Abdullah Aman Tutul

Texas A&M Univeristy, College Station

I am a graduate student and Research Assistant at the Department of CSE, at Texas A&M Univeristy, College Station advised by Dr. Theodora Chaspari, Assistant Professor, Texas A&M Univeristy. My research interest lies in trust factors of explainable AI and machine learning.

Research Experience

Jan 2021 - Present

Exploring trust in human-AI collaboration for speech-based data analytics task and building up an AI-assisted decision making frame work for detecting public speaking anxiety under supervision of Dr. Theodora Chaspari, Assistant Professor, Texas A&M Univeristy.

Sept 2021 - Present

Building robust machine learning models to track parent-child well-being from ambulatory data in collaboration with University of Southern California, Florida International University and Texas A&M University.

Sept 2021 - Present

Building bio-behaviorally aware adaptive training system for space-craft cost estimation in collaboration with Department of Aerospace Engineering, Texas A&M University.

June 2019 - 2020

Developed a machine learning model to detect people with Parkinson’s disease using brain signals under supervision of Dr. A. B. M. Alim Al Islam, Professor, Bangladesh University of Engineering and Technology

Oct 2018 - 2020

Detection and Correction of batch effect using machine learning under supervision of Dr. Md. Shamsuzzoha Bayzid, Assistant Professor, Bangladesh University of Engineering and Technology and Dr. Mahfuza Sharmin, PostDoctoral Research fellow, Stanford University.

April 2018 - 2019

Developed a novel lossless compression algorithm based on the heuristics of naive bayes theorem to compress multiple sequence aligned files under supervision of Dr. Md. Shamsuzzoha Bayzid


Published Papers

Abdullah Aman Tutul, Ehsanul Haque Nirjhar, Theodora Chaspari.
Investigating Trust in Human-Machine Learning Collaboration: A Pilot Study on Estimating Public Anxiety from Speech.
ICMI’21: Proceedings of the 2021 International Conference on Multimodal Interaction, October 2021(Acceptance rate 30%), Pages 288-296


Md Ashiqur Rahman, Abdullah Aman Tutul, A. B. M. Alim Al Islam
Solving The Maze of Diagnosing Parkinson’s Disease based on Portable EEG sensing to be Adaptable to Go In-The-Wild.
7th NSysS 2020 7th International Conference on Networking, Systems and Security, December 2020,(Acceptance rate 27%), Pages 63-67,(Best Paper Award)

Md Ashiqur Rahman, Abdullah Aman Tutul, Sifat Md Abdullah, Md. Shamsuzzoha Bayzid
CHAPAO: likelihood and hierarchical reference based representation of biomolecular sequences and applications to compressing multiple sequence alignments.
PLOS ONE 2022

Md Ashiqur Rahman, Abdullah Aman Tutul, Mahfuza Sharmin, Md. Shamsuzzoha Bayzid
BEENE: Deep Learning based Nonlinear Embedding Improves Batch Effect Estimation.
Bioinformatics 2023

Abdullah Aman Tutul, Theodora Chaspari, Sarah Ita Levitan, Julia Hirschberg
Human-AI Collaboration for the Detection of Deceptive Speech.
ACII LBR (Affective Computing + Intelligent Interaction Late Breaking Results) 2023

Submitted Papers

Abdullah Aman Tutul, Ehsanul Haque Nirjhar, Theodora Chaspari.
Investigating Trust in Human-AI Collaboration for a Speech-based Data Analytics Task.
Taylor & Francis, International Journal of Human-Computer Interaction 2023


Education

Texas A&M Univeristy, College Station

Graduate Student
Subject: Computer Science and Engineering (CSE)

Current CGPA: 4.00/4.00
Courses Taken: Analysis of Algorithms, Deep Learning, Machine Learning, Data Visualization, Software Engineering, Computer Architecture, Natural Language Processing, Pattern Analysis

January 2021 - Present

Bangladesh University of Engineering and Technology (BUET)

Obtained Degree: B.Sc. Engg
Subject: Computer Science and Engineering (CSE)

CGPA: 3.94/4.00

February 2015 - April 2019

Professional Experience

Amazon, Pittsburgh

Position:L5 Applied Scientist Intern, Alexa Speech

Role: Developed a contextual biasing model for few shot hot fixing in Automatic Speech Recognition.

May 2022 - August 2022

United Internation Univeristy

Position:Lecturer, Dept of Computer Science and Engineering (CSE)

Courses Instructed: Database Management System Theory, Database Management System Lab, Numerical Methods, Digital Logic Design Lab, Advanced Programming Lab, Theory of Computation, Digital System Design Lab, Assembly Language Programming Lab, Object Oriented Programming Lab

June 2019 - Dec 2020

Skills

  • Languages: Python, C, C++, Java, Intel 8086 Assembly Language, Turbo Asssembler, Bash, HTML, PHP, SQL.
  • Frameworks: Android Studio, PyTorch, Tensorflow, Django, Keras, IGraphics.
  • Hardware Tools: Adruino, NeuroSky Mindwave.
  • Database: Oracle SQL, MySQL, PostgreSQL, Cassandra, Firebase
  • Design Tools: Proteus circuit simulator, Logisim, AutoCAD and CISCO packet tracer.

Notable Projects

  • Image Classification: A deep learning model using advanced augmentation policy along with Wide Resnet which outperformed the performance of Wide ResNet on CIFAR 10 dataset. I have also evaluated different machine learning models to classify leukemic B-lymphoblast cells from normal B-lymphoid precursors from blood smear microscopic images.(github link)
  • Travel Book: A travelling software built with android studio, Firebase database, Maps API with many advanced features.(github link)
  • Smart Car Assistant: A hardware project using raspberry pi 2, python open cv, camera module which will track head orientation and eye gaze of drivers and detect whether they are inattentive to driving.(github link)
  • Online Multiplayer Game:It was built using java and socket programming. Here, a player can attack other player with blasting bombs or can get attacked by enemies.(github link)
  • Balloon Shooter:An arrow shooter game was built using 8086 assembler along with turbo GUI v3.(github link)

Skills

 
Technical Skills
  • Languages: Python, C, C++, Java, Intel 8086 Assembly Language, Turbo Asssembler.
  • Scripting Language: Bash, HTML, CSS, PHP, LATEX, SQL.
  • Frameworks: Android Studio, PyTorch, Django, Keras, IGraphics.
  • Hardware Tools: Adruino, NeuroSky Mindwave.
  • Database: Oracle SQL, MySQL, PostgreSQL, Cassandra, Firebase
  • Design Tools: Proteus circuit simulator, Logisim, AutoCAD and CISCO packet tracer.

Achievements

  • Best Paper: 7th NSysS 2020 7th International Conference on Networking, Systems and Security, December 2020,(Acceptance rate 27%)
  • Dean's List Buet: 2016, 2017, 2018, 2019
  • University Merit Scholarship Buet: 2016, 2017, 2018, 2019

Contact

Email

  • abdullahaman633@tamu.edu
  • abdullahaman633@gmail.com