Konstantinos Spiliopoulos Department of Mathematics and Statistics Boston University Center for Computing & Data Sciences 665 Commonwealth Ave, Boston, MA 02215 Office: CCDS 438 Tel: +1-617-353-5209 e-mail: kspiliop_at_math.bu.edu to send me an email replace _at_ by @.

Welcome! I am a Professor and the Director of Statistics at the Department of Mathematics and Statistics, Boston University. I am affiliated with the Center for Information and Systems Engineering, Boston University and with the Hariri Institute for Computing and Computational Sciences & Engineering at Boston University.

Previously, I was a Prager assistant professor at the Division of Applied Mathematics, Brown University during 2009-2012. I completed my PhD at the Department of Mathematics, University of Maryland at College Park in 2009 advised by Professor Mark Freidlin. My undergraduate studies were in Applied Mathematics and Physics at the National Technical University of Athens in Greece. (NTUA).

Research interests:

• Mathematical and computational methods for machine learning algorithms
• Stochastic optimal control and optimization
• Stochastic online algorithms and deep learning for partial differential equations
• Monte Carlo methods and development of provably-efficient simulation methods
• Interacting particle systems, agent based modeling and related applications to biological systems, opinion and social dynamics
• Asymptotic analysis for stochastic processes and stochastic partial differential equations (SPDE's) such as coarse-graining, multiple scale problems and large deviations
• Metastability analysis of dynamical systems
• Financial mathematics, Systemic risk and risk managenemt, large portfolio asymptotics, stochastic volatility models and large deviations
• Network modeling and statistical inference for stochastic processes

• Curriculum Vitae (Last updated: May 2024), Arxiv webpage, Google Scholar, GitHub webpage, Linkedin

Choosing learning rates while training neural networks in principled AND statistically robust ways: Shallow neural networks and Deep neural networks.

Books:

1. Forthcoming book "Mathematical Foundations of Deep Learning " by Konstantinos Spiliopoulos, Richard Sowers and Justin Sirignano. Code accompaning the book (to be made public in due time).

Submitted papers:

1. "Uniform in time bounds for a stochastic hybrid system with fast periodic sampling and small white-noise", (with Shivam Singh Dhama), 2024, [ArXiv preprint], submitted.
2. "Kernel Limit of Recurrent Neural Networks Trained on Ergodic Data Sequences", (with Samuel Chun-Hei Lam, Justin Sirignano), 2023, [ArXiv preprint], [CODE], submitted.
3. "On the large-time behaviour of affine Volterra processes", (with Antoine Jacquier and Alexandre Pannier), 2022, [ArXiv preprint], submitted.
4. "Scaling Limit of Neural Networks with the Xavier Initialization and Convergence to a Global Minimum ", (with Justin Sirignano), 2019, [ArXiv preprint], unpublished technical note, available on arxiv.

Book Chapters:

1. "Importance sampling for metastable and multiscale dynamical systems", Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology, (Editors: D. Holcman) , Springer, 2017, pp 29-53, [ArXiv preprint]
2. "Systemic Risk and Default Clustering for Large Financial Systems", Large Deviations and Asymptotic Methods in Finance, (Editors: P. Friz, J. Gatheral, A. Gulisashvili, A. Jacqier, J. Teichmann) , Springer Proceedings in Mathematics and Statistics, Vol. 110 2015, [SSRN] ,[ArXiv preprint].

Publications (by topic):

• Mathematical and Computational Methods for Machine Learning
• Monte Carlo Accelerated Methods
• Agent based modeling and applications to large networks (biological, financial, social)
• Homogenization, Large Deviations and Metastability for Stochastic Dynamical Systems (SDEs, SPDEs, Interacting Particle Systems)
• Financial Mathematics
• Statistical Inference for Stochastic Processes and Stochastic Dynamical Systems

Publications (complete list):

