**To create today is to create dangerously. Any publication is an act, and that act exposes one to the passions of an age that forgives nothing.**

Albert Camus

##### 2024

ISMP 2024, International Symposium on Mathematical Programming, Montreal, Canada.*(upcoming)**Fast convergence of Stochastic Algorithms for Constrained Optimization.*

2nd Derivative-Free Optimization Symposium, Padova, Italy.*(upcoming)**Line Search and Trust Region Methods in the Presence of Noise.*

##### 2023

- CSE DSI Machine Learning Seminar Series, Data Science Initiative, College of Science and Engineering, University of Minnesota, Minneapolis, MN.
*Next Generation Algorithms for Stochastic Optimization with Constraints.*(slides)

- Mathematics and Statistics Seminar, Department of Mathematics and Statistics, Loyola University, Chicago, IL.
*Next Generation Algorithms for Stochastic Optimization with Constraints.*(slides)

- INFORMS Annual Meeting 2023, Institute for Operations Research and the Management Sciences Conference, Phoenix, AZ.
*Next Generation Algorithms for Stochastic Optimization with Constraints.*(slides)

- MOPTA 2023, Modeling and Optimization: Theory and Applications, Bethlehem, PA.
*Balancing Communication and Computation in Gradient Tracking Algorithms for Decentralized Optimization*. (slides)

- CS and Math Department Seminar, UniversitÃ© Paris Dauphine, Paris, France.
*Next Generation Algorithms for Stochastic Optimization with Constraints.*(slides)

- SIAM-OPT 2023: SIAM Conference on Optimization, Seattle, WA.
*Algorithms for Deterministically Constrained Stochastic Optimization.*(slides)

- Michigan Institute Computational Discovery and Engineering (MICDE) Seminar Series Winter 2023, Ann Arbor, MI.
*Algorithms for Deterministically Constrained Stochastic Optimization.*(slides)

- 12th US-Mexico Workshop on Optimization and Its Applications, Huatulco, Oaxaca, Mexico.
*Algorithms for Deterministically Constrained Stochastic Optimization.*(slides)

##### 2022

- INFORMS Annual Meeting 2022, Institute for Operations Research and the Management Sciences Conference, Indianapolis, IN.
(slides)*Algorithms for Deterministically Constrained Stochastic Optimization.*

- ICCOPT 2022: International Conference on Continuous Optimization, Bethlehem, PA.
*Analysis of Trust-Region Methods with Errors.*(slides)

- IOS 2022: INFORMS Optimization Society Conference Meeting 2021, Greenville, SC.
Mathematics in Imaging, Data and Optimization (MIDO) Seminar, Department of Mathematical Science, Rensselaer Polytechnic Institute (RPI), Troy, NY.*(virtual)**Algorithms for Deterministically Constrained Stochastic Optimization.*(slides)

Computational Mathematics Seminar, Mathematical Sciences Institute, Australian National University, Canberra, Australia.*(virtual)**Algorithms for Deterministically Constrained Stochastic Optimization.*(slides)

WOPS 2022: Workshop on Optimization, Probability and Simulation, The Chinese University of Hong Kong, Shenzhen, China.*(virtual)**Algorithms for Deterministically Constrained Stochastic Optimization.*(slides)

##### 2021

INFORMS Annual Meeting 2021, Institute for Operations Research and the Management Sciences Conference, Anaheim, CA.*(virtual)**Adaptive Algorithms for Nonlinear Equality Constrained Stochastic Optimization.*(slides)

OR Colloquium, Penn State, Department of Industrial and Manufacturing Engineering.*(virtual)**Algorithms for Deterministically Constrained Stochastic Optimization*. (slides)

SIOPT 2021, SIAM Conference on Optimization, Spokane, WA.*(virtual)**Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization.*(slides)

*(virtual)*EURO 2021, 31st European Conference on Operations Research, Athens, Greece.*Analysis of Line Search and Trust Region Methods with Noise.*(slides)

*(virtual)*EUROPT 2021, 18th Workshop on Advances in Continuous Optimization, Toulouse, France.*Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization.*(slides)

*(virtual)*Statistics Seminar, UW Madison, Department of Statistics.*Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization.*(slides)

*(virtual)*3rd IMA and OR Society Conference on Mathematics of Operational Research.*Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization.*(slides)

*(virtual)*CSE 2021, SIAM Conference on Computational Science and Engineering.*A Symmetric Blockwise Truncated Optimization Algorithm for Machine Learning.*(slides)

##### 2020

*(virtual)*INFORMS Annual Meeting 2020, Institute for Operations Research and the Management Sciences Conference, National Harbor, MD.*Analysis Of A Generic Line Search Method With Noise: Algorithms, Convergence Rates And Gradient Approximation.*(slides)

*(postponed due to COVID-19)*DataX Workshop (September 2020): Old and New Open Questions in Optimization, Princeton University, Princeton, NJ.*Limited-Memory BFGS with Displacement Aggregation*.

