reducing costs and improving efficiency. By analyzing complex data and considering various factors such as demand, inventory, and transportation, they can create models that minimize delays, optimize routes, and streamline operations.
Enhancing Data Security
With their knowledge of cryptography and data encryption, Theoretical Computer Science researchers can help companies enhance their data security measures. They can develop robust encryption algorithms, design secure communication protocols, and identify vulnerabilities in existing systems to prevent data breaches and unauthorized access.
Machine Learning and AI
Theoretical Computer Science experts can contribute to the development of machine learning and AI algorithms. They can design efficient algorithms for training models, improve the accuracy of predictions, and optimize computational resources. Their expertise can help companies leverage the power of AI to automate processes, make data-driven decisions, and improve customer experiences.
Optimizing Financial Trading Strategies
By applying algorithms and mathematical models, Theoretical Computer Science researchers can optimize financial trading strategies. They can analyze market data, identify patterns, and develop algorithms that maximize returns and minimize risks. Their expertise can help companies make informed investment decisions and achieve better financial outcomes.
Solving Complex Computational Problems
Theoretical Computer Science experts excel in solving complex computational problems. They can develop algorithms and mathematical models to tackle challenges in various domains, such as optimization, scheduling, and network design. By collaborating with them, companies can find innovative solutions to their most challenging problems.