Emran Ali
PhD Researcher
IT @ Deakin University, Australia
CSM @ Coventry University, United Kingdom
AI | ML | DL | xAI | GenAI | Agentic AI | Health Informatics
Emran's Profile Summary
I am a research and development enthusiast in Data Analytics, Machine (Deep) Learning, Generative AI, Explainability, Interpretability and Optimisation. Experienced in applied research in: Health Informatics, Business Analytics, Automation, and Sustainable Environment.
Overview
- PhD: IT@Deakin & CSM@Coventry University - (Ongoing)
- Master's: IT(Research)@Deakin University
- Bachelor's: CSE@HSTU
- Scholarship (PhD): DUPRS, Cotutelle (Deakin & Coventry)
- Fellowship (Master's): STF, Ministry of Sci.&Tech., Bangladesh
- Industry Involvement (Research): Alfred Health & AETMOS
- Projects: ICU Seizure Detection & Air Quality Prediction
- Teaching: HSTU & (Part-time)@Deakin University
- Software Development: Sr. Dev.@DROIDBD & AAPBD
- Membership: ACS, IEEE, EMBS, DUSA, DAIS & DSEC
- Awards: (AWS AI/ML & Bertelsmann NextGen) Scholarship
- Email: emran.ali@research.deakin.edu.au
- MS Teams: wwm.emran@hotmail.com
- Website: https//www.linkedin.com/in/wwmemran
- Website: https://emran.humachlab.com
Research Area: Artificial Intelligence (AI) | Machine Learning (ML) | Deep Learning (DL) |
Generative AI (GenAI) | Agentic AI |
Interpretability* | Health Informatics* | (Bio)Signal Processing | Medical Technology (MedTech) |
Electroencephalography (EEG) | Hypnogram* |
Epilepsy | Sleep* | Aging* | Air Quality
Recent Works: Hypnogram Analysis, Sleep, Sleep Analysis, Sleep Disorder Detection, Aging, EEG
Signal Analysis, EEG Channel Optimisation, Epileptic Seizure Detection,
ML Model Interpretability, Meteorological Data Analysis, Air Quality Prediction, Realestate House
Suggestion (GenAI), Multi-Agent Research Assistant, Business Data Analysis, Education Data Analysis.
About
This is Emran.
I strive to cherish and appreciate every moment of my life.
I have a deep admiration for nature and a preference for simplicity.
I am a friendly individual with a strong passion for travel.
I am highly enthusiastic about learning new things, especially those that spark my interest.
My fascination with Machine Learning began during an early lecture that explained how both humans and
machines learn from their environment in similar ways.
Since then, exploring Machine Learning has become not only a personal passion but also an integral part
of my professional career.
I earned a 4-year Bachelor of Science (B.Sc.) degree in Computer Science and Engineering (CSE) from
Hajee Mohammad Danesh Science and Technology University (HSTU), Bangladesh, with one year of partial
research involvement.
My research focused on enhancing text-search algorithms with a practical application for smartphones.
During this period, I also completed various project-based works and actively engaged in numerous
activities, including voluntary service, technology event management, and participation in computer
programming contests.
After graduation, I worked in the software development industry in my home country for almost three
years and developed several iOS applications both independently and collaboratively.
I began my career at Kento Studios Ltd., later joined DROID Bangladesh (DROIDBD) Ltd., and eventually
worked at Advanced Apps Bangladesh (AAPBD) Ltd.
My responsibilities included software development strategies, automation, and industry-level management
tasks.
During this time, I was promoted to Senior Software Engineer and subsequently to Software Development
Manager, and I also received a Best Employee Award in recognition of my dedication and hard work.
Later, I joined HSTU as a faculty member in the Department of CSE, where I have been working for over
eight years.
I taught a variety of major CSE courses and was involved in research, academic projects, and student
supervision.
The courses I taught include major programming languages—C, C++, Java, PHP, and C#; web
technologies—HTML, CSS, PHP, MySQL; database courses—Database Systems, Oracle, MySQL; smartphone
application development; data science–related subjects such as Artificial Intelligence, Machine
Learning, and Pattern Recognition; as well as computer hardware fundamentals.
