Danial Mohseni Taheri

Ph.D. Candidate at University of Illinois at Chicago.

I am currently a Ph.D. candidate at the University of Illinois at Chicago, Department of Information and Decision Sciences. Here at UIC, I am working with Prof. Nadarajah. My research focuses on developing and applying machine learning, statistical, and optimization algorithms to enhance the accuracy of prediction and decision making in applications such as user behavior modeling, portfolio management, and investment.

I enjoy problem-solving and love coding. Ever since writing my first algorithm in Python, I have been obsessed with the idea of using programming languages to solve practical problems. I also enjoy building a statistical and mathematical frame for modeling problems as it challenges so many aspects of my intellect: creativity, sequential thinking, and problem-solving. Finally, I like to be challenged by learning new materials quickly.

RECENT NEWS:

November 2019:

PUBLICATIONS

  • Meeting Corporate Renewbale power targets, Under review in Management Science (with S. Nadarajah, A. Trivella) [PDF]
  • Interpretable User Models via Decision-rule Gaussian Processes, NuerIPS 2019 (AABI symposium) (with S. Nadarajah, T. Tulabandhula)
  • Investment under Limited Long-Term Information, Working Paper (with S. Nadarajah, A. Kelevin, S-E. Feleten )
  • Overbooking in Network of Storage Assets, Technical report (with S. Nadarajah, T. Tulabandhula )

SKILLS AND BACKGROUND

Interests

  • Machine Learning
  • Deep Learning
  • Reinforcement Learning
  • Applied statistics

Programming

  • Python (Pandas, Pytorch, Tensorflow, Keras, Scikit-Learn, Scipy)
  • C++
  • R, MATLAB
  • SQL, Spark
  • Unix, AWS

Education

  • PhD in Information and Decision Sciences, University of Illinois at Chicago(Exp. 2020)

  • BSc in Industrial Engineering, AmirKabir University, 2015

EXPERIENCE

Graduate Reaserch Assistant in Artificial Intelligence

  • Designed and implemented interpretable user models to predict users’ behavior using inference and transfer learning; tested the algorithm on corporate data; increased the accuracy of overbooking decisions by 10%.
  • Developed and implemented near-optimal stochastic decision-making algorithms to decrease the cost of constructing a portfolio of a financial commodity by 4%.
  • Proposed an algorithm for decision making under limited long-term information of uncertainties; calibrated a statistical model on time series corporate data.

Graduate Teaching Assistant in Data science

  • Machine learning: Deep learning, bayesian inference, reinforcement learning
  • Foundation of optimization: Linear and integer programming
  • Programming: Provided tutorials in Pytorch
  • Projects and leadership: Mentored graduate students in deep learning projects such as object detection and image classification (including CNN and RNN models).

Data science Mentor

  • Cloudbakers: Led a group of graduate students in gathering data and creating a pipeline for clustering repositories in GitHub to evaluate their health. Presented results to stakeholders, Fall 2019
  • Varuna (Startup): Collaborated with co-founders and graduate students on processing data and building a learning algorithm to predict failures in water purification plants , Spring 2019

INVITED TALKS

Interpretable User Models via Decision-rule Gaussian Processes
INFORMSAnnual Meeting, Seattle, Washington
OCT 2019
Meeting Corporate Renewable Power Targets
INFORMSAnnual Meeting, Seattle, Washington
OCT 2019
Overbooking in Network of Storage Assets
Production and Operations Management Society Annual Conference, Washington D.C. (POMS)
May 2019
Meeting Corporate Renewable Power Targets
Production and Operations Management Society Annual Conference (POMS)
May 2019
Investment under Limited Long-Term Information
Production and Operations Management Society Annual Conference (POMS)
May 2019
Dual Reoptimization based Approximate Dynamic Programming
INFORMS Annual Meeting, Phoenix, Arizona
Nov 2019
Meeting Corporate Renewable Power Targets
Production and Operations Management Society Annual Conference, Houston, Texas (POMS)
May 2019
Meeting Corporate Renewable Power Targets
Manufacturing & Service Operations Management Annual Conference, Dallas, Texas (MSOM)
Jul 2018