Omar Sharif

Omar Sharif

Graduate student at Dartmouth CS, advised by Prof. Sarah M. Preum. Interested to apply deep learning to understand natural language.

Education

Dartmouth College
PhD in Computer Science
Study Period: September 2022 - Ongoing
Supervisor: Prof. Sarah M. Preum Lab: Persist Lab

Chittagong University of Engineering and Technology (CUET)
Masters in Computer Science and Engineering
Study Period: August 2019 - January 2022
Supervisor: Prof. Moshiul Hoque Lab: CUET NLP

Chittagong University of Engineering and Technology (CUET)
Bachelors in Computer Science and Engineering
Study Period: March 2014 - November 2018
Supervisor: Prof. Moshiul Hoque

Academic Appointments

Graduate Research/Teaching Assistant [Sep 2022 - Ongoing]
Departmet of Computer Science, Dartmouth College

Assistant Professor (on leave) [July 2022 - Aug 2022]
Departmet of Computer Science and Engineering, CUET

Lecturer [July 2019 - June 2022]
Department of Computer Science and Engineering, CUET

Research Assistant [Dec 2018 - June 2019]
CUET NLP Lab

Certifications

Deep Learning Specialization
[Deep Learning] [DL Notes] (Coursera)

  • Get the foundations of deep learning and learn about CNN, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization and other hyper-parameter optimization techniques which help me to build successful deep learning projects.
  • Implement different case studies on autonomous driving, sign language reading, music generation, and natural language processing using tensorflow and python.

DeepLearning.AI TensorFlow Developer Specialization
[TensorFlow] (Coursera)

  • Built basic neural network, GRUs, LSTMs using tensorflow and get profound implementation knowledge of tensorflow.
  • Learned how to improve network performance using convolutions, how to teach machines to understand, analyze, and respond to human speech with natural language processing systems.

Natural Language Processing Specialization
[Enrolled]

  • Will learn about recurrent neural networks, LSTMs, GRUs & Siamese network in TensorFlow & Trax for sentiment analysis, text generation & named entity recognition.
  • Will apply encoder-decoder & self-attention to machine translate complete sentences, summarize text, build chatbots & question-answering.