Dr. D.Sc. Abebe Geletu is the AIMS Rwanda, German Research Chair based in Kigali, Rwanda. His current research focus includes systems optimization for sustainable resources utilization in Africa, multidisciplinary research and development for addressing engineering problems, AI and Data-driven approaches for complex problems.

Prior to joining AIMS in September 2021, he was an academic staff and a senior research scientist in applied mathematics, numerical methods of optimization, stochastic optimization, control engineering, data-driven optimization, machine learning, image processing and computer vision, etc. with applications in engineering sciences at the Technology University of Ilmenau, Germany.

Education

• B.Sc. Mathematics (Addis Ababa University, Ethiopia)
• M.Sc. Applied Mathematics (Addis Ababa University, Ethiopia)
• Ph.D.  Numerical Optimization (Technology University Ilmenau, Faculty of Mathematics and Natural Sciences, Germany)
• D.Sc. (Habilitus):  Systems Optimization (Technology University Ilmenau, Faculty of Computer Science and Automation, Germany)

Work experience:

• Lecturer: Haramaya University, Ethiopia – 9 years
• Research and Academic Staff: Technology University Ilmenau, Germany (Faculty of Mathematics) – 9years
• Senior Research Scientist: Technology University Ilmenau, Germany (Faculty of Computer Science and Automation) – 13years
• Visiting Professor: Addis Ababa University, Haramaya University, Hawassa University (Ethiopia), Technology University of Ilmenau, Germany, since 2013.

Current Research Interest:

• Mathematical optimization, intelligent and predictive control applications
• Big-data analytics, data-driven methods, and machine learning applications (in medicine, agriculture, sustainability systems, finance, communication, etc.)
• Optimization, AI and advanced technology implementation for African sustainability systems (smart water network systems, microgrid-based renewable energy generation, and distribution)
• Optimization and Deep Learning methods for image processing, computer vision, and applications
• Systems development and modernization of African agrifood supply-chain

Current Ph.D., Postdoc and M.Sc. Students

1. Addis Ababa University, Ethiopia
2. Mr. Muhammad Sani: Stochastic optimization of elliptic PDE systems under chance-constrained state variables, Addis Ababa University, Department of Mathematics (in progress).
3. Mr. Agegnehu Tesfaye Janka: Chance-constrained nonlinear mixed-integer optimization and applications, Addis Ababa University, Department of Mathematics (in progress).

• AIMS Rwanda (Ph.D. and Postdoc)
• Miss. Marcy Audrey Demafo Nangmo. Real-time model predictive control of microgrid based sustainable energy generation and distribution with optimal energy storage management, stable operation, and reliable demand coverage. (PhD in progress, since 2022)
• Mr. Michel Murwanashyaka: Intelligent predictive control and smart monitoring for water distribution network systems (PhD in progress, since 2022)
• Mr. Mugenga Ineza Remy: Chance constrained distributed model predictive control for stable, reliable, and coordinated operational management of multiple microgrids. (PhD in progress, since 2022)
• Dr. Peguy Kameni Nteuste:  Systems Optimization for Sustainable Resources Utilization. (Postdoc in progress, since 2022)

• AIMS Rwanda (current M.Sc.)Mr. Angelo Junior KITIO TSAGUE: Tensor decomposition techniques for machine learning methods and applications in hyperspectral image analysis. (in progress)Mr. Rabiu Muhammad Tsoho: Deep learning methods for real-time traffic speed estimation, vehicle detection, and identification. (in progress)Mr. Luel Hagos Berhe. Deep learning methods for text- to-speech transcription with application to the Ethiopian Geez Language. (in progress)Mr. Ange-Clement Akazan: Deep learning methods for weather prediction. (in progress)Miss Barbrah Phoebe: Using deep learning methods on facial image data to detect autistic patterns. (in progress)

• Past and current doctoral supervisions at TU Ilmenau, Germany (with Prof. Pu Li)Mrs. Ines Mynttinen: Optimierung autonom schaltender dynamischer Hybridsysteme (engl.: Optimization of autonomously switching dynamic hybrid systems) (closed in 2013)Mr. Michael Klöppel: Efficient numerical solution of chance constrained optimization problems with engineering applications (closed in 2014).Mr. Evgeny Lazutkin: Efficient solution of nonlinear optimal control problems and applications to power plants (closed in 2019).Mr. Xujiang Huang: Optimal operations of multi-agent systems for resource constrained problems (in progress).Mr. Kibru Teka: Optimization of parabolic PDE systems under chance constrained state variables (in progress).Mr. Ruslan Voropai: Model Predictive Control of parabolic PDE Systems with NonGaussian Distributed Uncertain Variables under Chance Constraints (in progress).

