Dr. Debdatta Sinha Roy | Data-driven | Best Researcher Award

Dr. Debdatta Sinha Roy, Oracle Retail Science R&D, United States

Debdatta Sinha Roy is a Principal Research Scientist in Operations Research and Data Science at Oracle, based in Burlington, Massachusetts, USA. He specializes in optimization, machine learning, and data-driven decision-making under uncertainty, with practical applications across retail, supply chain, logistics, and service operations. He holds a Ph.D. in Operations Management from the University of Maryland’s Robert H. Smith School of Business, where he received the Best Dissertation Proposal Award for his work on data-driven optimization in logistics. Debdatta earned his dual B.S.-M.S. degree in Mathematics from the Indian Institute of Science Education and Research, Mohali, where he was awarded the prestigious President of India Gold Medal. With professional experience at Oracle and Staples, his work has contributed to cutting-edge retail forecasting systems, fulfillment optimization, and intelligent logistics networks. He has also published impactful research on routing problems, stochastic modeling, and social choice theory, and maintains an academic lineage that traces back to George Dantzig.

Professional Profile:

ORCID

Summary of Suitability

Dr. Debdatta Sinha Roy is a highly accomplished researcher whose work lies at the intersection of operations research, optimization, and machine learning, with transformative applications in retail, supply chain logistics, and service operations. His research combines theoretical rigor with real-world impact, making him exceptionally suitable for recognition with the Best Researcher Award.

🎓 Education

Ph.D. in Operations Management/Management Science
📍 University of Maryland, College Park, USA (Aug 2014 – Aug 2019)
🏆 Best Dissertation Proposal Award in Management Science
📘 Dissertation: Data-Driven Optimization and Statistical Modeling to Improve Decision Making in Logistics
B.S.-M.S. Dual Degree in Mathematics
📍 Indian Institute of Science Education and Research, Mohali, India (Aug 2009 – May 2014)
🥇 President of India Gold Medal
📘 Thesis: Social Choice Theory and Max-Plus Algebra

💼 Work Experience

Oracle, Inc., Burlington, MA, USA
🧪 Principal Research Scientist (Sep 2024 – Present)
🧪 Senior Research Scientist (Jul 2021 – Aug 2024)
🔧 Projects: AI Foundation (Oracle Retail), recommendation systems, fulfillment forecasting, item classification, and forecasting pipelines.
Staples, Inc., Framingham, MA, USA
🔬 Research Scientist – Operations Research and Data Science (Sep 2019 – Jul 2021)
📦 Projects: Carton demand forecasting, on-demand routing, dynamic UPS/FedEx optimization, middle-mile logistics.
University of Maryland, College Park, MD, USA
🎓 Graduate Research Fellow (Aug 2014 – Aug 2019)
🔍 Focus: Optimization, ML, routing problems, Bayesian models, and graph-based heuristics.
Indian Statistical Institute, New Delhi, India
👨‍🏫 Visiting Research Student – Economics & Planning Unit (May 2012 – May 2014)
📊 Focus: Social Choice Theory, Mathematical Economics.
Indian Institute of Science, Bangalore, India
🧠 Summer Research Intern – Graph Theory and Combinatorics (May 2011 – Jul 2011)

🏅 Achievements, Awards & Honors

🏆 Best Dissertation Proposal Award, University of Maryland
🥇 President of India Gold Medal, IISER Mohali
🧬 Academic Lineage: George Dantzig → Thomas Magnanti → Bruce Golden → Debdatta Sinha Roy
🎯 Led high-impact industrial projects at Oracle and Staples integrating optimization + ML in real-world retail and logistics

Publication Top Notes:

Using regression models to understand the impact of route-length variability in practical vehicle routing

Data-driven optimization and statistical modeling to improve meter reading for utility companies

Modeling and Solving the Intersection Inspection Rural Postman Problem

Estimating the Tour Length for the Close Enough Traveling Salesman Problem

DATA-DRIVEN OPTIMIZATION AND STATISTICAL MODELING TO IMPROVE DECISION MAKING IN LOGISTICS

Elnaz Yaghoubi | Power System Analysis | Best Researcher Award

Dr. Elnaz Yaghoubi, karabuk university, Turkey.

