From 0f4dc9d4a7f0fedbf803171ae7b2e02d4271d21e Mon Sep 17 00:00:00 2001 From: Azmine Toushik Wasi Date: Fri, 11 Oct 2024 18:20:06 +0600 Subject: [PATCH] Wings information added --- research.html | 6 + team.html | 10 +- wings/AML.html | 188 ++++++++++++++++++++++++++++++ wings/BNLP.html | 293 +++++++++++++++++++++++++++++++++++++++++++++++ wings/DTP.html | 180 +++++++++++++++++++++++++++++ wings/HMAI.html | 202 ++++++++++++++++++++++++++++++++ wings/MedAI.html | 173 ++++++++++++++++++++++++++++ wings/OR_ML.html | 252 ++++++++++++++++++++++++++++++++++++++++ wings/index.html | 173 ++++++++++++++++++++++++++++ 9 files changed, 1472 insertions(+), 5 deletions(-) create mode 100644 wings/AML.html create mode 100644 wings/BNLP.html create mode 100644 wings/DTP.html create mode 100644 wings/HMAI.html create mode 100644 wings/MedAI.html create mode 100644 wings/OR_ML.html create mode 100644 wings/index.html diff --git a/research.html b/research.html index 4d5a0be..fa79336 100644 --- a/research.html +++ b/research.html @@ -15,6 +15,12 @@ content="black-translucent" /> + + + + + + diff --git a/team.html b/team.html index ee1d26c..065fbe8 100644 --- a/team.html +++ b/team.html @@ -187,7 +187,7 @@

Abdur Rahman

IPE, SUST
- AML, BNLP + AML, BNLP, OR+ML

@@ -220,14 +220,14 @@

Ikramul Haque Iban

IPE, SUST
- AML + AML, DTP

Siddhant Gupta

Siddhant Gupta

IE, IIT Roorkee
- BNLP, OR+ML + BNLP

@@ -249,14 +249,14 @@

Arnab Laskar

IPE, SUST
- AML + OR+ML, AML

Sahedul Mustaquim

Sahedul Mustaquim

IPE, SUST
- AML + OR+ML, AML

diff --git a/wings/AML.html b/wings/AML.html new file mode 100644 index 0000000..7e30938 --- /dev/null +++ b/wings/AML.html @@ -0,0 +1,188 @@ + + + + + + + + + + + + ⚙️ Applied Machine Learning (AML) Wing< | Computational Intelligence and Operations Laboratory (CIOL) + + + + + + + + + + + +
+

⚙️ Applied Machine Learning (AML) Wing

+
+

+ The AML wing focuses on using the power of machine learning to address real-world challenges within the Industrial and Production Engineering (IPE) domain. We specialize in a wide range of techniques, empowering us to analyze complex industrial data and develop innovative solutions that drive efficiency and optimization. +
Our goal : +

    +
  • Apply statistical and traditional machine learning methods to tackle diverse industrial challenges.
    • +
  • Utilize deep learning to analyze image, video, and sensor data for predictive maintenance and quality control.
    • +
  • Develop advanced forecasting models to predict trends in production, supply chains, and demand, facilitating proactive decision-making.
    • +
+

