Md Sarowar Morshed

Operations Research Engineer

Intel Corporation

Biography

I am an Operations Research Engineer at Intel. I completed my PhD in Industrial Engineering (Operations Research track) from Northeastern University in 2022. My PhD research was focused on designing scalable stochastic algorithms for solving Large-Scale Optimization and Causal Inference problems. My future research goal is to develop and analyze stochastic algorithms for solving optimization problems arising from diverse areas such as machine learning, data science, and numerical linear algebra. Recently, I have been working on new research directions including 1) optimization algorithms for machine learning, 2) numerical algorithms for data science, 3) stochastic algorithms for optimization problems, and 4) the mathematical foundation that validates these methods.

I received my Bachelor’s in Industrial & Production Engineering from the Bangladesh University of Engineering and Technology (BUET) in 2014, and a Master’s in Applied Mathematics from the University of Central Florida (UCF) in 2017. Outside of work, I love spending time with my family/friends, and playing chess/soccer.

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Interests

Operations Research
Mathematical Optimization
Machine Learning

Education

PhD in Operations Research, 2022

Northeastern University
MS in Applied Mathematics, 2017

University of Central Florida
BS in Industrial Engineering, 2014

Bangladesh University of Engineering & Technology

Skills

ML & Data Science

90%

Python

90%

R

80%

MATLAB

70%

Simulation

30%

Chess

20%

Experience

Operations Research Engineer

Intel Corporation

Jun 2022 – Present Chandler, Arizona

Responsibilities include:

Developing, applying and validating Build, develop, validate and apply decision algorithms, heuristics, optimization and simulation models for complex manufacturing and supply chain problems
Designing and validating deep learning based forecasting models for long range planning

Research Assistant

Northeastern University

Sep 2017 – May 2022 Boston, Massachusetts

Responsibilities include:

Designing randomized algorithms for large-scale linear optimization
Design scalable robust causal inference testing algorithm for big data
Writing grants and peer-reviewed publications
Mentoring Undergraduate and Masters Students

Teaching Assistant

University of Central Florida

Aug 2015 – May 2017 Orlando, Florida

Responsibilities include:

Teaching calculus, algebra and ordinary differential equations to undergraduate students
Teaching trigonometry, algebra and pre-calculus in the Mathematics Assistance & Learning Lab (MALL)

Project Engineer

ILO-BGMEA-BUET Project

Oct 2014 – Jan 2015 Dhaka, Bangladesh

Inspection & submission of Fire Safety Assessment report to International Labour Organization (ILO) about garments industries of Bangladesh

Intern

Square Pharmaceuticals

Jan 2013 – Feb 2013 Dhaka, Bangladesh

Development & implementation of scheduling algorithm for the production process.

Featured Publications

Md Sarowar Morshed

August, 2022 In Arxiv

Lagrangian Sketching Methods for Large-Scale Optimization

We developed the Lagrangian Sketching framework for solving large-scale optimization problems. The proposed framework extends the scope of Skecth & Project methods.

Md Sarowar Morshed

May, 2022 In Arxiv

Randomized Sketching Methods for Linear Optimization: Greedy Sampling & Momentum

In this thesis, our main focus is on the design, analysis, and implementation of such algorithms. In particular, we are interested in developing stochastic iterative methods for solving large-scale linear systems, linear feasibility, and linear programming problems.

Recent Publications

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Md Saiful Islam, Md Sarowar Morshed, Md Noor-E-Alam (2022). A Computational Framework for Solving Nonlinear Binary Optimization Problems in Robust Causal Inference. In INFORMS Journal On Computing.

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Md Sarowar Morshed (2022). Lagrangian Sketching Methods for Large-Scale Optimization. In Arxiv.

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Md Sarowar Morshed (2022). Augmented Newton Method for Optimization: Global Linear Rate and Momentum Interpretation. In Arxiv.

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Md Sarowar Morshed (2022). Randomized Sketching Methods for Linear Optimization: Greedy Sampling & Momentum. In Arxiv.

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Md Sarowar Morshed (2022). Penalty & Augmented Kaczmarz Methods For Linear Systems & Linear Feasibility Problems . In Arxiv.

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Md Sarowar Morshed (2021). Sketch & Project Methods for Linear Feasibility Problems: Greedy Sampling & Momentum. In Arxiv.

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Md Sarowar Morshed, Chrysafis Vogiatzis, Md Noor-E-Alam (2021). A primal–dual interior point method for a novel type-2 second order cone optimization. In Results in Control and Optimization.

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Md Sarowar Morshed, Sabbir Ahmad (2021). Stochastic Steepest Descent Methods for Linear Systems: Greedy Sampling & Momentum. In Arxiv.

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Md Sarowar Morshed (2021). Heavy Ball Momentum Induced Sampling Kaczmarz Motzkin Methods for Linear Feasibility Problems. In Arxiv.

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Md Sarowar Morshed, Md Saiful Islam, Md Noor-E-Alam (2021). Sampling Kaczmarz-Motzkin Method for Linear Feasibility Problems: Generalization & Acceleration. In Mathematical Programming.

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Md Sarowar Morshed, Md Noor-E-Alam (2020). Generalized Affine Scaling Algorithms for Linear Programming Problems. In Computers & Operations Research.

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Md Sarowar Morshed (2020). Logarithmic Integrals: A Review from Gradshteyn and Ryzhik to Recent Times. In Arxiv.

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Md Sarowar Morshed, Md Saiful Islam, Md Noor-E-Alam (2019). Accelerated Sampling Kaczmarz Motzkin Algorithm for Linear Feasibility Problem. In Journal of Global Optimization.

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Md Saiful Islam, Md Sarowar Morshed, Gary J. Young, Md Noor-E-Alam (2019). Robust Policy Evaluation from Large-Scale Observational Studies. In PLOS ONE.

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