(Please, find more details in my full cv)

List of Scientific Research Publications

1. Preprints and work in progress 2022
2. Designing reliable machine learning models using chance-constrained optimization methods (with Mr. Ruslan Voropai and Prof. Armin Hoffmann, TU Ilmenau)
3. Dynamics and intelligent control for a human single-leg prosthesis (with P.K. Nteutse, AIMS Rwanda)
4. Chance constrained model predictive control of parabolic PDE systems (with Mr. Ruslan
   Voropai and Prof. Pu Li, TU Ilmenau)
5. Chance constrained parabolic PDE systems with random data (with Mr. Kibru Teka and
   Prof. Pu Li, TU Ilmenau)
6. Analytic approximation and differentiability of joint chance constraints – part 2: weakened (LICQ) and subdifferentiability (with Prof. Armin Hoffmann, TU Ilmenau)

• Publications in peer-reviewed international journals
• A. Geletu, A. Hoffmann, P. Schmidt, P. Li: Chance constrained optimization of elliptic
  PDE systems with smoothing approximations. ESAIM: COCV, 26(2020)70. Published
  online: 30 September 2020. DOI:10.1051/cocv/2019077).
• E. Mohagheghi, J.G. Gasso, A. Geletu, P.  Li. Chance Constrained Optimization for Energy Management in Electric Vehicles. Trends Comput. Sci. Inf. Technol., 5(1): 044-045, 2020. DOI: https://dx.doi.org/10.17352/tcsit.000019.
• A. Geletu, A. Hoffmann, P. Li: Chance constrained problems in Banach spaces and
  applications. (2020, under revision)
• A. Geletu, A. Hoffmann, P. Li: Analytic approximation and differentiability of joint chance constraints. Optimization, 68(10), 1985–2023, 2019. DOI: 10.1080/02331934.2019.1643344.
• A. Geletu, P. Schmidt, P. Li: Stochastische Optimierung parabolische PDE-Systeme unter Wahrscheinlichkeitsrestriktionen am Beispiel der Temperaturreglung eins Stabs.
  (at-automatisierungstechnik, 2018, 66(11): 975–985).
• A. Geletu , A. Hoffmann, M. Klöppel, P. Li: An inner-outer approximation approach to
  chance constrained optimization. SIAM Journal on Optimization, 27(3), 1834 – 1857, 2017.
• A. Geletu, M. Klöppel, A. Hoffmann, P. Li: A tractable approximation of nonconvex
  chance constrained optimization with non-Gaussian uncertainties. Journal of Engineering
  Optimization, 47(4), pp. 495 – 520, 2015.
• E. Lazutkin, A. Geletu, P. Li: An approach to determining the number of time intervals
  for solving dynamic optimization problems. Industrial Engineering Chemical Research, 57, 4340–4350, 2018.
• E. Lazutkin, A. Geletu, S. Hopfgarten, P. Li: An analytical Hessian and parallel computing approach for efficient dynamic optimization based on control variable correlation analysis. Industrial Engineering Chemical Research, 54(48), 12086–12095, 2015.
• A. Geletu, P. Li: Recent developments in computational approaches to optimization under uncertainty and application in process systems engineering, ChemBioEng Reviews, 1(4), 170–190, 2014.
• A. Geletu, M. Klöppel, H. Zhang, P. Li: Advances and applications of chance-constrained approaches to systems optimization under uncertainty. International Journal of Systems Science, 44, 1209–1232, 2013.
• A. Geletu, A. Hoffmann, M. Klppel, P. Li: Monotony analysis and sparse-grid integration
  for nonlinear chance constrained process optimization. Journal of Engineering Optimization, 43, 1019-1041, 2011.
• M. Klöppel, A. Geletu, A. Hoffmann, P. Li: Using sparse-grid methods to improve computation efficiency in solving dynamic nonlinear chance-constrained optimization problems. Industrial Engineering Chemical Research, 50, 5693-5704, 2011.
• A. Geletu, A. Hoffmann: On robustness of set-valued maps and marginal value functions.
  Discussiones Mathematicae – Differential Inclusions, Control and Optimization, 25, 59-108, 2005.
• A. Geletu, A. Hoffmann: A Conceptual Method for Solving Generalized Semi-infinite
  Programming Problems via Global Optimization by exact discontinuous penalization,
  European Journal of Operations Research, 157(1), 3-15, 2004