+ + +

Team Members

+
+


+ + +
+ +
+ A M M Mukaddes +

Dr. Abul Mukid Md. Mukaddes

+

Professor of IPE, SUST +

+
+ +
+ Mahathir Mohammad Bappy +

Mahathir Mohammad Bappy

+

Assistant Professor, LSU +

+
+
+ Manjurul Ahsan +

Md Manjurul Ahsan

+

Research Assistant Professor, OU +

+
+
+ Md Asif Bin Syed +

Md Asif Bin Syed

+

SCM Analyst, The Home Depot +

+
+
+ +
+ +
+ MD Shafiqul Islam +

MD Shafiqul Islam

+

IPE, SUST +

+
+
+ Azmine Toushik Wasi +

Azmine Toushik Wasi

+

IPE, SUST +

+
+ +
+ Abdur Rahman +

Abdur Rahman

+

IPE, SUST +

+
+ +
+ Mahfuz Ahmed Anik +

Mahfuz Ahmed Anik

+

IPE, SUST +

+
+
+ +
+ +
+ Ikramul Haque Iban +

Ikramul Haque Iban

+

IPE, SUST +

+
+
+ Arnab Laskar +

Arnab Laskar

+

IPE, SUST +

+
+
+ Sahedul Mustaquim +

Sahedul Mustaquim

+

IPE, SUST +

+
+ +
+ Minhaz Chowdhury +

Minhaz Chowdhury

+

PME, SUST +

+
+
+ + + + + + +
+ + + +







+ + diff --git a/wings/BNLP.html b/wings/BNLP.html new file mode 100644 index 0000000..9cb46e7 --- /dev/null +++ b/wings/BNLP.html @@ -0,0 +1,293 @@ + + + + + + + + + + + + 🔠 Bangla Language and NLP (BNLP) Wing | Computational Intelligence and Operations Laboratory (CIOL) + + + + + + + + + + + +
+

🔠 Bangla Language and NLP (BNLP) Wing

+
+

+ + In our IPE curriculum, the dept. offer various courses spanning ergonomics, human factors engineering, behavior studies, psychology, and more. We've identified a considerable opportunity for multidisciplinary research by integrating these disciplines with AI or computer-related domains, particularly in HCI with AI. Surprisingly, there has been limited activity in this field in Bangladesh. Given the rapid growth of human-computer interaction (HCI), we have collectively decided to explore and advance in this area with AI. +
Our works are focused on: +

    +
  • Developing and Evaluating Human-AI Interaction Systems
    • +
  • Developing Human Machine/Robotics Interaction Systems
    • +
  • Evaluating Computer Human Interaction Systems
    • +
  • Exploring AI-assisted HMI/HCI/CHI Systems
    • +
  • Ergonomics, Safety and Bias in Interaction Systems
    • +
+

+ + +

Team Members

+
+


+ + +
+
+ Raima Islam +

Raima Islam

+

MS (CSE), Harvard University +

+
+
+ Azmine Toushik Wasi +

Azmine Toushik Wasi

+

IPE, SUST +

+
+ +
+ Rafia Islam +

Mst. Rafia Islam

+

Law, IUB +

+
+
+
+ + + +
+ Sheikh Ayatur Rahman +

Sheikh Ayatur Rahman

+

CSE, BRACU +

+
+
+ Wahid Faisal +

Wahid Faisal

+

IPE, SUST +

+
+ +
+ Siddhant Gupta +

Siddhant Gupta

+

IE, IIT Roorkee +

+
+ +
+ Taj Ahmad Turjo +

Taj Ahmad Turjo

+

IPE, SUST +

+
+ +
+ + +

Publications

+
+ +
+
    + +
  1. Explainable Identification of Hate Speech towards Islam using Graph Neural Networks +
    + Azmine Toushik Wasi +
    + EMNLP'24 NLP for Positive Impact Workshop ▪ + NeurIPS'23 Muslims in ML Workshop ▪ + Accepted ▪ + Oral ▪ + GNN ▪ + XAI +
    + [arXiv] ▪ + [OpenReview] +
    +

    +
    2. + +
  2. + HRGraph: Leveraging LLMs for HR Data Knowledge Graphs with Information Propagation-based Job Recommendation +
    + Azmine Toushik Wasi +
    + ACL'24 Knowledge Graphs and LLM Workshop ▪ + Accepted ▪ + GNN ▪ + KG
    + [ACL Anthology] + [Video] +
    +

    +
    3. + +
  3. + RoBERTa Ensemble for Identifying Children’s Medical Disorders in English Tweets +
    + Azmine Toushik Wasi, Sheikh Ayatur Rahman +
    + ACL'24 Social Media for Health Workshop ▪ + Accepted ▪ + NLP
    + [ACL Anthology] +
    +

    +
    4. + +
  4. + Analyzing Social Anxiety Effects through Context-Aware Transfer Learning on Reddit Data +
    + Sheikh Ayatur Rahman, Azmine Toushik Wasi +
    + ACL'24 Social Media for Health Workshop ▪ + Accepted ▪ + NLP
    + [ACL Anthology] +
    +

    +
    5. + + + + + +
  5. + Exploring Large Language Model Systems Design Perspective Using Cognitive Ergonomics +
    + Azmine Toushik Wasi +
    + ICML'24 LLMs and Cognition Workshop ▪ + Accepted ▪ + HCI ▪ + HMAI
    + [arXiv] +
    +