I was awarded a Science and Technology Fellowship (STF) from the Ministry of Science and Technology,
Government of the People’s Republic of Bangladesh, for higher studies in the STEM fields.
I then completed a 2-year research-based Master of Science (M.Sc.) degree in Information Technology (IT)
at Deakin University, Australia.
This program, offered by the School of IT (SIT) at the Melbourne Burwood campus, focused entirely on
research.
My master’s research primarily centred on applying machine learning and optimisation techniques to
physiological signal (biosignal) processing and disease detection, specifically analysing brain signals
(electroencephalograms—EEG) and applying machine learning methods for epileptic seizure detection.
During this period, I published several research articles and developed a Python-based feature
extraction library, which will soon be made available to the research community.
I also served as a research assistant on multiple projects.
One voluntary initiative, conducted by Deakin University in collaboration with Monash University and
Alfred Health, focused on automatic detection and prediction of epileptic seizures in ICU patients and
identifying the minimal EEG channels required for monitoring.
In another project with Monash University and AETMOS Australia (a provider of air quality monitoring and
environmental health solutions), I worked on indoor air-temperature prediction for air-quality
forecasting and examined its relationship with health implications.
I have been offered a Cotutelle (joint) Doctor of Philosophy (PhD) program at Deakin University,
Australia, in collaboration with Coventry University, United Kingdom.
My PhD research is fully funded through the Deakin University Postgraduate Research Scholarship (DUPRS).
This joint program is conducted by all participating universities and supervised by faculty members
across these institutions.
My research will focus on exploring the relationship between sleep, sleep stages, and healthy ageing.
I intend to apply interpretable machine learning models in this project, which will again involve the
analysis of physiological signals.
I continuously expand my knowledge in the latest tools and technologies related to Artificial
Intelligence (AI) and Machine Learning (ML).
I have learned and applied state-of-the-art concepts in Generative AI (GenAI) and Agentic AI in various
application areas, including AI automation.
I have also received several competitive scholarships from renowned organisations, such as the AWS AI/ML
Scholarship and the Bertelsmann Next Generation Tech Booster Scholarship, which enabled me to learn new
technologies through various courses and nanodegrees.
I possess strong management, leadership, and technical skills, with expertise in programming and data
analytics gained through extensive practice and experience.
I look forward to applying my research knowledge and development skills to create industry-grade
products and services that contribute to building a better future.
Key Information
Key information about the study, experience, research, and achievements.
Years of teaching and research experience
Years of software development experience
Projects with research contribution
Publications related to research
Institutional involvement in academic and research
Industrial involvement in research and software development
Research collaboration with institutes and industries
Specialisation Certificates for courses and training
Education
I am an enthusiastic, dedicated, and patient learner and researcher who aspires to explore and deepen my knowledge of Machine Learning and Deep Learning, particularly in their applied domains such as healthcare, automation, human–computer interaction, and the bio-sciences.
Summary
Current Status
- Doctor of Philosophy (PhD) Program
- Graduate Researcher, Higher Degree Research (HDR) at Deakin University
- Post-Graduate Research (PGR) Student at Coventry University
- Deakin–Coventry Cotutelle (Joint) Research Program.
- Application of AI, ML and DL in Health Informatics Research
- Institution-Industry Collaboration
Doctor of Philosophy (PhD)
Information Technology (IT)
Deakin University, Melbourne, Australia
Jan 2023 – Present | Full-time | 3-year program (maximum 4 years) | Ongoing
Specialisation: Applied Machine Learning (ML) and Deep Learning (DL) in
health informatics and (physiological) signal processing.
Scholarship: Deakin University Postgraduate Research Scholarship (DUPRS) –
awarded for the duration of the study at Deakin University
Research Topic: A Machine Learning-based Analysis of Sleep Patterns in
Healthy Ageing using Physiological Signals.
