Nima Manaf

Hi there!

I'm Nima, a data scientist with an insatiable curiosity and a passion for uncovering the hidden stories within data. My journey has been exciting, combining a Ph.D. in Business with explorations into engineering and AI. This unique blend has given me the ability to see the big picture while still appreciating the beauty in the details. I'm always eager to push the boundaries of what's possible, using innovative techniques to harness the power of data, compute, and digitization. Whether I'm working independently or collaborating with a diverse team, I bring enthusiasm and a positive attitude. I'm a lifelong learner who thrives in fast-paced, challenging environments, driven by a desire to make a real impact.

Work Experience

May 2022 - Present

Data Scientist

Rabobank, Utrecht, Netherlands

Driving data analytics at Rabobank's Risk Department

  • Spearheaded the EU AI-Act task force.
  • Evaluated ML models for ECB reporting.
  • Addressed methodological challenges for the Rural Portfolio.
  • Adapted latest EBA Guidelines with Python.
  • Developed monitoring frameworks for Risk-Adjusted Return on Capital.
  • Designed and implemented Challenger Models for the IFRS9 team.

Sept 2020 - April 2022

Postdoctoral Research Associate

Eindhoven University of Technology, Eindhoven, Netherlands

Leading cutting-edge research in the Future Logistics initiative while mentoring the next generation

  • Conducted research on evolutionary training of deep neural networks.
  • Applied Reinforcement Learning and Evolution Strategies for inventory management problems.
  • Supervised Bachelor’s and Master’s student theses.

Feb 2019 - Jan 2020

PhD Industrial Sabbatical

Bosch Center for AI, Stuttgart, Germany

Pioneered ML-driven automation for semiconductor decision-making.

  • Researched application of Q-Learning and Monte-Carlo Tree Search for parallel machine scheduling problems.
  • Developed the reinforced genetic algorithm.
  • Analyzed large manufacturing network data from the semiconductor wafer fabrication.
  • Learn Offline, Search Online, A Hybrid Approach to Solving Scheduling Problems Patent No. 389829

Education

Sept 2016 - Sept 2020

PhD in Business Administration

Koç University, Turkey

Ph.D. Thesis Title: Modelling and Control of Production Systems Based on Observed Inter-event Times: An Analytical and Empirical Investigation

  • Analyzed extensive event data from semiconductor wafer fabrication.
  • Developed ML and statistical methods for production time prediction.
  • Conducted theoretical research on optimal control based on data-analysis results.

You may find the full text of my PhD Thesis on arXiv, or an overview of it here

Supervisor: Prof. Dr. Barış Tan

Sept 2014 - Sept 2016

MSc in Operations and Information Systems

Koç University, Turkey

You may find the full text of my Master Thesis on the National Thesis Center of Turkey.

Sept 2010 - Sept 2014

BSc in Industrial Engineering

Sharif University of Technology, Iran

Awards, Patents, and Certificates

Awards
  • PhD Academic Excellence Award, Koç University, Turkey, Sept 2020
  • Exceptional Talent Student Title (ranked among top 0.1% students in the National University Entrance Exam among more than half a million participants), June 2010
  • Ranked among the top 1% of the participants in the National Chemistry Olympiad - Iran, Feb 2009
Scholarships
  • Productive 4.0 Project Scholarship from Scientific and Technological Research Council of Turkey, Sept 2017
  • Full Ph.D. Scholarship, Koç University, Turkey, Sept 2016
  • Full M.Sc. Scholarship, Koç University, Turkey, Sept 2014
Patents
  • Learn Offline, Search Online, A Hybrid Approach to Solving Scheduling Problems (Patent No. 389829)
Certificates
Grants
  • NWO (The Dutch Research Council) 500,000 Hours of Computing Time Grant on National Computer Facilities
  • NWO (The Dutch Research Council) 1000,000 Hours of Computing Time Grant on National Computer Facilities
Languages
  • Azerbaijani (Native)
  • Turkish (Native)
  • Farsi (Native)
  • English (Fluent)
  • Dutch (Beginner)
Personal Interests
  • Evolution
  • Markets
  • Electronic Music
  • Natural Language Processing
  • Mathematics
  • Numerical Computing
  • Physical Activities
  • Wandering in nature

Skills

Machine Learning and AI

Reinforcement Learning, Supervised Learning, Unsupervised Learning, Deep Learning, Graph Neural Networks, Gradient-Free Learning, Statistical Learning

Optimization Methods

Combinatorial Optimization, Stochastic Optimization, Evolution Strategies, Genetic Algorithms, Monte-Carlo Tree Search, Markov Decision Processes, Mathematical Programming, Constraint Programming, Dynamic Programming

Applications

Supply Chain Management, Resource Allocation, Inventory Control, Production Planning, Scheduling, Routing, Healthcare Operations, Queuing Systems, Semiconductor Wafer Fabrication

Software and Programming Languages

Programming Languages: Python, C++, SQL
Python-C++ Integration Module: Pybind11
Parallel Processing Modules: Ray, MPI, Multiprocessing
Discrete Optimization Modules: Gurobi, CPLEX, LocalSolver, SCIP, Google OR Tools
Machine Learning Modules: Pytorch, Deep Graph Library, Scikit-learn, XGBoost, LightGBM, CatBoost, Statsmodels
Data Analytics and Visualization Modules: Numpy, Scipy, Pandas, cudf, Zarr, Matplotlib, Seaborn, Bokeh, Plotly
Versioning tools: git

Leadership and Coordination

Master's Student Thesis Supervision
Bachelor's Student Thesis Supervision
Academia (Research) - Industry (Practice) Project Coordination
Project Management