    +
    6. + +
  6. + Exploring Bengali Religious Dialect Biases in Large Language Models with Evaluation Perspectives +
    + Azmine Toushik Wasi, Raima Islam, Mst Rafia Islam, Taki Hasan Rafi, Dong-Kyu Chae +
    + CHI'24 HEAL Workshop ▪ + Accepted ▪ + HCI ▪ + HMAI
    + [arXiv] +
    +

    +
    7. + +
  7. + LLMs as Writing Assistants: Exploring Perspectives on Sense of Ownership and Reasoning +
    + Azmine Toushik Wasi, Mst Rafia Islam, Raima Islam +
    + CHI'24 In2Writing Workshop ▪ + Accepted ▪ + HCI ▪ + HMAI
    + [arXiv] +
    +

    +
    8. + +
  8. + Ink and Individuality: Crafting a Personalised Narrative in the Age of LLMs +
    + Azmine Toushik Wasi, Raima Islam, Mst Rafia Islam +
    + CHI'24 In2Writing Workshop ▪ + Accepted ▪ + HCI ▪ + HMAI
    + [arXiv] +
    +

    +
    9. + +
  9. + ধরণী (Dhoroni): A Novel Multi-Perspective Bangla Climate Change and Environmental News Dataset +
    + Azmine Toushik Wasi, Wahid Faisal, Abdur Rahman, and Taj Ahmad +
    + In Review ▪ + Climate AI ▪ + BNLP +
    +

    +
    10. +
+ +
+ + +
+ + + +







+ + diff --git a/wings/DTP.html b/wings/DTP.html new file mode 100644 index 0000000..f0831af --- /dev/null +++ b/wings/DTP.html @@ -0,0 +1,180 @@ + + + + + + + + + + + + Digital Twin and Physics-Informed Machine Learning (DTP) Wing | Computational Intelligence and Operations Laboratory (CIOL) + + + + + + + + + + + +
+

🤖 Digital Twin and Physics-Informed Machine Learning (DTP) Wing

+
+

+ The Digital Twin and Physics-Informed Machine Learning (DT-PIML) Wing aims to bridge the gap between physical systems and their virtual counterparts, combining state-of-the-art simulation technologies with data-driven models. Digital Twin technology offers precise virtual replicas of real-world systems, allowing continuous monitoring, optimization, and predictive maintenance. By integrating physics-based principles with machine learning, this wing focuses on enhancing model accuracy and robustness, especially in complex industrial and engineering applications. +
Our goal : +

    +
  • Develop advanced Digital Twin models to control, optimize, simulate and monitor different systems in real time.
    • +
  • Incorporate physics-informed machine learning techniques to improve model reliability and performance in scenarios with limited or noisy data.
    • +
  • Explore the application of Digital Twins in diverse sectors, such as smart manufacturing, energy systems, supply chains, and medical AI.
    • +
+

+ + +

Team Members

+
+


+ + +
+
+ Manjurul Ahsan +

Md Manjurul Ahsan

+

Research Assistant Professor, OU +

+
+ +
+ MD Shafiqul Islam +

MD Shafiqul Islam

+

IPE, SUST +

+
+
+ Azmine Toushik Wasi +

Azmine Toushik Wasi

+

IPE, SUST +

+
+ +
+
+ +
+ Abdur Rahman +

Abdur Rahman

+

IPE, SUST +

+
+
+ Mahfuz Ahmed Anik +

Mahfuz Ahmed Anik

+

IPE, SUST +

+
+
+ Wahid Faisal +

Wahid Faisal

+

IPE, SUST +

+
+
+ Ikramul Haque Iban +

Ikramul Haque Iban

+

IPE, SUST +

+
+
+ + +

Publications

+
+ +
+
    + +
  1. + Stages of Integrating Digital Twin in Fused Deposition Modelling +
    + Abdur Rahman, Azmine Toushik Wasi, Mahfuz Ahmed Anik, and Md Manjurul Ahsan +
    + DigiTwin Conference | Purdue University ▪ + Accepted +
    +

    +
    2. + +
  2. + Sustainable Management of Rare Earth Elements for Clean Energy Using Prescriptive Digital Twins +
    + Mahfuz Ahmed Anik , Iqramul Hoque , MD Shafikul Islam, Azmine Toushik Wasi, Md Manjurul Ahsan and Mahathir Mohammad Bappy +
    + DigiTwin Conference | Purdue University ▪ + Accepted +
    +