Elnaz Yaghoubi is a dedicated Ph.D. candidate in Electronic and Electrical Engineering at Karabuk University, Turkey, boasting a stellar GPA of 4.0. Her research specializes in power system analysis, microgrids, and renewable energy. Elnaz holds an M.Sc. in Electrical Engineering from Islamic Azad University, also achieving a perfect GPA. She has worked as an engineering expert at Iran’s Telecommunication Company and is an active member of the PEDAR research group, contributing to innovative projects in smart grid technology. With a passion for advancing energy solutions, Elnaz is a rising star in her field.

Education and Experience:

Ph.D. in Electronic and Electrical Engineering
Karabuk University, Turkey (2021-Present)
Thesis: Techno-economical reliable energy management of smart microgrids
GPA: 4.0

M.Sc. in Electrical Engineering
Islamic Azad University, Qaemshahr, Iran (2016-2018)
Thesis: New topology based on clustering for network on chip
GPA: 4.0

B.Sc. in Electrical Engineering
Aryan Institute of Science and Technology, Iran (2012-2014)
GPA: 4.0

Associate’s Degree in Electrical Engineering
University College of Rouzbahan, Iran (2010-2012)
GPA: 4.0

Principle Researcher
PEDAR Group (2023-Present) 🧑‍🔬

Expert in Traffic Monitoring and Data Support
Telecommunication Company, Iran (2017-2021)

Data Network Design
Telecommunication Company, Iran (2015-2017)

Suitability for Best Researcher Award:

Dr. Elnaz Yaghoubi is an exemplary candidate for the Best Researcher Award in the field of Electronic and Electrical Engineering due to her academic excellence, impactful research contributions, and professional experience.

Professional Development:

Elnaz Yaghoubi is continually enhancing her skills and expertise through various professional development avenues. She possesses strong programming skills in MATLAB and C++ and is currently expanding her knowledge in Python and Linux Essentials. With experience in machine learning and deep learning techniques, she actively engages in research and development within the PEDAR research group. Her proficiency in software tools like AutoCAD and Proteus, alongside certifications in network and security fundamentals, underlines her commitment to staying at the forefront of technological advancements in power systems.

Research Focus:

Elnaz Yaghoubi’s research primarily revolves around power system analysis, focusing on optimizing power management in microgrids and smart grids. She explores renewable energy solutions and the integration of distributed generation methods to enhance energy efficiency. Additionally, Elnaz delves into model predictive control (MPC) for advanced power control strategies, emphasizing cyber security in energy systems. Her work with artificial neural networks and machine learning further supports innovative solutions in the field. Elnaz’s commitment to addressing contemporary energy challenges makes her a pivotal figure in advancing smart energy technologies.

Publication top Notes:

State-of-the-art review on energy and load forecasting in microgrids using artificial neural networks, machine learning, and deep learning techniques

Cited by: 85 | Year: 2023

The role of mechanical energy storage systems based on artificial intelligence techniques in future sustainable energy systems

Cited by: 15 | Year: 2023

Triple-channel glasses-shape nanoplasmonic demultiplexer based on multi nanodisk resonators in MIM waveguide

Cited by: 12 | Year: 2021

Reducing the vulnerability in microgrid power systems

Cited by: 11 | Year: 2023

Electric vehicles in China, Europe, and the United States: Current trend and market comparison

Cited by: 10 | Year: 2024

Tunable band-pass plasmonic filter and wavelength triple-channel demultiplexer based on square nanodisk resonator in MIM waveguide

Cited by: 10 | Year: 2022

A systematic review and meta-analysis of machine learning, deep learning, and ensemble learning approaches in predicting EV charging behavior

Cited by: 9 | Year: 2024