Activities and Involvement: Research · Development · Industry collaboration
· Student engagement via:
Australian Computer Society (ACS) · Deakin University Student Association (DUSA) · Deakin
Biomed Society (DUBS) · Deakin Software Engineering Club (DSEC) · Deakin AI Society
(DAIS)
Description:
This is a Cotutelle (joint) PhD program hosted by Deakin University (host institution),
Australia, in collaboration with Coventry University (partner institution), United Kingdom.
It is a full-time, research-based program spanning 3 years (maximum completion duration: 4
years), with a focus on, applied ML and DL with biomedical signal processing in detecting
sleep disorders.
All key milestones, including candidature confirmation, annual progress reviews, and final
thesis defense, are conducted independently by both institutions.
This project is about finding relationship between sleep pattern and different health status
(healthy or have sleep disorders) using a simpler physiological signal called Hypnogram for
assistive diagnostic.
Starting from traditional ML and ensemble ML to advanced models such as traditional DL, CNN,
RNN, graph neural networks (GNN), are applied to analyse the feasibility of a wearable sleep
monitoring system.
At Deakin, the program is conducted under the School of Information Technology (SIT),
Faculty of Science, Engineering and Built Environment (SEBE), and the research is based at
the Data Analytics and Research Lab (DARL).
Research and Projects:
Computational Science and Mathematical Modelling (CSM)
Coventry University, Coventry, United Kingdom
Jan 2023 – Present | Full-time | 3.5-year program (maximum 4 years) | Ongoing
Specialisation: Applied Machine Learning (ML) and Deep Learning (DL) in
health informatics and (physiological) signal processing.
Scholarship: Cotutelle Studentship Fund – awarded during the study period
at Coventry University
Research Topic: A Machine Learning-based Analysis of Sleep Patterns in
Healthy Ageing using Physiological Signals.
Description:
This Cotutelle (joint) PhD program is jointly administered by Deakin University (host
institution) and Coventry University (partner institution).
All key milestones, including candidature confirmation, annual progress reviews, and final
thesis defense, are conducted independently by both institutions.
The project is guided by a strong supervisory team of more than four specialists (2 from
each institutions) from Deakin University and Coventry University.
This project is about finding relationship between sleep pattern and different health status
(healthy or have sleep disorders) using a simpler physiological signal called Hypnogram for
assistive diagnostic.
Starting from traditional ML and ensemble ML to advanced models such as traditional DL, CNN,
RNN, graph neural networks (GNN), are applied to analyse the feasibility of a wearable sleep
monitoring system.
The research is carried out under the Centre for Computational Science and Mathematical
Modelling (CSM).
Research and Projects:
Master of Science (by Research) – MRes
Information Technology (IT)
Deakin University, Melbourne, Australia
Feb. 2020 – Feb. 2022 | Full-time | 2 years (maximum 3 years) | Awarded in Oct. 2022
Specialisation: Applied Machine Learning (ML) and system optimisation with
a focus on (pythological) signal processing and medical diagnostic
Fellowship: Science and Technology Fellowship (STF)
Research Topic: Minimising Scalp Electroencephalogram (EEG) Channels for
Epileptic Seizure Detection
Activities and Involvements: Research · Development · Industry
collaboration · Student engagement through Deakin University Student Association (DUSA)
Description:
This is a full-time, research-only program delivered under the School of Information
Technology (SIT), within the Faculty of Science, Engineering, and Built Environment (SEBE).
The research is conducted under the Data to Intelligence (D2I) Research Centre, focusing on
biomedical engineering, signal processing, and Machine Learning (ML).
The project focused on various aspects epileptic seizure detectino using EEG signal,
especiall, EEG channel minimisation.
Thesis: Minimising Electroencephalogram Channels for Epileptic Seizure
Detection — length over 50,000 words.
Research and Projects:
- Channel Minimisation for Epileptic Seizure Detection and Prediction using Signal Processing and Machine Learning on Surface EEG Data.