1. "Stochastic gradient descent-based inference for dynamic network models with attractors", (with Hancong Pan, Xiaojing Zhu, Cantay Caliskan, Dino P. Christenson, Dylan Walker, Eric D. Kolaczyk), Journal of Computational and Graphical Statistics, 2024, [ArXiv preprint], [CODE], to appear.
2. "Mean field limits of particle-based stochastic reaction-drift-diffusion models", (with Max Heldman, Samuel A. Isaacson and Qianhan Liu), Nonlinearity, 2024, [ArXiv preprint], to appear.
3. "Quantitative fluctuation analysis of multiscale diffusion systems via Malliavin calculus", (with Solesne Bourguin), Stochastic Processed and their Applications, 2024, [ArXiv preprint], to appear.
4. "Transport map unadjusted Langevin algorithms: learning and discretizing perturbed samplers", (with Benjamin J. Zhang, Youssef M. Marzouk), AIMS Foundations of Data Science, 2024, [ArXiv preprint], to appear.
5. "Importance sampling for stochastic reaction-diffusion equations in the moderate deviation regime", (with Ioannis Gasteratos and Mickey Salins), Stochastics and Partial Differential Equations: Analysis and Computations, Volume 12, 2024, pages 2081--2150, [ArXiv preprint].
6. "Fluctuation analysis for particle-based stochastic reaction-diffusion models", (with Max Heldman, Samuel A. Isaacson and Jingwei Ma), Stochastic Processed and their Applications, Volume 167, January 2024, 104234, [ArXiv preprint].
7. "Moderate deviations for fully-coupled multiscale weakly interacting particle systems", (with Zachary Bezemek), Stochastics and Partial Differential Equations: Analysis and Computations, Volume 12, 2024, pp. 1265-1373, [ArXiv preprint].
8. "Normalization effects on deep neural networks", (with Jiahui Yu), AIMS Journal on Foundations of Data Science, 2023, Volume 5, Issue 3: pp. 389-465, [ArXiv preprint], [CODE].
9. "PDE-constrained Models with Neural Network Terms: Optimization and Global Convergence", (with Justin Sirignano and Jonathan MacArt), 2023, Journal of Computational Physics, Volume 481, 15 May 2023, 112016, [ArXiv preprint].
10. "Moderate deviation principle for multiscale systems driven by fractional Brownian motion", (with Solesne Bourguin and Thanh Dang), Journal of Theoretical Probability, 36, Article number: 1 (2023), [ArXiv preprint].
11. "Disentangling positive and negative partisanship in affective polarization using a coevolving latent space network with attractors model", (with Xiaojing Zhu, Cantay Caliskan, Dino P. Christenson, Dylan Walker, Eric D. Kolaczyk), 2023, Journal of the Royal Statistical Society: Series A, Volume 186, Issue 3, July 2023, pp. 463-480, [ArXiv preprint], [CODE].
12. "Large deviations for interacting multiscale particle systems", (with Zachary Bezemek), Stochastic Processed and their Applications , Volume 155, January 2023, Pages 27-108, [ArXiv preprint].
13. "Geometry-informed irreversible perturbations for accelerated convergence of Langevin dynamics", (with Benjamin J. Zhang, Youssef M. Marzouk), 2022, Statistics and Computing, 32, Article number: 78 (2022), [ArXiv preprint].
14. "Rate of homogenization for fully-coupled McKean-Vlasov SDEs", (with Zachary Bezemek), Stochastics and Dynamics, Vol. 23, No. 02, 2350013 (2023), [ArXiv preprint].
15. "Online Adjoint Methods for Optimization of PDEs", (with Justin Sirignano), Applied Mathematics and Optimization, 85, Article number: 18 (2022). [ArXiv preprint].
16. "Moderate deviations for systems of slow-fast stochastic reaction-diffusion equations", (with Ioannis Gasteratos and Mickey Salins), Stochastics and Partial Differential Equations: Analysis and Computations, (2023), Vol.11, pp. 503--598. [ArXiv preprint].
17. "Mean Field Limits of Particle-Based Stochastic Reaction-Diffusion Models", (with Samuel A. Isaacson and Jingwei Ma), 2022, SIAM Journal on Mathematical Analysis, Vol. 54, No. 1, pp. 453--511, [ArXiv preprint].
18. "Asymptotics of Reinforcement Learning with Neural Networks", (with Justin Sirignano), Stochastic Systems, Vol. 12, No. 1, March 2022, pp. 2--29, [ArXiv preprint].
19. "Discrete-time inference for slow-fast systems driven by fractional Brownian motion", (with Solesne Bourguin and Siragan Gailus), 2021, SIAM Journal on Multiscale Modeling and Simulation, Vol. 19, No. 3, pp. 1333--1366, [ArXiv preprint].
20. "How reaction-diffusion PDEs approximate the large-population limit of stochastic particle models", (with Samuel A. Isaacson and Jingwei Ma), 2021, SIAM Journal on Applied Mathematics, Vol. 81, No. 6, pp. 2622--2657, [ArXiv preprint].
21. "Normalization effects on shallow neural networks and related asymptotic expansions", (with Jiahui Yu), 2021, AIMS Journal on Foundations of Data Science , June 2021, Vol. 3, Issue 2, pp. 151-200. [ArXiv preprint], [CODE].
22. "Metastability and exit problems for systems of stochastic reaction-diffusion equations", (with Michael Salins), 2021, Annals of Probability , Vol. 49, No. 5, pp. 2317--2370, [ArXiv preprint].
23. "Mean field analysis of deep neural networks", (with Justin Sirignano), 2021, Mathematics of Operations Research, Vol. 47, No. 1, pp. 120-152, [ArXiv preprint].
24. "Typical dynamics and fluctuation analysis of slow-fast systems driven by fractional Brownian motion", (with Solesne Bourguin and Siragan Gailus), 2021, Stochastics and Dynamics, Vol. 21, No. 07, 2150030, [ArXiv preprint], [Stochastics and Dynamics Best Paper Awards 2021].
25. "Optimal investment, derivative demand, and arbitrage under price impact", (with Michail Anthropelos and Scott Robertson), 2021, Mathematical Finance, Vol. 31, Issue 1, pp. 3-35, [ArXiv preprint].
26. "Selection of quasi-stationary states in the stochastically forced Navier-Stokes equation on the torus", (with Margaret Beck, Eric Cooper and Gabriel Lord), 2020, Journal of Nonlinear Science , Volume 30, pp. 1677--1702, [ArXiv preprint].
27. "Network effects and default clustering for large systems", (with Jia Yang), 2020, Journal of Applied Mathematical Finance, Volume 26, Issue 6, pp. 523--582, [ArXiv preprint].
28. "Importance sampling for slow-fast diffusions based on moderate deviations", (with Matthew Morse), 2020, SIAM Journal on Multiscale Modeling and Simulation, Vol. 18, No. 1, pp. 315--350. [ArXiv preprint].
29. "Mean field analysis of neural networks: a law of large numbers", (with Justin Sirignano), 2020, SIAM Journal on Applied Mathematics, Vol. 80, Issue 2, pp. 725--752. [ArXiv preprint].
30. "Information geometry for approximate Bayesian computation", 2020, SIAM/ASA Journal on Uncertainty Quantification, Vol. 8, Issue 1, pp. 229--260 [ArXiv preprint].
31. "Optimal scaling of the MALA algorithm with irreversible proposals for Gaussian targets", (with Michela Ottobre and Natesh S. Pillai), 2020, Stochastics and Partial Differential Equations: Analysis and Computations, Vol. 8, pp. 311--361 [ArXiv preprint]
32. "Stochastic gradient descent in continuous time: a central limit theorem", (with Justin Sirignano), 2019, Stochastic Systems , Volume 10, Issue 2, pp. 99-191, [ArXiv preprint].
33. "Mean field analysis of neural networks: A central limit theorem", (with Justin Sirignano), 2020, Stochastic Processes and their Applications , Volume 130, Issue 3, March 2020, pp. 1820-1852, [ArXiv preprint].
34. "Pathwise moderate deviations for option pricing", (with Antoine Jacquier), 2019, Mathematical Finance, Vol. 30, Issue 2, pp. 426--463, [ArXiv preprint].
35. "Large deviations and averaging for systems of slow--fast stochastic reaction--diffusion equations", (with Wenqing Hu and Michael Salins), 2019, Stochastics and Partial Differential Equations: Analysis and Computations, Vol. 7, Issue 4, pp. 808-?874, [ArXiv preprint].