• Contributions to Conferences and Proceedings
  
  
• R. Voropai, A. Geletu, P. Li: Chance constrained model predictive control of parabolic PDE systems with random parameters. A contribution to the 31st European Conference on Operations Research – EURO 2021, Athenes, Greek, 11 – 14 July, 2021.
• K. Teka, A. Geletu, P. Li: A Computation Approach to Chance Constrained Optimization of Boundary-Value Parabolic Partial Differential Equation systems. IFAC-PapersOnLine, Volume 53, Issue 2, 2020, Pages 2435-2440.
• A. Geletu, A. Hoffmann, P. Schmidt, P. Li.: Smoothing methods to chance constrained optimization of elliptic PDE systems. (23rd International Symposium on Mathematical Programming (ISMP2018), Bordeaux, France, July 1 – 6, 2018
• A. Geletu, A. Hoffmann and Pu Li: Differentiability of joint chance constraints under weakened LICQ. (23rd International Symposium on Mathematical Programming (ISMP2018), Bordeaux, France, July 1 – 6, 2018)
• E. Mohagheghi, A. Geletu, N. Bremser, M. Alramlawi, A. Gabash, P. Li: Chance constrained optimal power flow using the inner-outer approximation approach. 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), Palermo, Italy, June 12 – 15, 2018.
• J. Chen, M. Zeidan, A. Ostfeld, A. Geletu1, P. Li: Analysis of relations between pressure and water age in water distribution systems. 1st International WDSA/CCWI 2018 Joint Conference, Kingston, Ontario, Canada – July 23-25, 2018.
• A. Geletu, P. Schmidt, Hoffmann, P. Li: A Smoothing Approach to Chance Constrained Optimization of Parabolic PDE Systems under Uncertainty: A Case-Study. 18th French- German – Italian Conference on Optimization, September 25 – 28, 2017, Paderborn, Germany.
• A. Hoffmann, A. Geletu, P. Li: Analytic approximation and differentiability of joint chance constrain. GPCO 2017- 7th German-Polish Conference on Optimization 27.08.2017 – 01.09.2017, Bedlewo, Poland.
• A. Geletu, A. Hoffmann, P. Li: Chance constrained optimization in Banach Spaces. 14^th EUROPT Workshop on Advances in Continuous Optimization, Warsaw (Poland), July 1-2, 2016.
• M.-L. Correa Cordova, A. Geletu, P. Li: Optimal Scheduling of Vaccination Campaigns Using a Direct Dynamic Optimization Method, IFAC-PapersOnLine, 49–26 (2016) 207–212.
• A. Geletu, A. Hoffmann, M. Klöppel, P. Li: Asymptotic analytic approximation for nonconvex chance constrained optimization. 22nd International Symposium on Mathematical Programming, ISMP2015, Pittsburgh, Pennsylvania, USA, July 12-17, 2015.
• X. Huang, A. Geletu, P. Li: A soft-constrained optimization approach for model predictive control of multi-agent systems, Proceedings of the 16th IFAC Workshop on Control Applications of Optimization, Oct. 6-9, 2015, Garmisch-Partenkirchen, pp. 16-21.
• E. Lazutkin, S. Hopfgarten, A. Geletu, P. Li, A toolchain for solving dynamic optimization problems using symbolic and parallel computing, Proceedings of the 11th International Modelica Conference, Versailles, France, Sept. 21-23, 2015, pp. 311-320.
• E. Lazutkin, A. Geletu, S. Hopfgarten, P. Li: Sensitivity computation based on CasADi for dynamical optimization, 16th European Workshop on Automatic Differentiation, 8-9 December 2014, Jena, Germany.
• A. Geletu, P. Li: Coupling analytic approximation with polynomial chaos collocation to tackle non-convex chance constraints in control engineering applications, EngOpt 2014, Lisbon, Portugal, 8-11 Sept, 2014.
• E. Lazutkin, A. Geletu, S. Hopfgarten, P. Li: Modified multiple shooting combined with collocation method in JModelica.org with symbolic calculations, Proceedings of the 10^th International Modelica Conference, DOI 10.3384/ECP14096999, 10 – 12 March, 2014, Lund, Sweden, pp. 999 – 1006.