    +
    3. + 4 more works are in progress! + +
+ +
+ + +
+ + + +







+ + diff --git a/wings/HMAI.html b/wings/HMAI.html new file mode 100644 index 0000000..2b64544 --- /dev/null +++ b/wings/HMAI.html @@ -0,0 +1,202 @@ + + + + + + + + + + + + 🕵️‍♂️ Human Machine/AI Interaction (HMAI) Wing | Computational Intelligence and Operations Laboratory (CIOL) + + + + + + + + + + + +
+

🕵️‍♂️ Human Machine/AI Interaction (HMAI) Wing

+
+

+ + In our IPE curriculum, the dept. offer various courses spanning ergonomics, human factors engineering, behavior studies, psychology, and more. We've identified a considerable opportunity for multidisciplinary research by integrating these disciplines with AI or computer-related domains, particularly in HCI with AI. Surprisingly, there has been limited activity in this field in Bangladesh. Given the rapid growth of human-computer interaction (HCI), we have collectively decided to explore and advance in this area with AI. +
Our works are focused on: +

    +
  • Developing and Evaluating Human-AI Interaction Systems
    • +
  • Developing Human Machine/Robotics Interaction Systems
    • +
  • Evaluating Computer Human Interaction Systems
    • +
  • Exploring AI-assisted HMI/HCI/CHI Systems
    • +
  • Ergonomics, Safety and Bias in Interaction Systems
    • +
+

+ + +

Team Members

+
+


+ + +
+
+ Raima Islam +

Raima Islam

+

MS (CSE), Harvard University +

+
+
+ Azmine Toushik Wasi +

Azmine Toushik Wasi

+

IPE, SUST +

+
+
+
+ +
+ Rafia Islam +

Mst. Rafia Islam

+

Law, IUB +

+
+
+ Taj Ahmad Turjo +

Taj Ahmad Turjo

+

IPE, SUST +

+
+ +
+ Yeamim Touhid +

Yeamim Touhid

+

Management, CVGC +

+
+
+ + +

Publications

+
+ +
+
    +
  1. + Exploring Large Language Model Systems Design Perspective Using Cognitive Ergonomics +
    + Azmine Toushik Wasi +
    + ICML'24 LLMs and Cognition Workshop ▪ + Accepted ▪ + HCI ▪ + HMAI
    + [arXiv] +
    +

    +
    2. + +
  2. + Exploring Bengali Religious Dialect Biases in Large Language Models with Evaluation Perspectives +
    + Azmine Toushik Wasi, Raima Islam, Mst Rafia Islam, Taki Hasan Rafi, Dong-Kyu Chae +
    + CHI'24 HEAL Workshop ▪ + Accepted ▪ + HCI ▪ + HMAI
    + [arXiv] +
    +

    +
    3. + +
  3. + LLMs as Writing Assistants: Exploring Perspectives on Sense of Ownership and Reasoning +
    + Azmine Toushik Wasi, Mst Rafia Islam, Raima Islam +
    + CHI'24 In2Writing Workshop ▪ + Accepted ▪ + HCI ▪ + HMAI
    + [arXiv] +
    +

    +
    4. + +
  4. + Ink and Individuality: Crafting a Personalised Narrative in the Age of LLMs +
    + Azmine Toushik Wasi, Raima Islam, Mst Rafia Islam +
    + CHI'24 In2Writing Workshop ▪ + Accepted ▪ + HCI ▪ + HMAI
    + [arXiv] +
    +

    +
    5. + +
+ +
+ + +
+ + + +







+ + diff --git a/wings/MedAI.html b/wings/MedAI.html new file mode 100644 index 0000000..3db8d97 --- /dev/null +++ b/wings/MedAI.html @@ -0,0 +1,173 @@ + + + + + + + + + + + + 💉 Medical AI and Informatics (MedAI) Wing< | Computational Intelligence and Operations Laboratory (CIOL) + + + + + + + + + + + +
+

💉 Medical AI and Informatics (MedAI) Wing

+
+

+ In our Medical AI and Informatics Wing, we are at the forefront of integrating artificial intelligence into healthcare, revolutionizing medical research and practice. Through developing advanced AI models for drug discovery, protein analysis, medical image analysis, diagnostics, and patient-human-computer interaction (HCI), we aim to enhance the efficiency and accuracy of medical processes and patient care. +
Our goals: +