36. "Selection of quasi-stationary states in the Navier-Stokes equation on the torus", (with Margaret Beck and Eric Cooper), 2019, Nonlinearity , Vol. 32, pp. 209--237, [ArXiv preprint].
37. "Analysis of multiscale integrators for multiple attractors and irreversible Langevin samplers", (with Jianfeng Lu), 2018, SIAM Multiscale Modeling and simulation , Vol. 16, Issue 4, pp. 1859--1883. [ArXiv preprint].
38. "Discrete-time statistical inference for multiscale diffusions", (with Siragan Gailus), 2018, SIAM Multiscale Modeling and simulation , Vol. 16, Issue 4, pp. 1824--1858, [ArXiv preprint].
39. "DGM: A deep learning algorithm for solving partial differential equations", (with Justin Sirignano), 2018, Journal of Computational Physics , Vol. 375, pp. 1339--1364, [ArXiv preprint].
40. "Sequential Monte Carlo for fractional Stochastic Volatility Models", (with Alexandra Chronopoulou), 2018, Quantitative Finance , Vol. 18, Issue 3, pp. 507--517, [ArXiv preprint].
41. "Indifference pricing for Contingent Claims: Large Deviations Effects", (with Scott Robertson), 2018, Mathematical Finance , Vol. 28, Issue 1, pp. 335--371, [ArXiv preprint].
42. "Stochastic gradient descent in continuous time", (with Justin Sirignano), 2017, SIAM Journal on Financial Mathematics, Vol. 8, Issue 1, pp. 933--961, [ArXiv preprint]
43. "Dimension Reduction in Statistical Estimation of Partially Observed Multiscale Processes", (with Andrew Papanicolaou), 2017, SIAM Journal on Uncertainty Quantification, Vol. 5, pp. 1220-1247, [ArXiv preprint]
44. "Hypoelliptic multiscale Langevin diffusions: Large deviations, invariant measures and small mass asymptotics", (with Wenqing Hu), 2017, Electronic Journal of Probability, Vol. 22 (2017), paper no. 55, pp. 1-38, [ArXiv preprint]
45. "Rare event simulation via importance sampling for linear SPDE's", (with Michael Salins), 2017, Stochastics and Partial Differential Equations: Analysis and Computations, Vol. 5, Issue 4, pp. 652-690, [ArXiv preprint].
46. "The effect of heterogeneity on flocking behavior and systemic risk", (with Fei Fang and Yiwei Sun), 2017, Statistics and Risk Modelling, Vol. 34, No. 3--4, pp. 141-155, [ArXiv preprint]
47. "Moderate deviations principle for systems of slow-fast diffusions", (with Matthew R. Morse), 2017, Asymptotic Analysis, Vol. 105, No. 3-4, pp. 97-135, [ArXiv preprint].
48. "The pricing of contingent claims and optimal positions in asymptotically complete markets", (with Michail Anthropelos and Scott Robertson), 2017, Annals of Applied Probability, , Vol. 27, No. 3, pp. 1778-1830, [ArXiv preprint]
49. "Markov processes with spatial delay: path space characterization, occupation time and properties", (with Michael Salins), 2017, Stochastics and Dynamics , Vol. 17, No. 6, 1750042 (21 pages), [ArXiv preprint].
50. "Statistical Inference for Perturbed Multiscale Dynamical Systems", (with Siragan Gailus), 2017, Stochastic Processes and their Applications , Volume 127, Issue 2, pp. 419-448, [ArXiv preprint]
51. "Improving the convergence of reversible samplers", (with Luc Rey-Bellet), 2016, Journal of Statistical Physics , August 2016, Vol. 164, Issue 3, pp. 472-494, [ArXiv preprint].
52. "Rare event simulation for multiscale diffusions in random environments", 2015, SIAM Multiscale Modeling and Simulation , Vol. 13, No. 4, pp. 1290--1311 [ArXiv preprint].
53. "Escaping from an Attractor: Importance Sampling and Rest Points I", (with Paul Dupuis and Xiang Zhou), 2015, Annals of Applied Probability , Vol. 25, No. 5, pp. 2909-2958, [ArXiv preprint]
54. "Irreversible Langevin samplers and variance reduction: a large deviation approach", (with Luc Rey-Bellet), 2015, Nonlinearity , Vol. 28, pp. 2081-2103, [ArXiv preprint]
55. "Default Clustering in Large Pools: Large Deviations", (with Richard Sowers), 2015, SIAM Journal on Financial Mathematics , Vol. 6, (2015), pp. 86-116, [SSRN], [ArXiv preprint].
56. "Quenched Large Deviations for Multiscale Diffusion Processes in Random Environments", 2015, Electronic Journal of Probability, Vol. 20, (2015), no. 15, pp. 1-29, [ArXiv preprint]
57. "Variance reduction for irreversible Langevin samplers and diffusion on graphs", (with Luc Rey-Bellet), 2015, Electronic Communications in Probability, Vol. 20, (2015), no. 15, pp. 1-16, [ArXiv preprint].
58. "Non-asymptotic performance analysis of importance sampling schemes for small noise diffusions", 2015, Journal of Applied Probability , Vol. 52, pp. 1-14, [ArXiv preprint]
59. "Large Portfolio Asymptotics for Losses from Default", (with Kay Giesecke, Richard Sowers and Justin A. Sirignano), 2015, Mathematical Finance, Vol. 25, No. 1, (January 2015), pp. 77-114, [SSRN] ,[ArXiv preprint]
60. "Rare event simulation in the neighborhood of a rest point", (with Paul Dupuis), 2014, Winter Simulation Conference, article in pdf , (IEEE, 2014), pp. 564-573 .
61. "Filtering the Maximum Likelihood for Multiscale Problems", (with Andrew Papanicolaou), 2014, SIAM Multiscale Modeling and Simulation , Vol. 12, No. 3, pp. 1193-1229, [ArXiv preprint].
62. "Fluctuations Analysis for Loss from Default", (with Kay Giesecke and Justin A. Sirignano), 2014, Stochastic Processes and their Applications, Volume 124, Issue 7, pp. 2322-2362, [SSRN],[ArXiv preprint].
63. "Scaling Limits and Exit Law for Multiscale Diffusions", (with Sergio A. Almada), 2014, Asymptotic Analysis, Volume 87, pp. 65-90, [ArXiv preprint].
64. "Fluctuation analysis and short time asymptotics for multiple scales diffusion processes", 2014, Stochastics and Dynamics, Vol. 14, No.3, pp. 1350026 [ArXiv preprint].
65. "Maximum likelihood estimation for small noise multiscale disffusions", (with Alexandra Chronopoulou), 2013, Statistical Inference for Stochastic Processes,Volume 16, Issue 3, pp. 237-266, [ArXiv preprint]
66. "Large Deviations and Importance Sampling for Systems of Slow-Fast Motion", 2013, Applied Mathematics and Optimization, Vol. 67, pp. 123-161, [ArXiv preprint]
67. "Default Clustering in Large Portfolios: Typical Events", (with Kay Giesecke and Richard Sowers), 2013, Annals of Applied Probability, Volume 23, Number 1, pp. 348-385, [SSRN], [ArXiv preprint].
68. "Importance Sampling for Multiscale Diffusions", (with Paul Dupuis and Hui Wang), 2012, SIAM Multiscale Modeling and Simulation , Vol. 12, No. 1, pp. 1-27, [ArXiv preprint].
69. "Large Deviations for Multiscale Diffusions via Weak Convergence Methods", (with Paul Dupuis), 2012, Stochastic Processes and Their Applications, 122, pp. 1947-1987, [ArXiv preprint].
70. "Large Deviations Principle for a Large Class of One-Dimensional Homogeneous Strong Markov Processes", 2012, Journal of Theoretical Probability, Volume 25, Issue 4, pp. 925-949, [ArXiv preprint]
71. "Recovery Rates in Investment-Grade Pools of Credit Assets: A Large Deviations Analysis", (with Richard Sowers), 2011, Stochastic Processes and Their Applications, Volume 121, Issue 12, pp. 2861-2898, [SSRN] ,[ArXiv preprint].
72. "Rare Event Simulation in Rough Energy Landscapes", (with Paul Dupuis and Hui Wang), 2011, Winter Simulation Conference, article in pdf , (IEEE, 2011), pp. 504-515.
73. "Wiener Process with Reflection in Nonsmooth Narrow Tubes", 2009, Electronic Journal of Probability, Vol. 14, Paper no. 69, pp. 2011-2037 article in pdf
74. "Method of Moments Estimation of Ornstein-Uhlenbeck Processes Driven by General Levy Process", 2009, Annales de l'I.S.U.P., Volume 53 - Fascicule 2-3, pp. 3-19 [ArXiv preprint]
75. "Reaction Diffusion Equations with Non-Linear Boundary Conditions in Narrow Domains", (with Mark Freidlin), 2008, Asymptotic Analysis, Volume 59, Number 3-4, pp.227-249 article in pdf
76. "A note on the Smoluchowski- Kramers approximation for the Langevin equation with reflection", 2007, Stochastics and Dynamics, Vol. 7, No. 2, pp. 141-153 : article in pdf