• M. Klöppel, A. Geletu, A. Hoffmann, P. Li, J. Wensch: Analytical approximations for the solution of chance constrained optimization problems. GAMM – Proc. Appl. Math. Mech. 14, 779 – 780, 2014.
• M. Klöppel, A. Gabash, A. Geletu, P. Li: Chance constrained optimal power flow with non-gaussian distributed uncertain wind power generation, 12th International Conference on Environment and Electrical Engineering, EEEIC 2013, May 2013, Wroclaw, Poland, pp. 265-270.
• M. Klöppel, A. Hoffmann, A. Geletu, P. Li, Recent advances in chance-constrained
  optimization -an overview, GPCO 5, November 9 – 13 2011, Dobzcyce, Poland.
• M. Klöppel, A. Geletu, A. Hoffmann, P. Li: Optimierung von Energietransportsystemen unter Unsicherheiten, 126. GDN-Versammlung, September 17 -21, 2010, Dresden, Germany.
• A. Geletu, P. Li: Chance Constrained Process Optimization and Control under Uncertainty, 18th IFACWorld Congress, Pre-Conference Tutorial, August 27-28, 2011, Milano, Italy.
• M. Klöppel, A. Geletu, A. Hoffmann, P. Li: Evaluating integration approaches to robust process optimization and control using chance constrained programming. 2010 International Symposium on Computer-Aided Control System Design. Part of IEEE Multi-Conference on Systems and Control, Yokohama, Japan, September 8-10, 2010, pp. 1079–1084.
• A. Geletu, M. Klöppel, P. Li, A. Hoffmann: Efficient solution of chance-constrained nonlinear dynamic process optimization problems with non-Gaussian uncertainties, 2nd International Conference on Engineering Optimization, 6 – 9 September 2010, Lisboa, Portugal, published on CD, 10 pages.
• M. Klöppel, A. Geletu, A. Hoffmann, P. Li: Einsatz von Sparse Grid-Integrationstechniken in der wahrscheinlichkeitsrestringierten Optimierung, GOR Workshop: Vector Optimization of Complex Structures, March 17 – 19, 2010, Erlangen, Germany. 4 of 5.
• M. Klöppel, A. Geletu, P. Li, A. Hoffmann: A numerical approach to a chance constrained nonlinear dynamic optimization problem, 4th German Polish Conference on Optimization Methods and Applications, March 14 – 18, 2009, Moritzburg, Saxony.
• A. Geletu, M. Klöppel, P. Li, A. Hoffmann: A moving horizon approach to a chance
  constrained nonlinear dynamic optimization problem. Proceedings of 4th IFAC Workshop on Control Applications of Optimization, May 6 – 8, 2009, Agora, Finland, Vol.42, Issue 2, pp. 103–107.
• M. Klöppel, A. Geletu, A. Hoffmann, P. Li : Annual International Conference of the
  German Operations Research Society (GOR), Jointly Organized with the Austrian Society of Operations Research (ÖGOR) and the Swiss Society of Operations Research (SVOR), Karlsruhe, September 6–8, 2006.
• A. Geletu, A. Hoffmann: A conceptual method for solving generalized semi-infinite programming problems via global optimization by exact discontinuous penalization. International Workshop on Smooth and Nonsmooth Optimization – Theory and Applications, July 12 –13, 2001, University of Rotterdam, the Netherlands.

D. Preprints und Tutorials

1. A. Geletu: Solving optimization problems using the matlab optimization toolbox-a tutorial. (on Research Gate)
2. A. Geletu: GAMS-Modeling and Solving Optimization Problems (on Research Gate)
3. A. Geletu: Orthogonal Polynomials, Quadratures & Sparse-Grid Methods for Probability
   Integrals (on Research Gate)
4. A. Geletu: Introduction to Topological Spaces and Set-Valued Maps (130 pages)
   (Wikipedia: https://en.wikipedia.org/wiki/Multivalued_function)
5. A. Geletu, A. Hoffmann: Approximation of a convex compact set in the plane by an
   alternating sequence of arcs and lines – arc splines (Preprint No. M 3/00, April 2000,
   Institute of Mathematics, Technical University of Ilmenau).