### Quantum Computing for Finance: State-of-the-Art and Future Prospects

- Daniel Egger
- Claudio Gambella
- et al.

- 2020
- IEEE TQE

He/Him/His

Senior Research Manager - AI & Quantum, Master Inventor

IBM Research Europe - Ireland
Dublin, Ireland

Dr. Martin Mevissen is the Senior Research Manager for AI & Quantum at the IBM Research lab in Dublin, Ireland. He received a M.S. degree in mathematics from ETH Zurich in 2007, and a Ph.D. degree in mathematical and computing sciences from Tokyo Institute of Technology in 2010. After a post-doctoral fellowship with LAAS-CNRS in Toulouse, he joined IBM Research in 2011. Dr. Mevissen’s expertise lies in the areas of mathematical optimization, operations research, decision making under uncertainty and their applications. He has published in top venues and presented at numerous conferences & research institutions worldwide. Dr. Mevissen has been recipient of IBM Research Outstanding Technical Achievement Awards and an IBM Research Division Award. His current focus is in quantum algorithms for mathematical optimization problems, optimisation-based methods for quantum systems, AI Applications and scaling and automating AI. Dr. Mevissen is a Master Inventor and a member of the Mathematical Science Council at IBM Research.

**Educational Background**

- Dr.Sc., Mathematical and Comp. Sciences, Tokyo Institute of Technology, 2010.
- M.Sc., Mathematics, ETH Zurich, 2007.

**Publications**

- "Exploring quantum computing use cases for logistics", I. Othmani, M. LaDue, M. Mevissen, IBM Institute for Business value (2022).
- “Quantum computing for Finance: State oft he art and future prospects“, D. Egger, C. Gambella, J. Marecek, S. McFaddin, M. Mevissen, R. Raymond, A. Simonetto, S. Woerner, E. Yndurain, IEEE Transactions on Quantum Engineering, Vol. 1 (2020).
- “Projections onto the set of feasible inputs and the set of feasible solutions“, C. Gambella, J. Marecek, M. Mevissen, 57th Annual Allerton Conference on Communication, Control and Computing (2019), pp. 937-943
- “A Fine-Grained Variant oft he Hierarchy of Lasserre“, W. Ma, J. Marecek, M. Mevissen, 57th Annual Allerton Conference on Communication, Control and Computing (2019), pp. 580-586.
- “A Hidden Markov Model for Route and Destination Prediction“, Y. Lassoued, J. Monteil, Y. Gu, G. Russo, R. Shorten, M. Mevissen, 2017 IEEE 20th International Conference on Intelligent Transportation (2017).
- “Polynomial Optimization for Pressure Management: Global solutions for the valve setting problem”, B. Ghaddar, B. Eck, M. Claeys, M. Mevissen, European Journal of Operational Research 261 (2), pp. 450 – 459 (2017).
- “Special Issue on: Nonlinear and combinatorial methods for energy optimization“, C. D’Ambrosio, A. Frangioni, A. Lodi, M. Mevissen, EURO Journal on Computational Optimization 5, 1-2 (2017)
- “MINLP in transmission expansion planning“, J. Marecek, M. Mevissen, J. Villumsen, 2016 Power Systems Computation Conference (2016), pp. 1-8
- 'Optimal Power Flow as a Polynomial Optimization Problem', B. Ghaddar, J. Marecek, M. Mevissen, IEEE Transactions on Power Systems, Vol. 31 (2016), Issue 1, pp. 539-546.
- 'Quadratic Approximations for Pipe Friction', B. Eck, M. Mevissen, Journal for Hydroinformatics (2014), 17(3) (2015), pp. 462-472.
- 'Unified framework and toolkit for commerce optimization under uncertainty', B. Kawas, A. Koc, M. Laumanns, C. Lee, M. Mevissen, N. Taheri, S. van den Heever, R. Verago, IBM Journal of Research and Development, Vol. 58 (2014), Issue 5/6, pp. 1-13.
- 'Robustness to Time Discretization Errors in Water Networks', N. Taheri, F. Wirth, B. Eck, M. Mevissen, R. Shorten, Operations Research Proceedings (2014), pp. 581-588.
- “Mean squared error minimization for inverse moment problems“, D. Henrion, J.B. Lasserre, M. Mevissen, Applied Mathematics & Optimization 70 (2014), No. 1, pp.83-110.
- 'Data-driven distributionally robust polynomial optimization', M. Mevissen, E. Ragnoli, J.Y. Yu, Advances in Neural Information Processing Systems (2013), pp. 37-45.
- “Fast non-linear optimization for design problems on water networks“, B. Eck, M. Mevissen, World Environmental and Water Resources Congress 2013.
- “Valve Placement in Water Networks: Mixed Integer Non-Linear Optimization with Quadratic Pipe Friction“, B. Eck, M. Mevissen, September 2012, IBM Research Report (RC25307).
- “Moment and SDP relaxation techniques for smooth approximations of problems involving nonlinear differential equations“, M. Mevissen, J.B. Lasserre, D. Henrion, Proceedings of the 18th IFAC World Congress on Automatic Control (2011), pp. 10887-10892.
- “Exploiting Sparsity in Linear and Nonlinear Matrix Inequalities via Positive Semidefinite Matrix Completion“, S. Kim, M. Kojima, M. Mevissen, M. Yamashita, Mathematical Programming, 129 (2011), No. 1, pp. 33-68.
- “SDP Relaxations for Quadratic Optimization Problems Derived from Polynomial Optimization Problems“, M. Mevissen, M. Kojima, Asia-Pacific Journal of Operations Research, Asia-Pacific Journal of Operations Research, 27 (2010), No. 1, pp. 1-24.
- “Solutions of Polynomial Systems Derived from the Steady Cavity Flow Problem“, M. Mevissen, K. Yokoyama, N. Takayama, Proceedings of the 2009 International Symposium on Symbolic and Algebraic Computation, pp. 255-262.
- “Solving partial differential equations via sparse SDP relaxations“, M. Mevissen, M. Kojima, J. Nie, and N. Takayama, Pacific Journal of Optimization, 4 (2008), No. 2, pp. 213-241.