- Epileptic Seizure Detection using Single-channel Deep Learning Models on Continuous EEG Recordings from ICU Patients (A collaborative work with Monash University and Alfred Health).
- Air Quality (Indoor Temperature) Prediction Based on Meteorological and Indoor Sensor Data (A MAAP Linkage ARC Project Funded by the Australian Research Council (ARC), and a Collaborative Work with Monash University and Sensor Industry AETMOS Australia).
Bachelor of Science (B.Sc.)
Computer Science and Engineering (CSE)
Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur, Bangladesh
Jan. 2007 – Dec. 2010 | Full-time | 4-year | Awarded in Apr. 2012
Research Topic: Advanced string search algorithms using indexed binary
search for a J2ME-based English-to-English dictionary application.
Activities and Involvements: Academic coursework · Research ·
Software/Application development · Competitive programming · Active member of the
programming community — Programmers Arena
Description:
This is a full-time undergraduate program offered by the Department of Computer Science and
Engineering (CSE), under the Faculty of Computer Science and Engineering. The curriculum
spans a broad range of computer science and engineering topics including:
mathematics, physics, statistics, computer programming (C, C++, Java, PHP, etc.), database
systems, artificial intelligence, machine learning, software engineering, system
architecture, and microprocessor systems.
A mandatory final-year thesis/project is required for program completion.
Thesis: J2ME English-to-English Dictionary with Indexed Binary Search —
length approximately 9,500 words
Research and Projects:
Professional Experiences
I am a dedicated and quick-learning professional with proven expertise in both industry and academia. My unique background enables me to bridge the gap between academic research and practical industrial applications through extensive hands-on experience in research and development. I bring over 3 years of experience in software development and project management, alongside approximately 12 years of academic engagement, including research, teaching, and industry collaboration. My journey reflects a deep passion for innovation, solution-driven thinking, and interdisciplinary integration. I am particularly enthusiastic about advancing health informatics through the development of AI- and ML-based methods, devices, and applications, with a focus on optimisation, real-world impact, and scientific rigour.
Summary
Areas of Expertise
- Teaching and Training
- Application of AI, ML and DL
- Applied Research in Health Informatics, Business Analytics, System Automation & Sustainable Environment
- Industries-Academia Collaboration
- Software Development, Team Management & Project Management
Research Interests
- Data Science
- Machine (Deep) Learning
- Generative AI and Agentic AI
- Interpretability
- Optimisation
- Biomedical Science
- Health Informatics
- Disease Detection and Prediction
- Time series Data Analysis
- Biosignal Analysis
- Hypnogram EEG and Brain Signal Analysis
- Epilepsy
- Sleep*
- Aging*
- Air Quality
Research Experiences
Deakin University
Deakin University, Melbourne, Australia
Graduate Researcher (PhD Student)
Jan. 2023 – Present | Full-time | 3 years
Description:
- Sleep disorder detection using Hypnogram
- Efficacy of sleep dynamics for sleep disorder detection
- Analysis of age in sleep analysis
- Impact of noise in Hypnogram in sleep analysis
Responsibilities:
- Studying research methodology and strategy
- Conducting experiments and evaluations
- Preparing documentation and publishing articles
Related Skills: Research · Health Informatics · Machine Learning · Deep Learning · Biomedical Sciences · Signal Processing · Data Science · Data Analysis · Deep Learning · Python (Programming Language) · Biomedical Engineering · LaTeX · Programming · Algorithms · GitHub
Research Assistant
Oct. 2024 – Nov. 2024, Oct. 2023 – Dec. 2023 | Casual/Contract | 2+3 months
Description:
- Feasibility analysis of Generative AI solutions for ECG-based heart disease detection
- Security analysis and risk assessment for agentic AI-based healthcare platforms
Responsibilities:
- Studying research methodology and strategy
- Conducting experiments and evaluations
- Preparing documentation and publishing articles
Related Skills: Research · Health Informatics · Machine Learning · Deep Learning · Biomedical Sciences · Signal Processing · Data Science · Data Analysis · Deep Learning · Python (Programming Language) · Biomedical Engineering · LaTeX · Programming · Algorithms · GitHub
Graduate Researcher (MRes Student)
Feb. 2020 – Oct. 2022 | Full-time | ~2.75 years
Description:
- Epileptic seizure detection using EEG
- Seizure detection using single and multi-channel EEG
- Factors influencing a real-world seizure detection system
- EEG channel minimisation for seizure detection
Responsibilities:
- Studying research methodology and strategy
- Conducting experiments and evaluations
- Preparing documentation and publishing articles
Related Skills: Research · Health Informatics · Machine Learning · Biomedical Sciences · Signal Processing · Data Science · Data Analysis · Deep Learning · Python (Programming Language) · Biomedical Engineering · LaTeX · Programming · Algorithms · GitHub
Research Assistant
Aug. 2020 – Sep. 2022 | Casual/Contract | 2 years
Description:
- Research collaboration with Alfred hospital for real-world healthcare application
- Epileptic seizure detection in critical setting of ICU
Responsibilities:
- Research and collaboration with Monash University and Alfred Health in the initial design of a seizure detection system for ICU patients.