Other Publications:

• PhD Thesis. "Asymptotic problems for stochastic processes with reflection and related PDE's", University Of Maryland, College Park, USA, May 2009, Thesis
  Advisor: Professor Mark Freidlin.
• M.A. scholarly paper. "The Smoluchowski-Kramers approximation for the Langevin equation with reflection in 1-D", University Of Maryland, College Park, USA, May 2006, Scholarly paper
  Advisor: Professor Mark Freidlin.
• Undergraduate thesis. "Extension of Ito Formulae to Sobolev Spaces and some Applications", National Techincal University of Athens, Greece,June 2004, Thesis in Greek
  Advisor: Professor Ioannis Spiliotis.

Current Students and Postdoctoral Associates:

• Ankan Ganguly, Postdoctoral fellow at Boston University, 2023-2026
  
• Shivam Singh Dhama, Postdoctoral fellow at Boston University, 2023-2026
  
• Konstantin Riedl, Postdoctoral fellow at Oxford University, 2024-2027
  
  
• Lanlan Liu, PhD candidate, co-advised with Samuel Isaacson, Fall 2021-present
  Project: Analysis and computation of stochastic reaction-diffusion models for biological systems.
• Hancong Pan, PhD candidate, co-adviced with Eric Kolaczyk, Spring 2022-present
  Project: Analysis and computation for co-evolving latent space network networks with attractors.
• Yao Chen, PhD candidate, co-advised with Samuel Isaacson, Spring 2024-present
  Project: TBA.
• Nikos Georgoudios, PhD candidate, Spring 2024-present
  Project: TBA.
• Zhuo Zhao, PhD candidate, co-advised with Max Reppen, Summer 2024-present
  Project: TBA.

Former Students and Postdoctoral Associates:

• Jiahui Yu, Postdoctoral fellow, 2020-2022
  Project: Normalization effects in neural networks
• Siragan Gailus, Postdoctoral fellow, 2018-2020
  Project: Averaging and statistical inference for multiscale systems driven by fractional Brownian motion.
  First position: Post-doctoral fellow at TU Berlin, Germany.
• Michael Salins, Postdoctoral fellow, 2015-2017
  First position: Assistant Professor at Mathematics and Statistics Department at BU, Boston.


• Zachary Bezemek, PhD, Spring 2023
  Project: Interacting particle systems in multiscale environments.
  First position: Assistant Research Professor at Duke University, North Carolina.
• Ioannis Gasteratos, PhD, co-advised with Michael Salins, May 2022
  Project: Moderate deviations for multiscale stochastic reaction-diffusion equations and related importance sampling schemes.
  First position: Post-doctoral fellow at Imperial College, London.
• Jingwei Ma, PhD, co-adviced with Samuel Isaacson, May 2021
  Project: Stochastic reaction-diffusion problems in modelling biological systems
  First position: Data scientist at Tik-Tok.
• Jia Yang, PhD, August 2020
  Project: Clustering, contagion and dynamic network models.
  
• Eric Cooper, PhD, co-adviced with Margaret Beck, May 2019
  Project: Selection of quasi-stationary states in the Navier-Stokes equation on the torus.
  First position: Senior Data Scientist at Sports Betting Innovative Analytics.
• Matthew Morse, PhD, December 2018
  Project: Moderate deviations and importance sampling for multiscale diffusions.
  First position: Lecturer at Department of Mathematics and Statistics, University of Maine.
• Siragan Gailus, PhD, August 2018
  Project: Statistical Inference for Multiscale Diffusions with Small Noise.
  First position: Post-doctoral fellow, Boston University.


• Zixin Ding, Undegraduate student, Summer 2019
  Project: Irreversibility in stochastic gradient descent methods.
• Weiwei Wu, MA student, Summer 2018
  Project: Feedback in dynamic networks.
  First position: PhD Student at University of California at San Diego.
• Quentin Chauleur, Undergraudate visiting student from France, ENs de Rennes, Summer 2017
  Project: Exploration of rare event simulation methods for stochastic dynamical systems.
• Ting Wang, Undergraduate student, Summer 2017
  Project: Study of irreversible perturbations in estimation.
• Fei Fang, MA student, Summer 2015
  Project: The effect of heterogeneity on flocking behavior and systemic risk.
  First position: PhD Student at University of North Carolina at Chapel Hill.
• Yiwei Sun, Undergraduate student, Summer 2015
  Project: The effect of heterogeneity on flocking behavior and systemic risk.
• Do Young Yoon, Undergraduate student, Summer 2012
  Project: Introduction to stochastic process
  
• Abhay Sagar, MSc student (Brown University), Summer 2010
  Project: Independent Study on Survival Analysis

Distinctions, Awards and Grants:

• 2023-2026, NSF-DMS 2311500.
• 2021-2025, NSF-SES 2120115.
• 2021-2025, NSF-DMS 2107856.
• 2020-2025, Department of Defense/ARO W911NF2010244.
• 2020-2022, SIMONS FELLOW in Mathematics; Award No 672441.
• 2016-2021, NSF CAREER AWARD, NSF-DMS 1550918.
• 2015, Alfred P. Sloan Foundation support for attending the EVA 2015 conference.
• 2013-2017, Hariri Institute Junior Fellow.
• 2013-2017, NSF-DMS 1312124.
• 2012, SIAM travel grant for the 2012 SIAM Conference on Financial Mathematics & Engineering (FM12).
• 2011, IATF travel grant, Brown University.
• 2011, NSF block travel grant for the 16th INFORMS Applied Probability Conference.
• 2008-2009, Monroe Martin Talk Award in the presentation competition of the Spotlight on Graduate Research at the University of Maryland.
• Fall 2008, Awarded Department of Mathematics Dissertation Fellowship, University of Maryland.
• 2007-2008, Seymour Goldberg Paper Award in the written competition of the Spotlight on Graduate Research at the University of Maryland.
• 2007, Levermore Foundation Travel Grant, University of Maryland.
• 2006, Goldhaber Travel Grant, Graduate School, University of Maryland.
• 2004-2006, Block Grant Fellowship from the Department of Mathematics of the University of Maryland.
• 2004-2005, Award from Eygenidio Foundation for outstanding Greek Students that are pursuing graduate studies.
• 2003-2005, Three times awarded from the Technical Chamber of Greece for academic excellence at the School of Applied Mathematics and Physical Sciences of the National Technical University of Athens, Greece.
• 2003-2005, Three times awarded from the Greek State Scholarships Foundation for academic excellence at the School of Applied Mathematics and Physical Sciences of the National Technical University of Athens, Greece.

Editorial Work:

• 2024-present, Associate Editor for Machine learning for computational science and engineering.
• 2021-present, Associate Editor for SIAM Journal on Financial Mathematics.
• 2020-2021, Editor for a special issue on "Machine Learning in Finance" for Applied Mathematical Finance.
• 2020-present, Associate Editor for Applied Mathematical Finance.
• 2018-present, Associate Editor for Foundations of Data Science (an AIMS Journal).