    +
  • Innovate AI-driven techniques for drug discovery and protein analysis to accelerate the development of new treatments and understand biological mechanisms.
    • +
  • Enhance medical image analysis to improve the accuracy and speed of diagnosing conditions using AI.
    • +
  • Develop AI-based diagnostic tools to support healthcare professionals in making precise and timely decisions.
    • +
  • Improve patient-human-computer interaction (HCI) to create more intuitive and accessible healthcare technologies.
    • +
+

+ + + +

Team Members

+
+


+ + +
+ +
+ Manjurul Ahsan +

Md Manjurul Ahsan

+

Research Assistant Professor, OU +

+
+
+ Riashat Islam +

Riashat Islam

+

Research Scientist, SDAIA +

+
+
+ Azmine Toushik Wasi +

Azmine Toushik Wasi

+

IPE, SUST +

+
+ +
+ Sheikh Ayatur Rahman +

Sheikh Ayatur Rahman

+

CSE, BRACU +

+
+
+ + +

Publications

+
+ +
+
    +
  1. + Neural Control System for Continuous Glucose Monitoring and Maintenance +
    + Azmine Toushik Wasi +
    + ICLR'24 Tiny Papers ▪ + Accepted ▪ + CO ▪ + Medical AI
    + [OpenReview] ▪ + [arXiv] +
    +

    +
    2. +
  2. + RoBERTa Ensemble for Identifying Children’s Medical Disorders in English Tweets +
    + Azmine Toushik Wasi, Sheikh Ayatur Rahman +
    + ACL'24 Social Media for Health Workshop ▪ + Accepted ▪ + NLP
    + [ACL Anthology] +
    +

    +
    3. + +
  3. + Analyzing Social Anxiety Effects through Context-Aware Transfer Learning on Reddit Data +
    + Sheikh Ayatur Rahman, Azmine Toushik Wasi +
    + ACL'24 Social Media for Health Workshop ▪ + Accepted ▪ + NLP
    + [ACL Anthology] +
    +

    +
    4. +
+ +
+ + + +







+ + diff --git a/wings/OR_ML.html b/wings/OR_ML.html new file mode 100644 index 0000000..c071e92 --- /dev/null +++ b/wings/OR_ML.html @@ -0,0 +1,252 @@ + + + + + + + + + + + + Operations Research with ML (OR+ML) Wing | Computational Intelligence and Operations Laboratory (CIOL) + + + + + + + + + + + +
+

🚇 Operations Research with ML (OR+ML) Wing

+
+

+ Traditional optimization techniques in Industrial and Production Engineering (IPE) provide a robust foundation for solving complex problems and challenges of modern supply chains and manufacturing systems. By integrating machine learning (ML) with optimization, we can unlock new possibilities for enhancing efficiency, decision-making, and process improvement across various domains. CIOL focuses on this intersection, leveraging the strengths of both fields for groundbreaking research. +
Our goal : + +

    +
  • Develop ML-powered algorithms that efficiently solve complex optimization problems within the constraints of intricate industrial settings.
    • +
  • Use ML to analyze industrial data, build better optimization models, and improve decision-making under uncertainty, leading to increased profitability.
    • +
  • Fuse ML models with traditional optimization techniques to create powerful hybrid methods that maximize the strengths of both approaches.
    • +
  • Develop AI-powered forecasting models to optimize inventory management, production scheduling, and resource allocation in supply chains.
    • +
  • Create AI-driven risk assessment tools to proactively identify and mitigate disruptions within complex supply chain networks.
    • +
  • Utilize graph neural networks to optimize transportation routes, improve network resilience, and analyze the inter-connectivity of supply chains.
    • +
+