- Data pre-processing and result post-processing.
- ML and DL model evaluation, testing, and visualisation.
- Worked as an official (funded) employee from Aug 2021 to Dec 2021 and the rest of the period as a volunteer.
Related Skills: Research · Health Informatics · Machine Learning · Biomedical Sciences · Signal Processing · Data Science · Data Analysis · Deep Learning · Python (Programming Language) · Biomedical Engineering · LaTeX · Programming · Algorithms · GitHub
Research Assistant
Mar. 2022 – Sep. 2022 | Casual/Contract | approximately 2.5 years
Description:
- Research collaboration with AETMOS for real-world sustainable environment application
- Air quality and air temperature prediction for indoor settings
Responsibilities:
- A MAAP linkage ARC project funded by the Australian Research Council (ARC).
- Research and collaboration with Monash University and AETMOS (https://aetmos.com.au/) for Air Quality Prediction.
- Air Quality and Indoor Air Temperature Prediction from meteorological and traffic data.
- Effect of indoor and outdoor temperature on people's health.
- Application of Deep Learning (DL).
Related Skills: Research · Machine Learning · Signal Processing · Data Science · Data Analysis · Deep Learning · Python (Programming Language) · LaTeX · Programming · GitHub · Project Management
Hajee Mohammad Danesh Science and Technology University (HSTU)
HSTU, Dinajpur, Bangladesh
Research Supervisor
Sep. 2014 – Jan. 2025 | Full-time | ~12 years
Responsibilities:
- Research conduction.
- Research supervision of undergraduate students.
Related Skills: Research · Machine Learning · Programming · Algorithms · Teaching · OOP · Database Design · Educational Technology · C · C++ · Java · University Teaching · Public Speaking · Programming Languages
Training Experiences
Intersect Australia
Sydney, Australia
Digital Research Trainer
Mar. 2023 – Present | Casual/Contract | ~3 years
Responsibilities:
- Training the researchers.
- Training assistance.
- Training content creation and modification.
- PYTHON101: Introduction to Programming: Python
- PYTHON203: Data Manipulation and Visualisation
- PYTHON205: Introduction to Machine Learning: Regression
- PYTHON206: Introduction to Machine Learning: Classification
- PYTHON207: Introduction to Machine Learning: Unsupervised Learning
Related Skills: Programming · Machine Learning · Data Science · Deep Learning · Python (Programming Language) · Teaching · Database Design · Training · Assistance · Demonstration
Teaching Experiences
Deakin University
Deakin University, Melbourne, Australia
Graduate Reserach Teaching Fellow (GRTF)
Feb. 2025 – Present | Part-time/Contract | ~1 years
Responsibilities:
- Course (sessional) assistance.
- Assistance in examination process and evaluation.
