CV
Education
- Ph.D in Operations Research, University at Buffalo (SUNY), 2020
- M.S. in Industrial Engineering, K. N. Toosi University, 2014
Work experience
- Data Scientist / OR Scientist, Deccan International, 2020
- Graduate Research Assitant, 2015-2020
- Project Control Engineer, Mahab Ghodss, 2010-2015
Skills
- Machine Learning
- Network Optimization
- Probabilistical Modelling
- Mathematical Optimisations
- Statistical Modelling
Publications
Talks
- Aarabi, F., Batta, R., , “Server Positioning and Response Strategies for Spatially Arriving Jobs with Degradation: Light and Medium Traffic Cases” , INFORMS annual meeting 2021, Anaheim, CA, October 24-27 2021.
- Aarabi, F., Batta, R., , “A Mixed Integer Programming Approach for Scheduling Spatially Distributed Jobs with Degradation Rate: Application to Pothole Repair” , TRISTAN, Hamilton Island, Australia, June 2019.
- Aarabi, F., Batta, R. , “Using the Hypercube Queueing Model for Response to Jobs with Degradation”, Session: Joint Session TSL/Practice Curated:Patrolling and Service Delivery Problems, INFORMS annual meeting 2018, Phoenix, AZ, November 3-8, 2018.
- Aarabi, F., Batta, R. , “An MIP Approach for scheduling jobs with degradation rate”, UB Engineering graduate student poster competition and 2018 ISE graduate student poster competition, University at Buffalo, The State University of New York at Buffalo.
- Aarabi, F., Batta, R. , “An MIP Approach for Planning Pothole Repair”, Session: Resilience in Transportation Infrastructure Systems, INFORMS annual meeting 2017, Houston, TX, October 22-25, 2017.
Teaching
IE 305, Applied Probability (Undergraduate level course). It is an OR undergraduate core course . This course covers probability and its application to engineering problems. Assisted by conducting weekly recitation sessions, providing weekly office hours, grading assignments and exams, giving quizzes, and proctoring.
IE 504, Facilities Design (Graduate level course). This course covers facilities design related problems, especially in manufacturing systems.
IE 582, Robotics (Graduate level course). This course focuses on Analysis of robots and robotic systems. Kinematics, coordinate transform, vision systems, off-line programming, and simulation of robotic systems. Assisted in teaching Python and Linux, providing weekly office hours, grading assignments and exams, giving quizzes, and proctoring.
IE 374, Systems Modeling and Applications of OR (Undergraduate level course). This course covers the markov system modeling, markov decision processes and applications, queueing theory.