Invited Talks and Lectures:

1. July 14-18 2025, Invited talk at the workshop 44th Conference on Stochastic Processes and their Applications, to be held in Wroclaw, Poland
2. July 9-11 2025, Invited talk at the workshop Vienna Congress on Mathematical Finance, to be held in Vienna, Austria
3. June 3-5 2025, Invited talk at the SPDEs Workshop at Ohio State University
4. May 17 2025, Invited talk at Athens Probability Colloquium, Athens, Greece
5. April 25 2025, Invited talk at Department of Mathematics, Florida State University, Colloquium talk
6. April 4 2025, Invited talk at Department of Mathematics and Statistics, McGill University, Montreal, Canada
7. March 3-7 2025, Invited talk at the workshop on "SIAM Conference on Computational Science and Engineering (CSE)", Fort Worth, Texas
8. February 11 2025, Invited talk at Department of Mathematics and Statistics, UMass Amherst, Amherst, MA.
9. November 10-15 2024, Invited talk at the workshop on "Modeling, Learning and Understanding: Modern Challenges between Financial Mathematics, Financial Technology and Financial Economics", BIRS, Canada
10. October 21-25 2024, Invited talk at the workshop on "SIAM Conference on Mathematics of Data Science (MDS24)", Atlanda, Georgia
11. September 13-15 2024, Invited talk at the workshop on "Robust Optimization and Simulation of Complex Stochastic Systems", ICERM, Providence, USA
12. July 5 2024, Invited talk at the School of Electrical and Computer Engineering, National Techinal University of Athens, Greece
13. July 3-4 2024, Workshop on "Archimedes Workshop on Foundation of Modern AI", National Techinal University of Athens, Greece
14. May 6-10 2024, Invited talk at the workshop on "Interacting Particle Systems: Analysis, Control, Learning and Computation", ICERM, Providence, USA
15. April 16 2024, Invited talk at the Analysis and Probability Seminar Department of Mathematics, University of Connecticut, Connecticut, USA
16. November 14 2023 , Invited talk at the Data Science Seminar series at the School of Mathematics, University of Minnesota.
17. 20-22 October 2023, Invited talk at the Eastern Conference on Mathematics Finance (ECMF7) conference at North Carolina State University.
18. 18-20 October 2023 , Invited talk at the workshop on "Extreme and Rare Events: Modeling, Algorithms, and Applications", MIT, Cambridge, USA.
19. July 4-6 2023, Invited talk at the workshop on "Mean field limits for interacting particle systems: uniform propagation of chaos, phase transitions and applications", Imperial College, London, UK.
20. June 19-23 2023, Summer school on Mathematics of Machine and Statistical Learning, National Technical University of Athens, Greece.
21. May 21-24 2023, AFOSR Workshop on Topics at the Intersection of Deep Learning and Computational Nonlinear Control, Monterey, CA.
22. April 17-19 2023, Physics for Neural Networks Workshop, Princeton.
23. March 10 2023, Invited talk at the One World Dynamics seminar (virtual seminar series).
24. Fenruary 27-March 3, 2023, Invited talk at the Rare Events: Analysis, Numerics, and Applications to be held at the newly established Brin Math Research Center, University of College Park, Maryland .
25. February 15, 2023, Invited talk at Los Alamos National Laboratory, Applied Mathematics and Plasma Physics T-5.
26. January 4-7, 2023, Invited talk at the AMS Special Session on Stochastic Analysis and Applications, Joint Mathematical Meeting, Boston
27. December 5, 2022, Invited talk at the Emerging Capabilities & Data Science seminar of Discover Financial Services.
28. October 17-21, 2022, Invited talk at the Asymptotic Problems in Probability and PDE: a Conference in Honor of Mark Freidlin, University of Maryland, College Park, USA.
29. October 1-2, 2022, Invited talk at the AMS Sectional Meeting, "Connections between theoretical and applied dynamical systems: a session in honor of the 60th birthdays of Renato Feres and Boris Hasselblatt", University of Massachusetts in Amherst
30. August 16, 2022, Invited talk at Machine learning seminar at Meta (Facebook).
31. July 4-8, 2022, Invited talk at the Second Congress of Greek Mathematicians, Athens, Greece.
32. June 13-16, 2022, Invited talk at the Conference on the mathematics of complex data at KTH Royal Institute of Technology Stockholm, Sweden.
33. May 13, 2022, Invited talk at the Stochastics, Data and Computing Seminar in Iliniois Institute of Technology (IIT).
34. March 26-27, 2022, Invited talk at the AMS Spring Sectional Meeting (#1177) at Purdue University, West Lafayette, IN.
35. March 24, 2022, Invited talk at the Probability and Stochastic Analysis seminar, Ohio state University.
36. November 29, 2021, Invited talk at the Computational and Applied Math Seminar, Tufts University.
37. November 19, 2021, Invited talk at the Department of Mathematics, Houston University.
38. November 12, 2021, Invited talk at the Department of Mathematics, Tulane University.
39. October 25, 2021, Invited talk at the Department of Mathematics, University of Southern California.
40. October 7, 2021, Invited talk at the Department of Statistics, Columbia University.
41. September 16, 2021, Invited talk at the SIAM Financial Mathematics and Engineering (SIAG/FME) Seminar Series.
42. September 1-7, 2021, Invited talk at the Mathematics and Computation of Financial Engineering planned in Erice (Sicily, Italy)
43. July 1 2021- December 17 2021, Participant on the semester long program on Mathematics of Deep Learning at the Isaac Newton Institute for Mathematical Sciences in Cambridge, England
44. June 21, 2021, Invited talk at the Emerging Capabilities & Data Science seminar of Discover Financial Services.
45. June 1-4, 2021, Invited talk at the session on SIAM conference on Financial Mathematics, Philadelphia, US.
ECRM-MRM seminar
46. May 23-27, 2021, Invited talk at the special section on the interplay between dynamics and data science" at the SIAM conference on Dynamical Systems, Portland, Oregon, US.
47. April 15, 2021, Invited talk at the Applied Probability and Risk Seminar at Columbia University, US.
48. March 20-21, 2021, Invited talk at the special section on stochastic analysis at the AMS Fall Eastern Sectional Meeting
49. March 1-5, 2021, Invited talk at the session on Computational statistics meets computational dynamics, SIAM CSE conference
50. February 5, 2021, Presentation at Sparse data and small datasets in machine learning, Hariri Institute, BU.
51. February 2, 2021, Invited talk at the session on Stochastic Analysis seminar at Imperial College, London, UK.
52. January 22, 2021, Invited talk at the the Clarkson Center for Complex Systems Science, Clarkson University.
53. January 6-9, 2021, Invited talk at the SIAMMINI7 - SIAM Minisymposium on Mathematics of Machine Learning in Finance at the 2021 JMM meeting
54. November 16-17, 2020, Invited talk at the workshop on Uncertainty Management and Machine Learning in Engineering Applications.
55. November 4, 2020, Invited talk at the Probability Seminar of the Department of Mathematics of Univeristy of Utah and University of Arizona (joint seminar).
56. October 7, 2020, Invited talk at the Scientific Computation Seminar at Nottingham, England, UK.
57. October 3-4, 2020, Invited talk at the special section on turbulence and mixing in fluid dynamics at the AMS Fall Eastern Sectional l Meeting
58. September 10, 2020, Invited talk at the financial mathematics seminar at Florida State University
59. July 25, 2020, Invited talk at the Thematic day on the mean field training of multi-layer networks
60. September 9-11, 2020, Invited talk at a conference on Machine Learning in Finance, Imperial College, London. (cancelled due to COVID-19)
61. June 28-July 3, 2020, Invited talk at BIRS Workshop Invitation: Modeling, Learning and Understanding: Modern Challenges between Financial Mathematics, Financial Technology and Financial Economics. (cancelled due to COVID-19)
62. June 8-11, 2020, Invited talk at Workshop on Mathematics for Complex Data, Stockholm, Sweden. (cancelled due to COVID-19)
63. June 5-9, 2020, Invited talk at 13th AIMS Conference on Dynamical Systems, Differential Equations and Applications, Atlanta, USA. (cancelled due to COVID-19)
64. April 10, 2020, Invited talk at Applied Math / Applied Math Lab Seminar, Courant Institute, NYU. (cancelled due to COVID-19)
65. April 3, 2020, Invited talk at Department of Mathematics, Tufts University. (cancelled due to COVID-19)
66. December 11-14, 2019, Invited talk at SIAM Conference on Analysis of Partial Differential Equations, La Quinta, California.
67. October 14-18, 2019, Invited participant at Deep learning and partial differential equations, AIM Workshop San Jose, California.
68. July 8-12, 2019, Invited talk at Stochastic Processes and their applications conference, Chicago, 2019.
69. June 4-7, 2019, Invited talk and Mini-symposium organizer at SIAM Conference on Financial Mathematics and Engineering (FME19), Toronto, Canada.
70. May 19-23, 2019, Invited talk at SIAM Conference on Applications of Dynamical Systems at Snowbird, Utah.
71. May 15-17, 2019, Invited talk at NESS conference 2019, Hartford, Connecticut.
72. April 15, 2019, Invited talk at Department of Applied Probability and Statistics at Sanda Barbara (UCSB), CA.
73. March 14, 2019, Invited talk at Department of Mathematics at the University of Connecticut (Uconn), Connecticut.
74. Feb 25-March 1, 2019, Invited talk at SIAM Conference on Computational Science and Engineering (CSE19), Spokane, WA.
75. November 4-7, 2018, Invited talk at Informs Annual Meeting 2018, Phoenix, Arizona
76. October 24, 2018, Invited talk at ORFE Seminar, Princeton University, NJ.
77. September 17-21, 2018, Invited lecture at Advances in Computational Statistical Physics Perspectives en physique statistique computationnelle, CIRM, Marseille, France.
78. Aug 30-31, 2018, Visit at Department of Mathematics, Imperial College, England.
79. July 10-13, 2018, Invited lecture at Numerical analysis for deterministic and stochastic differential equations, NTUA, Athens, Greece.
80. April 25, 2018, Invited Talk at the Mathematical Finance and Applied Probability Seminar, Department of Mathematics, University of Connecticut.
    
