SEARCH

PhD Researcher Resume Example

Love this resume?Build Your Own Now
PHD RESEARCHER
Professional Summary

I specialize in operations research, supply chain management, and transportation problems. I am currently completing a Ph.D. in applied mathematics, and I also have MS degrees in applied mathematics as well as a graduate certificate in data science. I have received extensive training in data science through courses, workshops, and a variety of other advancement opportunities. In addition, I am proficient with both SAP and Tableau data visualization software.

Enthusiastic Data and Operations Research Analysts eager to contribute to team success through hard work, attention to detail and excellent organizational skills. A clear understanding of Data Visualization and Supply Chain Management and training in Machine Learning Tools. Motivated to learn, grow and excel in Logistics and Supply Chain Industries.

Skills
  • Experienced in Python, MATLAB, R
  • Expert in SQL and good knowledge in data visualization package SAP, Tableau
  • Good skills in machine learning application tools and software such as Spark, Scikit-learn, TensorFlow, Scala
  • Proficient in Microsoft Office (Word, Excel, PowerPoint, Outlook)
  • Familiar with Google collab, AWS
  • Expert in document preparation software LATEX, LyX.
  • Big data, Data Entry, Data Management, Data Visualization, Data mining
  • Procurement Analysis, Cost analysis, Profit Optimization
  • Demand Forecasting, Inventory Control, Supply Chain Management
  • Efficient researcher
Work History
PhD Researcher, 01/2016 to Current
Company Name – City, State
  • Completed an inventory supply chain project with arbitrary demand distributions.
  • Defined gener- alized ordering cost/production function for arbitrary number of suppliers.
  • Developed a complete mathematical formulation for inventory supply chain policy.
  • Developed an optimal policy struc- ture for dual suppliers with lost sales(unsatisfied demand is lost) strategies.
  • The software tools used were MATLAB and Python.
  • Developed a policy for arbitrary demand that minimizes the total expected cost (or equivalently, maximizes the total expected profit) over the infinite horizon for dual suppliers or a single supplier with big volume order.
  • This methodology can predict the demand based on historical data, and then decide the volume of orders that are required to order to minimize the inventory costs.
  • Completed a project for an infinite horizon problem with exponential demand.
  • Developed a generalized optimal policy structure to order/produce inventory volume so that the expected total cost is minimized.
  • This policy optimally considers all suppliers, both local and distant.
  • Proposed a reduction of this policy that, under specific conditions, is optimal in the single supplier case.
  • Completed a project addressing the backlog sales (i.e., unsatisfied demand backloged) case and de- veloped an ordering policy for general demand distributions.
  • The planning horizon is infinite and the supply can be either multisource or single source.
  • Used MATLAB for numerical experiments and verified both numerical and theoretical results for the newly proposed policy.
  • Working on a project developing a deep neural network based algorithm for inventory ordering policies for both backlog and nonbacklog cases.
  • The programming language in use is Python.
  • Lead author of one published paper and two unpublished papers, all arising from these projects.
  • Completed a project on image classification using convolutional neural networks.
  • Used VGG-16, the pre-trained convolutional neural network, which is trained on the Animals-10 dataset.
  • Used Python with the matplotlib, pandas, numpy, keras, and tensor flow libraries to classify the animals correctly from the dataset, which contains 28,266 images of animals belonging to 10 different categories.
  • Improved validation accuracy to 86%.
  • Completed a big data project on house price prediction using advanced regression techniques in R such as multiple linear regression, random forests and gradient boosting.
  • Used the 10-fold cross-validation technique on the training set to estimate the reduced mean square error.
  • Completed a classification project on prostate cancer data using Python, Scikit Learn (a data mining tool).
  • Used grid search for automatic parameter tuning of the classification algorithms.
  • The algorithms explored were the decision tree, neural net, support vector machine, Gaussian naive Bayes, logistic regression, nearest neighbor, bagging, random forest, and AdaBoosting algorithms.
Senior Lecturer, 02/2012 to 12/2015
Company Name – City, State
  • Utilized innovative methods of instruction, including video, interactive class activities and discussions to present course material.
  • Completed a project on transportation problems with the goal of minimizing the total transportation costs. Proposed a new algorithm, known as the lowest allocation method (LAM). This
    the algorithm requires fewer iterations than any other known algorithm and yields a near-optimal solution to the transportation problem.
  • Co-author of an article that studied a transportation problem and proposed a new approach known as the implied cost method (ICM), which generates the optimal solution that is more accurate than those obtained with Vogel's approximation method (VAM), and moreover, the estimates generated with ICM are always very close to, if not coinciding with, the optimal solution.
  • Selected material relevant to each course of study and presented in an engaging fashion. Lectured and developed curriculum in financial mathematics for undergraduate bachelor of business administration students. Designed approximately 40 assignments and a number of exams. Developed other teaching materials such as syllabi, visual aids, and example solutions.
  • Lectured on financial mathematics to approximately 2000 students.
Supply Chain Data Entry and Trainer, 05/2008 to 03/2011
Company Name – City, State
  • Recorded information to the internal database, performed data entry and retrieval, and performed arithmetical computations. Used Microsoft Excel for calculations, simulations, and creating tools.
  • Worked with a team to define potential solutions to computer business needs and guided the business management in choosing the best option and approach. Managed all technical and logistical preparations for the procurement of materials from markets in other parts of the country. Determined the volume of inventory to order.
  • Carried out component cost analysis on all current product lines and future product releases and arranged for the timely payment for all materials ordered, ensuring optimal pricing of all inventory sold and maximal product profit margins.
  • Reviewed and analyzed any inventory problems. Handled transactions and safety stock requirements. Established supply chain partnerships to increase operational readiness and support.
  • Monitored, analyzed and reported on inventory accuracy and control. Scheduled procurement and distribution for groups of products which are typically high demand in specific regions or
    needed on an urgent basis.
  • Performed continuous evaluations of content and plans in order to enhance delivery and improve effectiveness.
  • Instructor of Microsoft Word, Microsoft Excel, Microsoft PowerPoint, and Firefox.
Education
Ph.D.: Mathematics, Expected in 06/2020
The University of Texas At Dallas - City, State

