Engineering Data

Ashkan B. Jeddi

************.*@***.***

Linkedin.com/in/ashkanbagheri/

EXPERIENCE

The Ohio State University / Graduate Research Associate JANUARY 2019 – PRESENT, COLUMBUS, OH

- Application of Machine Learning Techniques in Solving Engineering Problems

- Deep Learning-Based Computer Vision Approach for Damage Detection from Reconnaissance Data

- Intelligent Management of Real-World Engineering Systems using Reinforcement Learning

- Development of Novel Safe Reinforcement Learning Approach with Transformers

- Using Physics Guided Neural Networks in Modeling Engineering Phenomena Sharif University of Technology / Graduate Research Assistant SEPTEMBER 2015 – SEPTEMBER 2017, TEHRAN, IRAN

TECHNICAL SKILLS

Machine Learning (Linear Regression,

Multiple-Linear Regression, Polynomial

Regression, Logistic Regression, SVR,

Random Forest, K-NN, SVM, Decision

Trees, K-Means, Hierarchical Clustering)

Artificial Intelligence (Bayesian

Networks, DNN, CNN, RNN, LSTM,

Transformers, Computer Vision, Speech

Recognition, NLP, High-Performance

Computing, Parallel and Distributed DNN

Training, Reinforcement Learning, GAN)

Statistical Relational Learning

Data Mining (Data Cleaning &

Interpretation, CRISP-DM)

EDUCATION

The Ohio State University, Columbus / Ph.D., Engineering JANUARY 2019 – PRESENT, COLUMBUS, OH

Minor: Computer Science Engineering, Statistical Data Analysis GPA: 3.918

Sharif University of Technology, Tehran, Iran / M.Sc., Engineering SEPTEMBER 2015 – SEPTEMBER 2017, TEHRAN, IRAN

GPA: 3.86, Distinguished Student (2017)

Iran University of Science and Technology, Tehran, Iran / B.Sc., Engineering SEPTEMBER 2011 – SEPTEMBER 2015, TEHRAN, IRAN

GPA: 3.82, Distinguished Student (2015)

Salam College, Tehran, Iran / High School Diploma in Physics and Mathematics SEPTEMBER 2007 – SEPTEMBER 2011, TEHRAN, IRAN

Qualified for 1st and 2nd stages of National Olympiad on Physics (2009 -2010) Qualified for 1st stage of National Olympiad on Astronomy and Astrophysics (2009) Ranked top 10 in RoboCup Entrance Exam among 300 Students (2007) LANGUAGES & APTITUDES

Python (TensorFlow, Keras, PyTorch,

Pandas, Numpy, Sci-Kit Learn, Matplotlip,

Seaborn, Django)

Git

SQL

AWS

R (Rstudio)

JMP

C++

MATLAB (fuzzy toolbox, neural networks

toolbox, image processing toolbox,

optimization)

Linux

HTML

LaTeX

MS Office

PROJECTS

Optimal Maintenance Planning of Infrastructural Systems using Safe Reinforcement Learning and Recurrent Neural Networks

Advisor: Prof. Eric Fosler-Lussier, SPRING 2020

Review of Papers, Project Adam: Building an Efficient and Scalable Deep Learning Training System and Mesh-TensorFlow: Deep Learning for Supercomputers Advisor: Prof. Dhabaleswar K. Panda, AUTUMN 2019

Utility Poles Degradation Model using Deep Neural Networks with Distributed Training Advisor: Prof. Dhabaleswar K. Panda, AUTUMN 2019

Distributed Training of CBOW and Skip-Gram Models on Word2Vec Dataset using PyTorch and Horovod

Advisor: Prof. Dhabaleswar K. Panda, AUTUMN 2019

Management of Degrading Power Distibution Networks using Machine Learning Advisor: Prof. Yoonkyung Lee, SPRING 2019

RELEVANT COURSEWORK

Speech and Language Processing

Data Mining

Neural Networks

Advanced Artificial Intelligence

High Performance Deep Learning

Statistical Machine Learning

Design of Experiments

Statistics

Linear Algebra

Calculus I – II

LANGUAGES RELEVANT PUBLICATIONS

English (Full Proficiency, TOEFL iBT: 102

GRE General: 312)

Spanish (Basic)

French (Basic)

Farsi (Native)

Dehghani, N. L., Jeddi, A. B., & Shafieezadeh, A. “Intelligent hurricane resilience enhancement of power distribution systems via deep reinforcement learning”. Applied Energy, 285, 116355.

Jeddi, A. B., Dehghani, N. L., & Shafieezadeh, A. “Uncertainty-aware Safe Reinforcement Learning using Transformers and Lyapunov Approach” – In preparation

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