81. April 23, 2018, Invited Talk at the Probability and Statistics Seminar, Department of Mathematics and Statistics, UMASS at Amherst
    
82. April 16-19, 2018, Invited lecture at SIAM Uncertainty Quantification meeting 2018, Garden Grove, California.
83. March 17-18, 2018, Invited lecture at AMS Spring Central Sectional Meeting, Ohio State University, Columbus
84. March 9, 2018, Invited lecture at Scientific computing seminar, Brown University, Providence
85. November 21, 2017, Invited lecture at Applied Mathematics Seminar, Department of Mathematics, Imperial College, England.
86. October 31, 2017, Invited lecture at Department of Mathematics and Statistics, McGill University, Canada.
87. September 15, 2017, JP Morgan and Chase, Quantitative Finance Seminar.
88. August 31-September 2, 2017, Invited lecture at SIAM Conference on Mathematical Modelling in Finance 2017, Imperial College, England.
89. July 14-17, 2017, Invited lecture at Greek stochastics 2017 conference, Milos, Greece.
90. June 14-17, 2017, Invited lecture at Ninth Workshop on Random Dynamical Systems, Bielefeld, Germany.
91. November 25, 2016, Invited lecture at Stochastic Analysis Seminar, Department of Mathematics, Imperial College, England.
92. November 22, 2016, Invited lecture at Statistics Seminar, Department of Mathematics, Imperial College, England
93. November 17-19, 2016, Invited lecture at 2016 SIAM Conference on Financial Mathematics & Engineering (FM16), 2016 conference in Austin, Texas
94. November 12-13, 2016, Co-organizing a Special Session on Recent Advances in Stochastic Processes and Stochastic Computation during the Fall 2016 Southeastern AMS Sectional Meeting North Carolina State University, Raleigh, NC
95. October 18, 2016, Invited Talk at the Applied Analysis and Computation Seminar, Department of Mathematics and Statistics, UMASS at Amherst
    
96. September 5-9, 2016, Invited lecture at MCMC and particle methods: sampling, inference and stochastic approximation, 2016 workshop in ICMS Edinburgh, Scotland
97. August 15-19, 2016, Co-organizing the BU-Keio Joint conference in Probability and Statistics
98. July 18-22, 2016, Invited lecture at Stochastic numerical algorithms, multiscale modeling and high-dimensional data analytics, 2016 workshop in ICERM, Providence, USA
99. July 10-13, 2016, Invited lecture at Greek stochastics 2016 conference, Tinos, Greece
100. June 20-24, 2016, Invited lecture at Spatially Distributed Stochastic Dynamical Systems in Biology Workshop in Newton Institute at Cambridge, England
101. April 27, 2016, Invited lecture at Probability Seminar, Department of Mathematics, University of Maryland at College Park.
102. April 18, 2016, Invited lecture at Colloquium Series on Applied and Computational Mathematics, Department of Mathematics, Penn State University.
103. March 29-April 1, 2016, Invited lecture at the 11th International Workshop on Rare Event Simulation (RESIM), Eindhoven, Netherlands
104. March 16-19, 2016, Seminar on Stochastic Processes 2016, University of Maryland
105. January 14, 2016, Invited lecture at CISE Graduate Student Workshop 3.0.
106. December 7, 2015, Invited lecture at Mathematical Finance, Risk and Uncertainty Seminar, Department of Industrial and Enterprise Systems Engineering and Mathematics Department at the University of Illinois, Urbana-Champaign.
107. November 1-4, 2015, Three Invited lectures at INFORMS Annual Meeting, Philadelphia
108. October 19, 2015, Invited lecture at Department of Mathematics and Statistics, Dynamics seminar, Boston University
109. September 24, 2015, Invited lecture at Department of Mathematics Probability seminar, Duke University
110. August 8-13, 2015, Invited lecture at 2015 Joint Statistical Meeting (JSM), Seattle, Washington
111. July 11-13, 2015, Invited lecture at Greek stochastics 2015 conference, Crete, Greece
112. June 15-19, 2015, Invited lecture at Extreme Value Analysis (EVA) Conference at University of Michigan
113. June 1-5, 2015, Invited/Sponsored Participant at Methods of Mathematical Finance a conference in honor of Steve Shreve?s 65th birthday Carnegie Mellon University, Pittsburgh, PA
114. May 1, 2015, Session Chair and talk at Conference on Mathematical Finance and Partial Differential Equations at Rutgers University, New Brunswick
115. April 8, 2015, Invited lecture at BU-Brown PDE Seminar
116. March 31, 2015, Invited lecture at Department of Mathematics, University of Tennessee
117. March 7-8, 2015, Invited lecture at AMS Eastern Section Meeting
118. January 28, 2015, Invited lecture at Hariri Institute, Boston University
119. January 16, 2015, Invited lecture at Department of Mathematics, Michigan State University
120. December 20-22, 2014, Greek stochastics 2014 conference, Athens, Greece
121. December 7-10, 2014, 2014 Winter Simulation Conference at Savannah, Georgia
122. November 13-15, 2014, Invited lecture at the SIAM Financial Mathematics conference at Chicago
123. Octomber 28, 2014, Invited lecture at the Department of Mathematics, Wayne State University
124. Octomber 20, 2014, Invited lecture at the Department of Mathematics, Carnegie Mellon University
125. September 22-26, 2014, Systemic Risk: Mathematical Modelling and Interdisciplinary Approaches, at the Isaac Newton Institute for Mathematical Sciences in England
126. August 27-29, 2014, Invited lecture at the 10th International Workshop on Rare Event Simulation (RESIM), Amsterdam, Netherlands
127. June 2-6, 2014, Invited lecture at the Computational methods for statistical mechanics -- At the interface between mathematical statistics and molecular simulation, in Edinburgh, Scotland
128. May 6, 2014, Invited lecture at the Probability Seminar at CUNY
129. April 26 2014, Invited lecture at the The 28th New England Statistical Symposium, 26 April 2014
     