- MIS140-Introduction to Machine Learning || Python, ML, AI || T2-2025
- SIT107+SIT720-Machine Learning || Python, ML, AI || T1-2025
- SIT719-Analytics for Security and Privacy || Linux, Computer Security, Security Analytics || T1-2025
- SIT103+SIT772-Database Fundamentals || Database Management, SQL || T1-2025
Related Skills: Machine Learning · Data Science · Deep Learning · Python (Programming Language) · Programming · Security · Computer Security · Data Security · Database · SQL · Teaching · Database Design · Educational Technology · University Teaching
Sessional Academic Staff
Mar. 2020 – Present | Casual/Contract | ~5 years
Responsibilities:
- Course assistance.
- Assistance in examination process and evaluation.
- Assistance in student HelpHub.
- SIT107+SIT720-Machine Learning || Python, ML, AI || T2-2020, T2-2021, T1-2022, T2-2022, T2-2023, T2-2024
- MIS781-Business Intelligence and Database || Database, SQL, Power BI || T1-2023
- MIS710-Machine Learning in Business || Python, ML, Business use case analysis: || T2-2023, T1-2024, T2-2024, T1-2025
- MIS384-Marketing Analytics || Database, SQL, BigQuery, GCP || T1-2024
- Other miscellaneous courses: Database, Computer programming (C, C++, C#)
Related Skills: Machine Learning · Data Science · Deep Learning · Python (Programming Language) · Programming · Teaching · Database Design · Educational Technology · University Teaching
Hajee Mohammad Danesh Science and Technology University (HSTU)
HSTU, Dinajpur, Bangladesh
Assistant Professor
Sep. 2017 – Present | Full-time | ~9 years
Responsibilities:
- Course (theory and sessional) conduction, examination process and evaluation.
- Research conduction and supervision.
- Currently on leave for higher studies since February 2020.
Related Skills: Research · Machine Learning · Programming · Algorithms · Teaching · OOP · Database Design · Educational Technology · C · C++ · Java · University Teaching · Public Speaking · Programming Languages
Lecturer
Sep. 2014 – Aug. 2017 | Full-time | 3 years
Responsibilities:
- Course (theory and sessional) conduction, examination process and evaluation.
- Research conduction and supervision.
Related Skills: Research · Machine Learning · Programming · Algorithms · Teaching · OOP · Database Design · Educational Technology · C · C++ · Java · University Teaching · Public Speaking · Programming Languages
Industrial (Software Development) Experiences
Advanced Apps Bangladesh (AAPBD) Ltd.
AAPBD, Dhaka, Bangladesh
Project Development Manager & Senior Software Engineer
Jan. 2014 – Aug. 2014 | Full-time | 8 months
Responsibilities:
- AAPBD previously was DROIDBD, and currently working as AppBajar and The Borak.
- Project Management: Project management, app design, app testing, and client management.
- Involved in the development of more than 50 apps.
- iOS application design, development, implementation, testing and instructing new members.
- Other platforms: Android apps, web apps using PHP, MySQL, JS etc
Related Skills: Programming · Algorithms · iOS Development · Swift (Programming Language) · Xcode · GitHub · Software Engineering · Mobile Applications · Android Development · Software Project Management · Project Management · Software Design · Web Services · OOP · iOS · Objective-C · iOS Application Development
Droid Bangladesh (DROIDBD) Ltd.
DROIDBD, Dhaka, Bangladesh
Senior Software Engineer
May. 2012 – Dec. 2013 | Full-time | 1.75 years
Responsibilities:
- iOS application design
- iOS application development & implementation
- iOS application testing
- iOS application training new members
Related Skills: Programming · Algorithms · iOS Development · Xcode · GitHub · Software Engineering · Mobile Applications · Software Design · Web Services · OOP · iOS · Objective-C · iOS Application Development
Kento Studios Ltd.