Specialization in Optimal Inventory Control, Dynamic Programming, Stochastic Optimization, Cost Minimization under the supervision of Dr. Alain Bensoussan and Dr. Viswanath Ramakrishna.

Graduate Certificate in Data Science: Data Science, 12/2019
The University of Texas At Dallas - City, State

Topics Covered: Big Data Management and Analytics, Machine Learning, Statistical Machine Learning, Algorithm and Data Structure, Foundation of Data Sciences, Combinatorics and Graph Theory, Optimization, Operations Research, Numerical Analysis.

Master of Science: Applied Mathematics, 05/2019
The University of Texas At Dallas - City
Certifications
  • Machine Learning A-ZTM: Hands-On Python & R In Data Science, Udemy
  • R Programming in Data Science: High Volume Data, LinkedIn
  • Six Sigma Green Belt, Project Management Institute
Build Your Own Now

DISCLAIMER

Resumes, and other information uploaded or provided by the user, are considered User Content governed by our Terms & Conditions. As such, it is not owned by us, and it is the user who retains ownership over such content.

How this resume score could be improved?

Many factors go into creating a strong resume. Here are a few tweaks that could improve the score of this resume:

82Good
Resume Strength
  • Formatting
  • Word choice
  • Measurable results
  • Strong summary
  • Typos

Resume Overview

School Attended

  • The University of Texas At Dallas

Job Titles Held:

  • PhD Researcher
  • Senior Lecturer
  • Supply Chain Data Entry and Trainer

Degrees

  • Ph.D. : Mathematics , Expected in 06/2020
    Graduate Certificate in Data Science : Data Science , 12/2019
    Master of Science : Applied Mathematics , 05/2019

Similar Resumes

View All
PhD-Scholar-resume-sample

PhD Scholar

Mexico City, Mexico City