130. April 1-4, 2014, Invited lecture at the SIAM conference on Uncertainty Quantification, Savannah, Georgia
131. March 29-30, 2014, Invited lecture at the AMS Sectional Meeting on Mathemtical Finance at University of Maryland, Baltimore County, Baltimore, MD
132. March 13, 2014, Invited lecture at the Stochastics Seminar, Georgia Tech
133. January 15-18, 2014, Invited lecture at the Joint Mathematical Meetings, Baltimore
134. December 5, 2013, Invited lecture at Division of Applied Mathematics, Brown University
135. November 20, 2013, Invited lecture at Hariri Institute, Boston University
136. November 13, 2013, Invited Colloqium lecture at Department of Statistics, University of Connecticut
137. October 17, 2013, Invited lecture at Math Finance Seminar, Columbia University
138. October 12-12, 2013, Invited lecture at AMS Sectional Meeting Program, Temple University, Philadelphia.
139. September 20-22, 2013, Invited lectures at BU-Keio Probability workshop, Boston University, Boston.
140. July 8-12, 2013, Session Chair and Speaker at SIAM Annual Meeting, San Diego, California.
141. June 9-12, 2013, Speaker at SIAM Conference on Mathematical Aspects of Material Science, Philadelphia, Pennsulvania.
142. April 2013, Invited lecture at the The 27th New England Statistical Symposium, 27 April 2013
     
143. April 2013, Invited lecture at the Workshop on Large deviations and asymptotic methods in finance, Imperial College London, England, 9-11 April 2013
     
144. April 2013, Invited lecture at the AMS Sectional Meeting, Boston College, Boston, 6-7 April 2013
     
145. March 2013, Invited Talk at the Stochastics Seminar, Mathematics Department, University of Utah
     
146. February 2013, Invited Talk at the Stochastics Seminar, Mathematics Department, Worcester Polytechnic Institute
     
147. November 2012, Invited Talk at the Seminar of Financial Mathematics, Mathematics Department, University of Michigan, Ann Arbor
     
148. October-November 2012, Invited Talk at the Monte Carlo Methods in the Physical and Biological Sciences, Workshop at ICERM, Brown University, Providence
     Title: Escaping from an attractor: importance sampling and rest points.
149. October 2012, Session Chair at the 2012 Informs Annual meeting in Phoenix, Arizona
     
150. October 2012, Invited Talk at the Probability, PDE and Math Finance Seminar, Department of Mathematics, Rutgers University
     
151. October 2012, Invited Talk at the Probability Seminar, Department of Mathematics, MIT
     
152. October 2012, Invited Talk at the Probability Seminar, Department of Mathematics and Statistics, UMASS at Amherst
     
153. September 2012, Invited Talk at the Data Assimilation Workshop, Oxford-Man Institute, England
     
154. July 2012, Invited Talk at the SIAM Conference on Financial Mathematics and Engineering, Minnesota
     Title: Most Likely Path to Systemic Failure.
155. July 2012, Invited Talk at the Department of Mathematics, University of California at San Diego
     Title: Large Deviations and Monte Carlo Methods for Problems with Multiple Scales.
156. January 2012, Invited Talk at the Department of Statistics & Operations Research, University of North Carolina
     Title: Large Deviations, Metastability and Monte Carlo Methods for Multiscale Problems.
157. 12-16 December 2011, Invited Talk at the EPSRC Symposium Workshop - Multiscale Systems: Theory and Applications, Warwick, England.
     Title: Large deviations for multiscale diffusions and fast simulation.
158. 17 October 2011, Invited Talk at the Department of Operations Research and Financial Engineering, Princeton University.
     Title: Default clustering in large portfolios and most likely path to failure.
159. 5-9 September 2011, Invited Talk at the ENUMATH Conference 2011 Leicester, England.
     Title: Default clustering in large portfolios: typical and atypical events.
160. 6-8 July 2011, Invited Talk at the Applied Probability Society Conference, Royal Institute of Technology (KTH),Stockholm, Sweden.
     Title: Large Deviations and Fast Simulation for Multiscale Diffusions and Rough Energy Landscapes.
161. April 2011, Invited Talk at the Department of Mathematics at Chicago University.
     Title: Large Deviations and Importance Sampling for Multiscale Diffusions.
162. March 2011, Invited Talk at the Department of Mathematics at Stanford University.
     Title: Default clustering in large portfolios: typical and atypical events.
163. Feb 2011, Invited Talk at the Department of Mathematics and Statistics at Boston University.
     Title: Large Deviations and Importance Sampling for Multiscale Diffusions.
164. March 2011, Invited Talk at the Department of Applied Physics and Applied Mathematics at Columbia University.
     Title: Large Deviations and Importance Sampling for Multiscale Diffusions.
165. Feb 2011, Invited Talk at the Department of Mathematics and Statistics at Boston University.
     Title: Large Deviations and Importance Sampling for Multiscale Diffusions.
166. Oct 2010, Invited Talk at the Rare Event Simulation Workshop in Bordeaux, France.
     Title: Large Deviations and Importance Sampling for Multiscale Diffusions.
167. June 2010, Talk at the Department of Mathematics at the University of Minnesota.
     Title: Reaction-Diffusion Equations with Nonlinear Boundary Conditions in Narrow Domains and Wave Front Propagation.
168. April 2009, Invited talk at the Department of Mathematics at the University of Illinois at Urbana-Champaign.
     Title: Reaction-Diffusion Equations with Nonlinear Boundary Conditions in Narrow Domains and Wave Front Propagation.
169. April 2009, Invited talk at the Department of Statistics at Warwick University.
     Title: Reaction-Diffusion Equations with Nonlinear Boundary Conditions in Narrow Domains and Wave Front Propagation.
170. January 2009, Invited talk at the Department of Statistics and Applied Probability and the Center for Financial Mathematics and Statistics (CRFMS) at the University of Santa Barbara.
     Title: Reaction-Diffusion Equations with Nonlinear Boundary Conditions in Narrow Domains and Wave Front Propagation.
171. October 2008, Talk at the Applied Partial Differential Equations Research Interaction Team (RIT) at the University of Maryland.
     Title: Reaction-Diffusion Equations in Narrow Domains and Wave Front Propagation.
172. September 2008, Invited talk at the School of Applied Mathematics and Physics of the National Technical University of Athens, Greece
     Title: Reaction-Diffusion Equations with Non-Linear Boundary Conditions in Narrow Tubes and Wave Front Propagation.
173. May 2008-2007, Invited lectures on Advanced Analytic Methods with Applications (Graduate course at the University of Maryland)
     Title: Lectures in homogenization with probabilistic methods.
174. May 2008, Invited talk at the Graduation Conference at the University of Maryland.
     Title: Reaction Diffusion Equations with Non-Linear Boundary Conditions in Narrow Domains. (presentation)
175. April 2008, Invited talk at the Graduate Research Interaction Day at the University of Maryland.
     Title: Wave Front Propagation In Narrow Domains.
176. November 2007, Talk at the Mathematical Finance Research Interaction Team (RIT) at the University of Maryland.
     Title: Log Prices following General Levy Driven Ornstein- Uhlenbeck Processes.
177. September 2007, Invited talk at the Graduate Students Statistics and Probability seminar at the University of Maryland.
     Title: Probabilistic Approach in Homogenization: An Introduction. (presentation)
178. September 2007, Invited talk at the Summer School ''De Ludo Aleae'' on probability, Universita' ``La Sapienza'' Roma, Italy.
     Title: Reaction Diffusion Equations with Non-Linear Boundary Conditions in Narrow Domains. (presentation)
179. June 2006, Invited talk at the Workshop: Large Scale Stochastic Dynamics and Interaction with Kinetic Theory, Foundation for Research and Technology, Heraklion Crete, Greece.
     Title: The Smoluchowski-Kramers approximation for the Langevin equation with reflection. (presentation)