*(postponed due to COVID-19)*SIOPT 2020, SIAM Conference on Optimization, Hong Kong.*Global Convergence Rate Analysis of a Line Search Algorithm with Noise*.

*(postponed due to COVID-19)*MDS 2020: SIAM Conference on Mathematics of Data Science, Cincinnati, OH.*Sampled Quasi-Newton Methods For Deep Learning*.

- JMM 2020, Joint Mathematics Meetings, Denver, CO.
*A Theoretical and Empirical Comparison of Gradient Approximations in Derivative-Free Optimization: Algorithms, Convergence Analysis and Noise*. (slides)

##### 2019

- Numerical Analysis and Scientific Computing Seminar, November 2019, Courant Institute of Mathematical Sciences, New York University, New York, NY.
*Limited-Memory BFGS with Displacement Aggregation. (slides)*

- INFORMS Annual Meeting 2019, Institute for Operations Research and the Management Sciences Conference, Seattle, WA.
*Quasi-Newton Methods For Deep Learning: Forget The Past, Just Sample.*(slides)

- Young Researchers Workshop 2019, ORIE, Cornell University, Ithaca, NY.
*Global Convergence Rate Analysis of a Generic Line Search Algorithm with Noise*. (slides)

- ICCOPT 2019, International Conference on Continuous Optimization, Berlin, Germany.
*Aggregated Quasi-Newton Methods*. (slides)

- INFORMS PhD Seminar 2019, Lehigh University, Bethlehem, PA.
*A Theoretical and Empirical Comparison of Gradient Approximations in Derivative-Free Optimization*. (slides)

- CSE 2019, SIAM Conference on Computational Science and Engineering, Spokane, WA.
*Scaling up and Randomizing Derivative-Free Optimization for Machine Learning*. (slides)

##### 2018

- INFORMS Annual Meeting 2018, Institute for Operations Research and the Management Sciences Conference, Phoenix, AZ.
*Stochastic Quasi-Newton Methods â€“ Past, Present and Future*. (slides)

- 2nd NSF TRIPODS PI Workshop 2018, University of California, Santa Cruz, CA.
*Do we Need 2nd Order Methods in Machine Learning?*(poster)

- MOPTA 2018, Modeling and Optimization: Theory and Applications, Bethlehem, PA.
*Derivative-Free Optimization of Noisy Functions via Quasi-Newton Methods*. (slides)

- ISMP 2018, International Symposium on Mathematical Programming, Bordeaux, France.
*Derivative-Free Optimization of Noisy Functions via Quasi-Newton Methods*. (slides)

- SPIE-MRSEC Student Seminar Series 2018, Northwestern University, Evanston, IL.
*Methods for Large Scale Nonlinear and Stochastic Optimization*. (slides)

##### 2017

- OptML Seminar 2017, Lehigh University, Bethlehem, PA.
*Stochastic Newton and Stochastic Quasi-Newton Methods for Nonlinear Optimization*. (slides)

- INFORMS Annual Meeting 2017, Institute for Operations Research and the Management Sciences Conference, Houston, TX.
*Derivative-Free Optimization via Quasi-Newton Methods*. (slides)

- IFORS 2017, International Federations on Operations Research Societies Conference, Quebec city, Canada.
*Balancing Computation and Communication in Distributed Optimization*. (slides)

- MMLS 2017, Midwest Machine Learning Symposium, Chicago, IL.
*Are Newton-Sketch and Subsampled Newton Methods Effective in Practice?*(poster)

- SIOPT 2017, SIAM Conference on Optimization, Vancouver, Canada.
*A Numerical Investigation of Sketching and Subsampling*. (slides)

- ACNTW 2017, Northwestern University, Chicago, IL.
*Are Newton-Sketch and Subsampled Newton Methods Effective in Practice?*(poster)

- CASSC 2017, SIAM Student Conference (Chicago area), Evanston, IL.
*A Multi-Batch L-BFGS Method for Machine Learning*. (slides)

##### 2016

- NeurIPS 2016, Neural Information Processing Systems Conference, Barcelona, Spain.
- ECML 2016, European Conference on Machine Learning, Riva del Garda, Italy.
- Fields Institute Workshop on Nonlinear Optimization Algorithms and Industrial Applications 2016, Toronto, Canada.
*A Robust Multi-Batch L-BFGS Method for Machine Learning*. (poster)

- CASSC 2016, SIAM Student Conference (Chicago area), Chicago, IL.
*An Adaptive Quasi-Newton Algorithm for Training RNNs*. (slides)