Kento Studios, Dhaka, Bangladesh
Programmer
Feb. 2012 – May. 2012 | Full-time | 4 months
Responsibilities:
- iOS application design
- iOS application development
- iOS application testing
- iOS Game design
Related Skills: Programming · Algorithms · iOS Development · Xcode · GitHub · Software Engineering · Mobile Applications · Software Design · Web Services · OOP · iOS · Objective-C · iOS Application Development
Expertise, Skills and Achievements
A consolidated overview of expertise, skills, and achievements acquired through academic and professional experience.
Skills and Tools
Through self-assessment and practical experience, I am proficient in modern data analytics tools, machine learning frameworks, and essential soft skills.
Bertelsmann Next Generation Tech Booster Scholarship
Next Generation Tech Booster Scholarship (Phase 1) from Bertelsmann for a Udacity Nanodegree program, valued over $1,500 · Oct 2024
AWS AI/ML Scholarship
AWS AI/ML Scholarships (Phases 1 & 2) to pursue two Udacity Nanodegree programs valued at over $8,000 · Feb 2024 & Oct 2023
Cotutelle Studentship
Cotutelle (joint) Studentship as part of the joint doctoral program at Deakin and Coventry University · (Ongoing)
DUPR Scholarship
Fullly funded DUPR Scholarship for Joint PhD research at Deakin and Coventry University · (Ongoing)
Best Presentation Award
Annual School Conference - School of IT, Deakin University · Dec 2021
Science and Technology Fellowship (STF)
Fully funded fellowship for higher education - STF Trust, Ministry of Science and Technology, Bangladesh · Feb 2020
Best Employee Award
Best employee of year 2014 - Advanced Apps Bangladesh (AAPBD) Ltd., Bangladesh · Jul 2014
Country Topper (Bangladesh)
Post-graduation Entrance Exam - South Asian University (SAU), New Dehli, India · Apr 2013
Undergraduate Department Topper
First Place from the undergrad batch (CSE) - HSTU, Bangladesh · Mar 2012
InUPC Champion
Intra-University Programming Contest (InUPC) Champion - HSTU, Bangladesh · Feb 2009
Courses, Trainings and Certificates
A curated list of all completed courses, training programs, bootcamps, conferences, and earned certificates.
- All
- Certificate
- Training
- Course
- Conference
- Bootcamp
Researcher
Project: A MACHINE LEARNING BASED ANALYSIS OF SLEEP PATTERNS IN AGING
USING
PHYSIOLOGICAL SIGNALS.
Funding: Centre for Computational Science and Mathematical Modelling
(CSM), Coventry University, United Kingdom. (Jan. 2023 - Ongoing).
Research Assistant
Project: Air Quality Prediction (Temperature Prediction) for Indoor
Environments in
Different Cities of Australia.
Funding: An MAAP linkage project funded by the Australian Research
Council (ARC).
(Mar. 2022 - Dec. 2022).
Research Assistant
Project: Channel minimisation and epileptic seizure detection using
single channels
using Deep Learning from continuous iEEG of ICU patients.
Funding: A voluntary collaboration of Deakin University, Monash
University and Alfred
Health. (Apr. 2020 - Mar. 2022) - (Status: initial phase completed).
Project Research Associate
Project: DESIGNING A 3-LAYER NETWORK SECURITY TECHNIQUE IN SERVERS FOR
PREVENTION OF
DDOS ATTACK.
Funding: Institute of Research and Technology (IRT), HSTU. (Jul. 2018 -
Jun. 2019).
Project Research Associate
Project: ANALYSIS AND DESIGN OF A NON-INVASIVE WAY OF MEASURING AND
MONITORING
BLOOD-SODIUM CONCENTRATION LEVEL USING NEAR-INFRARED SPECTROSCOPY.
Funding: Institute of Research and Technology (IRT), HSTU. (Jul. 2018 -
Jun. 2019).
Memberships
Memberships held as a student and professional, including voluntary and organisational affiliations.