+ + +

Team Members

+
+


+ + +
+ +
+ A M M Mukaddes +

Dr. Abul Mukid Md. Mukaddes

+

Professor of IPE, SUST +

+
+ +
+ Mahathir Mohammad Bappy +

Mahathir Mohammad Bappy

+

Assistant Professor, LSU +

+
+
+ Md Asif Bin Syed +

Md Asif Bin Syed

+

SCM Analyst, The Home Depot +

+
+ +
+ +
+ +
+ MD Shafiqul Islam +

MD Shafiqul Islam

+

IPE, SUST +

+
+
+ Azmine Toushik Wasi +

Azmine Toushik Wasi

+

IPE, SUST +

+
+
+ Mahfuz Ahmed Anik +

Mahfuz Ahmed Anik

+

IPE, SUST +

+
+
+ +
+ +
+ Abdur Rahman +

Abdur Rahman

+

IPE, SUST +

+
+
+ Arnab Laskar +

Arnab Laskar

+

IPE, SUST +

+
+
+ Sahedul Mustaquim +

Sahedul Mustaquim

+

IPE, SUST +

+
+
+ + +

Publications

+
+ +
+
    + +
  1. + Neural Control System for Continuous Glucose Monitoring and Maintenance +
    + Azmine Toushik Wasi +
    + ICLR'24 Tiny Papers ▪ + Accepted ▪ + CO ▪ + Medical AI
    + [OpenReview] ▪ + [arXiv] +
    +

    +
    2. + +
  2. SupplyGraph: A Benchmark Dataset for Supply Chain Planning using Graph Neural Networks +
    + Azmine Toushik Wasi, + MD Shafikul Islam Sohan, + Adipto Raihan Akib +
    + AAAI'24 Graphs and more Complex structures for Learning and Reasoning Workshop (Full Paper) ▪ + Accepted ▪ + GNN ▪ + Supply Chains ▪ + Datasets and Benchmarks +
    + [Paper Site] ▪ + [arXiv] ▪ + [GitHub] ▪ + [Kaggle] +
    +

    +
    3. +
  3. Optimizing Inventory Routing: A Decision-Focused Learning Approach using Neural Networks +
    + MD Shafikul Islam Sohan, + Azmine Toushik Wasi +
    + NeurIPS'23 New in ML Workshop (Extended Abstracts) ▪ + Accepted ▪ + CO ▪ + OR-ML ▪ + Supply Chains +
    + [Paper Site] ▪ + [arXiv] ▪ + [OpenReview] +
    +

    +
    4. +
  4. + Graph Neural Networks in Supply Chain Optimization: Concepts, Perspectives, Dataset and Benchmarks +
    + Azmine Toushik Wasi, MD Shafikul Islam, Adipto Raihan Akib, and Mahathir Mohammad Bappy +
    + In Review ▪ + GNN ▪ + Supply Chain +
    +

    +
    5. + +
  5. + Presecriptive Analytics: A Review in the Landscape of Machine Learning +
    + In Progress ▪ + AML ▪ + SCM +
    +

    +
    6. + +
+ +
+ + +
+ + + +







+ + diff --git a/wings/index.html b/wings/index.html new file mode 100644 index 0000000..c948021 --- /dev/null +++ b/wings/index.html @@ -0,0 +1,173 @@ + + + + + + + + + + + + Research | Computational Intelligence and Operations Laboratory (CIOL) + + + + + + + + + + + +
+

Research Wings

+
+ + +

🚇 Operations Research with ML (OR+ML) Wing

+
+

+ Traditional optimization techniques in Industrial and Production Engineering (IPE) provide a robust foundation for solving complex problems and challenges of modern supply chains and manufacturing systems. By integrating machine learning (ML) with optimization, we can unlock new possibilities for enhancing efficiency, decision-making, and process improvement across various domains. CIOL focuses on this intersection, leveraging the strengths of both fields for groundbreaking research. +
Our goal : + +

    +
  • Develop ML-powered algorithms that efficiently solve complex optimization problems within the constraints of intricate industrial settings.
    • +
  • Use ML to analyze industrial data, build better optimization models, and improve decision-making under uncertainty, leading to increased profitability.
    • +
  • Fuse ML models with traditional optimization techniques to create powerful hybrid methods that maximize the strengths of both approaches.
    • +
  • Develop AI-powered forecasting models to optimize inventory management, production scheduling, and resource allocation in supply chains.
    • +
  • Create AI-driven risk assessment tools to proactively identify and mitigate disruptions within complex supply chain networks.
    • +
  • Utilize graph neural networks to optimize transportation routes, improve network resilience, and analyze the inter-connectivity of supply chains.
    • +
+

