Engineer Machine

Syeduzzaman Khan

********@*.********.*** **** Pacific Ave, Stockton, CA 95211 209-***-****

GitHub: https://github.com/sskhan67

Selected Professional Experience

August’18-June’20 Graduate Teaching Assistant

School of Engineering and Computer Science

University of the Pacific, Stockton, CA

January’17- July’17 Junior officer at Network and Data Centre Infrastructure Team Information Technology Division, United Commercial Bank Ltd. Corporate Head office, Gulshan Avenue, Dhaka, Bangladesh September’16- December’16 Software Engineer

Exquisite ICT Ltd., Dhaka, Bangladesh

February’14- August’16 IT Support Engineer

Modern Lift Ltd.

Dhaka 1206, Bangladesh

June’12-April’13 Master Thesis Student

Schaeffler Technologies AG & Co. KG

Herzogenaurach, Germany

November’11-March’12 Student Research Assistant, Institute for Knowledge-Based Systems and Knowledge Management, University of Siegen, Siegen, Germany

Education

Master of Science in Engineering Science 2020

University of the Pacific, Stockton, CA, Majored in Computer Engineering with GPA: 3.92

• Relevant Courses: Computational Intelligence, High-Performance Computing, Data Analytics Programming, Data Science, Computer Vision

• Master’s Thesis: A Probabilistic Machine Learning Framework for Cloud Resource Selection on the Cloud [link]

- Developed multi-class Gaussian Naïve Bayes classifier for recommending cloud instance

- Tools: Linux Perf, Python, Pandas, NumPy, Scikit-learn, Matplotlib, Cloud Platforms: AWS EC2, Azure, Google Cloud Platform (GCP), Linode

Master of Science in Mechatronics 2013

University of Siegen, Siegen 57068, Germany

Bachelor of Science in Electrical and Electronics 2010 United International University (UIU), Dhaka 1212, Bangladesh Publications

D. Samuel, S. Khan, C.J. Balos, Z. Abuelhaj, A.D. Dutoi, C. Kari, D. Mueller, and V.K. Pallipuram (2020), A2Cloud-RF: A Random Forest-based Statistical Framework to guide Resource Selection for High-Performance Scientific Computing on the Cloud, 22 July 2020, Conc. and Comp.: Pract. and Exp [link]

My Contributions: insights into decision tree/forest construction, execution on the Cloud, curating data for analysis

L. Her, S. Khan, D. Samuel, X. Ai, S. Chen, and V.K. Pallipuram, A2Cloud-cc: A Machine Learning Council to Guide Resource Selection for Scientific Applications, 26-28 November 2020, 19th IEEE International Symposium on Network Computing and Applications. My Contributions: Implemented K-Means clustering for class labels generation, Applied Gaussian Naïve Bayes Classifier for Cloud instance recommendation, execution on the Cloud, curating data for analysis

Selected Projects

Neural network algorithm implementation for classifying the digit from USPS handwritten digit dataset [link]

- Implemented a neural network for handwritten digit recognition with accuracy above 88%

- Tools: MATLAB

Electricity consumer prediction based on supervised and non-supervised algorithm [link]

- Predicted electricity consumers using K-Means and KNN

- Tools: Python, Pandas, Scikit-learn, NumPy, Matplotlib Accelerating Canny Edge Detector on NVIDIA Quadro P4000 GPU using CUDA [link]

- GPU implementation of the serial code and achieved 45 times speedup versus optimized serial implementation

- Tools: C, CUDA for C, NVIDIA profiler, BASH

Technical Skills

Software Experience C/C++, Python, Pandas, NumPy, SQL, Scikit-learn, TensorFlow, Git, R, UNIX shell scripting/Bash, CUDA, MATLAB/SIMULINK

Operating System. Linux, Windows, Mac OS

Professional Developments

• An Introduction to Interactive Programming in Python, Rice University (USA) and Coursera

(https://www.coursera.org/records/cQ89yjWK7qhXpBn3)

• Become a Machine Learning Specialist, LinkedIn Learning [link]

• Applied Machine Learning: Foundations [link]

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