ACS Associate Member
Australian Computer Society (ACS) · Aug. 2023 - Dec. 2024
DUSA Member
Deakin University Student Association (DUSA) - Deakin University · Apr. 2020 - Dec. 2023
DSEC Member
Deakin University Software Engineering Club (DSEC) - Deakin University · Jan. 2023 - Dec. 2023
DAIS Member
Deakin AI Society (DAIS) - Deakin University · Jan. 2023 - Dec. 2023
IEEE Student Member
Institute of Electrical and Electronics Engineers (IEEE) - IEEE · Jan. 2022 - Dec. 2023
EMBS Student Member
IEEE Engineering in Medicine and Biology Society (EMBS) - IEEE · Jan. 2022 - Dec. 2023
IEEE Young Professionals
Institute of Electrical and Electronics Engineers (IEEE) - IEEE · Jan. 2022 - Dec. 2023
Advisor and Founding Member
Programmers Arena - HSTU · Sep. 2014 - Present
Advisor
CSE Club - HSTU · Sep. 2014 - Present
Seminar Speaker
Presented a talk at a seminar on Higher Studies in Abroad - Journey to Australia and Research Experiences, Organized by CSE Club, HSTU on Sep. 2022
Keynote Speaker
Delivered a keynote at a seminar on career development and the future of mobile app development in Bangladesh, Organized by AFCSE, HSTU on Apr. 2015
Bengali
Native language · Excellent proficiency in Listening, Reading, Writing, and Speaking (LRWS).
English
Professional level - Medium of instruction at HSTU and Deakin University · IELTS (6.5) - LRWS (6.0,6.5,6.5,7.0) - 2019.
Spanish
Beginner-level self-learner with foundational vocabulary and expressions.
Portfolios
Publicly available GitHub repositories demonstrating projects with my core contributions.
DIHC_Downloader |
A fully Python-based utility library to recursively download the contents from a web directory including subdirectories and files.
DIHC_FeatureManager |
A python (and Matlab) based library for advanced feature extraction and feature engineering related task for Machine Learning.
AWS_Udacity_AIML_Scholarship_Program |
A python Machine Learning and Deep Learning repository containing all the projects completed in AWS AI/ML Scholarship (Phase 1 and 2) programs. It contains a collection of 6 end-to-end projects from 2 Udacity nanodegree.
Section Leader - Code in Place (CIP)
Facilitated student learning in Python through Stanford's global volunteer-driven Code in Place program · Stanford Online · Apr 2023 - Apr 2024
Scientific Journal Reviewer
Actively involved in peer-review of scientific manuscripts for journals affiliated with EAMBES · European Alliance of Medical and Biological Engineering and Science (EAMBES) · Aug 2023 - Present
Publications
All the publications (reports and articles) in journal, conference, poster, symposium, blog, etc.
Journals
Epileptic seizure detection using CHB-MIT dataset: The overlooked perspectives
DOI/Link: 10.1098/rsos.230601
Sensor-based indoor air temperature prediction using deep ensemble machine learning: An Australian urban environment case study
DOI/Link: 10.1016/j.uclim.2023.101599
A LSB Based Image Steganography Using Random Pixel and Bit Selection for High Payload
DOI/Link: 10.5815/ijmsc.2021.03.03
Enhancement of single-handed Bengali sign language recognition based on HOG features
DOI/Link: http://www.jatit.org/
Mapping Character Position Based Cryptographic algorithm with Numerical Conversions
DOI/Link: https://ijcsse.org/
Pseudo random ternary sequence and its autocorrelation property over finite field
DOI/Link: 10.5815/ijcnis.2017.09.07
Smart Campus Using IoT with Bangladesh Perspective: A Possibility and Limitation
DOI/Link: 10.22214/IJRASET.2017.8239
Study of Abstractive Text Summarisation Techniques
DOI/Link: https://www.ajer.org/
Conferences
An Efficient Feature Optimisation Approach with Machine Learning for Detection of Major Depressive Disorder Using EEG Signal
Optimal Feature Identification and Major Depressive Disorder Prediction through Correlation-Based Machine Learning Approach
Performance Analysis of Entropy Methods in Detecting Epileptic Seizure from Surface Electroencephalograms
DOI/Link: 10.1109/EMBC46164.2021.9629538
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