+ +

🤖 Digital Twin and Physics-Informed Machine Learning (DTP) Wing

+
+

+ The Digital Twin and Physics-Informed Machine Learning (DT-PIML) Wing aims to bridge the gap between physical systems and their virtual counterparts, combining state-of-the-art simulation technologies with data-driven models. Digital Twin technology offers precise virtual replicas of real-world systems, allowing continuous monitoring, optimization, and predictive maintenance. By integrating physics-based principles with machine learning, this wing focuses on enhancing model accuracy and robustness, especially in complex industrial and engineering applications. +
Our goal : +

    +
  • Develop advanced Digital Twin models to control, optimize, simulate and monitor different systems in real time.
    • +
  • Incorporate physics-informed machine learning techniques to improve model reliability and performance in scenarios with limited or noisy data.
    • +
  • Explore the application of Digital Twins in diverse sectors, such as smart manufacturing, energy systems, supply chains, and medical AI.
    • +
+

+ + +

🕵️‍♂️ Human Machine/AI Interaction (HMAI) Wing

+
+

+ +In our IPE curriculum, the dept. offer various courses spanning ergonomics, human factors engineering, behavior studies, psychology, and more. We've identified a considerable opportunity for multidisciplinary research by integrating these disciplines with AI or computer-related domains, particularly in HCI with AI. Surprisingly, there has been limited activity in this field in Bangladesh. Given the rapid growth of human-computer interaction (HCI), we have collectively decided to explore and advance in this area with AI. +
Our works are focused on: +

    +
  • Developing and Evaluating Human-AI Interaction Systems
    • +
  • Developing Human Machine/Robotics Interaction Systems
    • +
  • Evaluating Computer Human Interaction Systems
    • +
  • Exploring AI-assisted HMI/HCI/CHI Systems
    • +
  • Ergonomics, Safety and Bias in Interaction Systems
    • +
+

+ + + +

⚙️ Applied Machine Learning (AML) Wing

+
+

+ The AML wing focuses on using the power of machine learning to address real-world challenges within the Industrial and Production Engineering (IPE) domain. We specialize in a wide range of techniques, empowering us to analyze complex industrial data and develop innovative solutions that drive efficiency and optimization. +
Our goal : +

    +
  • Apply statistical and traditional machine learning methods to tackle diverse industrial challenges.
    • +
  • Utilize deep learning to analyze image, video, and sensor data for predictive maintenance and quality control.
    • +
  • Develop advanced forecasting models to predict trends in production, supply chains, and demand, facilitating proactive decision-making.
    • +
+

+ +

🔠 Bangla Language and NLP (BNLP) Wing

+
+

+ +In our NLP with Bangla Language Wing, we're pioneering the exploration of natural language processing in Bangla - our mother tongue and national language. Through developing and evaluating NLP models and constructing Bangla knowledge graphs, we're paving the way for advancements in linguistic understanding and technology in the Bengali language. +
Our goal : +

    +
  • Develop and refine Bangla NLP techniques for tasks such as text classification, sentiment analysis, and machine translation.
    • +
  • Create robust evaluation methods to assess the performance of Bangla NLP models and systems.
    • +
  • Working on Bangla Knowledge Graphs to work with complex relations between words and concepts, enabling intelligent semantic applications.
    • +
+

+ + +

💉 Medical AI and Informatics (MedAI) Wing

+
+

+ In our Medical AI and Informatics Wing, we are at the forefront of integrating artificial intelligence into healthcare, revolutionizing medical research and practice. Through developing advanced AI models for drug discovery, protein analysis, medical image analysis, diagnostics, and patient-human-computer interaction (HCI), we aim to enhance the efficiency and accuracy of medical processes and patient care. +
Our goals: +

    +
  • Innovate AI-driven techniques for drug discovery and protein analysis to accelerate the development of new treatments and understand biological mechanisms.
    • +
  • Enhance medical image analysis to improve the accuracy and speed of diagnosing conditions using AI.
    • +
  • Develop AI-based diagnostic tools to support healthcare professionals in making precise and timely decisions.
    • +
  • Improve patient-human-computer interaction (HCI) to create more intuitive and accessible healthcare technologies.
    • +
+

+ + + +



+ CIOL is always looking for strong, self-motivated, and hardworking research students and collaborators. If you are interested in joining or collaborating the lab, please email your CV and a short personal description with your research interests to ciol.management@gmail.com. + Any student or researcher from any university can join us if the research areas are aligned. We are open to all. +

+ +
+ + + +







+ +