Some workshops and conferences that I attended in the past:

• 17-21 March, 2014, Workshop on Stochastic Graph Models, ICERM, Providence, RI.
• 3-8 August, 2013, JSM 2013, Montreal, Canada.
• 9-12 June, 2013, Speaker at SIAM Conference on Mathematical Aspects of Material Science, Philadelphia, Pennsulvania.
• 20-24 May, 2013, Invited Participant Conference on Asymptotic Problems in Honor of Mark Freidlin's Birthday , Maryland.
• 27 April, 2013, Invited lecture at the The 27th New England Statistical Symposium
  
• 9-11 April, 2013, Invited lecture at the Workshop on Large deviations and asymptotic methods in finance, Imperial College London, England
  
• 6-7 April, 2013, Invited lecture at the AMS Sectional Meeting, Boston College, Boston
  
• January 14-18, 2013, Invited Participant at IMA Annual Program Year Workshop Theory and Applications of Stochastic PDEs, Minnesota, Minneapolis.
• July 8-11, 2012, Speaker at SIAM Conference on Financial Mathematics and Engineering, Minnesota, Minneapolis.
• June 4-8, 2012, Probability, Control and Finance A Conference in Honor of Ioannis Karatzas, Columbia University, New York.
• December 12-16, 2011, Speaker at EPSRC Symposium Workshop - Multiscale Systems: Theory and Applications, Warwick, England.
• September 5-9, 2011, Speaker at ENUMATH Conference 2011 Leicester, England.
• July 6-8, 2011, Speaker at Applied Probability Society Conference, Royal Institute of Technology (KTH),Stockholm, Sweden.
• January 24-28, 2011, Participant at Random Media: Homogenization and Beyond IPAM, UCLA.
• October 28-29, 2010, Invited Speaker at Rare Event Simulation Workshop in Bordeaux, France.
• June 7-18, 2010, Participant at New Mathematical Models in Economics and Finance IMA, University of Minnesota.
• May 6-9, 2010, Participant at Stochastics and Dynamics: Asymptotic Problems CSCAMM, University of Maryland at College Park.
• June 9-13, 2008, Participant at The 12th International Conference on Hyperbolic Problems: Theory, Numerics, Applications CSCAMM, University of Maryland at College Park.
• February 21-22 2008, Participant at the February Fourier Talks at the University of Maryland at College Park.
• April 13-15 2007, Minicourse in C++ by Daniel Duffy: Preparation for a Life in Quantitative Finance.
• October 2006, Participant at the Mathematical Finance Conference in honor of the 60th Birthday of Dilip B. Madan, University of Maryland, College Park, USA.

Seminars that I have co-organized or I am co-organizing:

• Colloquium seminar series, Department of Mathematics and Statistics, Boston University
• Probability and Statistics seminar, Department of Mathematics and Statistics, Boston University
• Probability seminar, Division of Applied Mathematics, Brown University
• Students Statistics and Probability seminar at University of Maryland at College Park

Graduate Teaching:

• GRS MA783- Advanced Stochastic Processes (Boston University) Spring 2019, Fall 2021, Fall 2022
  
• GRS MA782- Hypothesis Test (Boston University) Spring 2016, Spring 2022, Spring 2023
  
• GRS MA779- Probability Theory I (Boston University) Fall 2024
  
• GRS MA777- Multiscale Methods for Stochastic Processes and Differenial Equations (Boston University) Spring 2018 , Fall 2023
  
• GRS MA752- Mathematical Foundations of Deep Learning (Boston University) Spring 2024
  
• GRS MA884- Seminar in Probability and Statistics with focus on Multiscale Analysis: Theory, Computation and Applications (Boston University) Spring 2014 , Fall 2019
  


• Fall 2011, Topics in Homogenization: Theory and Computation (APMA 2811L-Brown University)
• Fall 2010, Topics on Averaging and Metastability with Applications (APMA 2811G-Brown University)
• Summer 2010, Topics on Survival Analysis (APMA 2980-Brown University, independent study)
• Fall 2009, Asymptotic Problems for Differential Equations and Stochastic Processes (APMA 2811D-Brown University)
• Spring 2008 and Spring 2007, Advanced Analytic methods with applications (Math 648M-University of Maryland at College Park) Lectures in homogenization with probabilistic methods

Undergraduate Teaching:

• MA 583-Introduction to Stochastic Processes (Boston University), Spring 2013, Spring 2015, Spring 2016, Spring 2018, Spring 2019
• MA 581-Introduction to Probability (Boston University), Spring 2015, Fall 2021,
• MA 115-Statistics I (Boston University), Fall 2012, Fall 2013, Fall 2014, Fall 2015, Fall 2017, Fall 2018, Fall 2019


• APMA 1200-Operations Research -- Probabilistic Models (Brown University), Spring 2011, Spring 2012
• APMA 1680-Nonparametric Statistics (Brown University), Spring 2010
• Math 140-Calculus I (University of Maryland at College Park), Summer 2008
• 2006 - 2008, Discussion leader for College Algebra (Math 113), Intoduction to Differential Equations (Math 246), Calculus III (Math 241) -University of Maryland at College Park

Other Links:

• National Technical University of Athens ,NTUA