**Thesis**

- 'Sparse Semidefinite Programming Relaxations for Large Scale Polynomial optimization and their applications to differential equations', M. Mevissen, Doctoral Thesis, Tokyo Institute of Technology, 2010.

**Presentations**

- 'Decision-support Tools and Approaches for Optimisation under Uncertainty', GOR meeting, Bad Honnef, November 2015.
- 'Sparse Polynomial Optimization for Urban Distribution Networks', 27th EURO Conference 2015, Glasgow, July 2015.
- 'Management by Exception - Big data analytics for decision support in operations control', AGIFORS Airline Operations 2015, Abu Dhabi, May 2015.
- 'Sparse Polynomial Optimization for Urban Distribution Networks', MINO/COST Springschool on Optimization, Tilburg, March 2015.
- 'Sparse Polynomial Optimization for Urban Distribution Networks', CWM3O, Budapest, September 2014.
- 'Sparse Polynomial Optimization for Urban Distribution Networks', 20th IFORS, Barcelona, July 2014.
- 'Data-driven distributionally robust polynomial optimization', GeoLMI2013, Marseille, France, November 2013.
- 'Optimizing the Reliability of Power Distributions Systems', CWMINLP2013, Paris, October 2013.
- 'Optimizing the Operations of Power Distribution Systems', 26th EURO Conference 2013, Rome, Italy, July 2013.
- 'Advanced statistic modelling and operations research for optimizing electrical distribution grids', INFORMS Analytics 2013, San Antonio, April 2013.
- 'Distributionally Robust Optimization for Polynomial Optimization Problems', 21st International Symposium on Mathematical Programming, Berlin, Germany, August 2012.
- 'Nonlinear Optimization for Decision Problems in Water Distribution Networks under Uncertainty', 25th EURO Conference 2012, Vilnius, Lithuania, July 2012.
- 'Moment Methods and SDP Relaxations for Nonconvex Problems', HPOPT 2012, Delft, Netherlands, June 2012.
- 'Convex Optimization and MINLP Approaches for Decision Problems in Water Distribution Networks', INFORMS Optimization 2012, Coral Gables, February 2012.
- 'Reconstruction of density functions by L2 norm minimization and semidefinite programming', OR 2011, Zurich, Switzerland, August 2011.
- 'Moment and SDP relaxation methods for smooth approximations of nonlinear differential equations', SIAM Conference on Optimization, Darmstadt, Germany, May 2011.
- “Sparse SDP relaxation and moment methods for approximating solutions of nonlinear differential equations“, UC San Diego, October 2010.
- “Sparse SDP relaxations for Large Scale Polynomial Optimization and Applications to Differential Equations“, Tilburg University, Netherlands, June 2010.
- “Reduction of SDP relaxations for polynomial optimization problems“, 20th International Symposium on Mathematical Programming, Chicago, August 2009.
- “Solutions of Polynomial Systems Derived from the Steady Cavity Flow Problem“, International Symposium on Symbolic and Algebraic Computation, Seoul,July 2009.
- “Reduction techniques for SDP relaxations of polynomial optimization problems“, EURO Conference 2009, Bonn, July 2009.
- “Exploiting Sparsity in Nonlinear Matrix Inequalities and their SDP Relaxations“, 7th EUROPT Workshop Advances in Continuous Optimization, Remagen, July 2009.
- “Semidefinite programming techniques for solving nonlinear boundary value problems“, Conference on Optimization with interfaces and free boundaries, Regensburg, March 2009.
- “Nonconvex optimization methods for solving nonlinear differential equations“, Annual Meeting of the Mathematical Society of Japan, Tokyo, September 2008.
- “Semidefinite programming in polynomial and nonconvex quadratic optimization“, 4th Sino- Japanese Optimization Meeting, Tainan, Taiwan, August 2008.
- “Polynomial optimization techniques for second order PDEs and optimal control problems“, SIAM Conference on Optimization, Boston, May 2008.
- “Polynomial optimization techniques to solve nonlinear partial differential equations“, 2008 INFORMS Optimization conference, Atlanta, March 2008.
- “Solving partial differential equations via sparse SDP relaxations“, Workshop on Advances in Optimization, Tokyo Institute of Technology, April 2007.

### Quantum Computing for Finance: State-of-the-Art and Future Prospects

- Daniel Egger
- Claudio Gambella
- et al.

- 2020
- IEEE TQE

- 30 Oct 2023
- US
- 11803783

- 29 May 2023
- US
- 11665184

- 08 May 2023
- CN
- ZL201980010539.6

- 05 Apr 2023
- JP
- 7257727

- 06 Feb 2023
- US
- 11574377

- 06 Jun 2022
- US
- 11351913

- 26 Apr 2022
- GB
- 2581604

- 04 Apr 2022
- US
- 11293766

- 07 Mar 2022
- US
- 11267482

- 03 Mar 2022
- CN
- ZL201880064441.4

DE

Senior Research Scientist

SW

Manager, Quantum Computational Science