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Eid Ul Adha Mubarak!May this Eid bring faith, joy, and prosperity to you and your family.Regards, Muhammad Saeed
27/05/2026

Eid Ul Adha Mubarak!
May this Eid bring faith, joy, and prosperity to you and your family.
Regards,
Muhammad Saeed

Call for Papers – Research Journal of Computer Science & Information Technology (RJCSIT)Lahore Garrison University invit...
04/05/2026

Call for Papers – Research Journal of Computer Science & Information Technology (RJCSIT)

Lahore Garrison University invites researchers, academicians, and practitioners to submit their original research papers for Volume 10, Issue 1 (2026) of the Research Journal of Computer Science & Information Technology.

Submission Deadline: 10 May 2026
No Publication Fee | APC: None
Rolling submissions with fast review decisions

Scope and Topics: Artificial Intelligence and Machine Learning
Computer Vision and Image Processing
Cybersecurity and Network Security
Cloud Computing, IoT and Distributed Systems
Data Science, Big Data and Analytics
Software Engineering and Systems Architecture
Bioinformatics and Health Informatics
Natural Language Processing and Human-Computer Interaction

Editor-in-Chief: Prof. Dr. Muhammad Atif
Managing Editor: Dr. Sajid Ullah Khan

Submit your manuscript online at: lgurjcsit.lgu.edu.pk

For queries:
[email protected]
[email protected]

Contribute your research and be part of advancing innovation in computer science and information technology.

Alhamdulillah, I am pleased to share that our research paper has been published in the International Journal of Molecula...
30/04/2026

Alhamdulillah, I am pleased to share that our research paper has been published in the International Journal of Molecular Sciences, a Q1 journal with Impact Factor 4.9.

Excited to share that another of our book chapters has been published with IGI Global “Towards Ethical AI in Dermatolog...
30/04/2026

Excited to share that another of our book chapters has been published with IGI Global

“Towards Ethical AI in Dermatological Diagnostics: Balancing Patient Privacy, Fairness, and Human-Centered Design”

This work explores how artificial intelligence is transforming dermatology—and more importantly, how we can ensure it is ethical, fair, and patient-centered. As AI continues to enhance diagnostic accuracy and healthcare delivery, it also raises critical concerns around data privacy, algorithmic bias, and transparency .

In this chapter, we highlight the importance of:
🔹 Protecting patient data and privacy
🔹 Addressing bias across diverse skin tones and populations
🔹 Designing AI systems that keep humans—both patients and clinicians—at the center

AI has immense potential to improve early detection and access to care, especially in resource-limited settings, but responsible implementation is key to building trust and equity in healthcare .

🔗 Read more: https://www.igi-global.com/gateway/chapter/407177

Grateful to be part of advancing conversations around ethical and trustworthy AI in healthcare.

Alhamdulillah!I’m delighted to share that our review article has been officially accepted and published in a Q1 journal....
28/04/2026

Alhamdulillah!

I’m delighted to share that our review article has been officially accepted and published in a Q1 journal.

Journal: International Journal of Molecular Sciences (IJMS)
Impact Factor: ~5.6

Title: Next-Generation Artificial Intelligence Strategies for Mechanistic Cancer Target Discovery and Drug Development: A State-of-the-Art Review

Honored to be a co-author alongside an outstanding team of researchers. Grateful for this milestone and looking forward to contributing further to the field.

Holistic Evaluation of Language Models (HELM)Evaluating LLMs goes beyond just accuracy. A truly robust model must be ass...
23/04/2026

Holistic Evaluation of Language Models (HELM)

Evaluating LLMs goes beyond just accuracy. A truly robust model must be assessed across multiple dimensions:

✔️ Accuracy
✔️ Calibration
✔️ Robustness
✔️ Fairness
✔️ Bias
✔️ Toxicity
✔️ Efficiency

This HELM framework highlights how different models perform across diverse real-world scenarios from question answering to summarization and beyond.

The takeaway: No single metric tells the whole story. Responsible AI requires a holistic view.

Understanding LLM evaluation ROUGE and BLEU are key evaluation metrics, ROUGE for summarization, BLEU for translation qu...
21/04/2026

Understanding LLM evaluation
ROUGE and BLEU are key evaluation metrics, ROUGE for summarization, BLEU for translation quality against human references.
Both help measure how well AI performs

Understanding the difference between Fine-Tuning and RAG (Retrieval-Augmented Generation) is key when building modern AI...
20/04/2026

Understanding the difference between Fine-Tuning and RAG (Retrieval-Augmented Generation) is key when building modern AI applications.
Fine-Tuning
– Trains a model on specific data
– Best for specialized, consistent tasks
– Knowledge is “baked into” the model
RAG
– Retrieves real-time information from external sources
– Keeps responses up-to-date and contextual
– Ideal for dynamic knowledge use cases
Choosing the right approach depends on your problem:
Stable domain? Fine-tune.
Dynamic data? Go with RAG.

Peaceful night in DHA Lahore Silence, fresh air, and nature at its best.Capturing these calm moments through my lens 📸 ...
18/04/2026

Peaceful night in DHA Lahore
Silence, fresh air, and nature at its best.
Capturing these calm moments through my lens 📸

RAG vs Fine-Tuning — How Modern AI Systems WorkThis diagram clearly shows the difference between two powerful approaches...
14/04/2026

RAG vs Fine-Tuning — How Modern AI Systems Work

This diagram clearly shows the difference between two powerful approaches in AI:

🔹 RAG (Retrieval-Augmented Generation)
User query → embedding → vector database → relevant context → LLM → response
👉 Best for dynamic knowledge, real-time data, and explainable outputs
👉 Easy to update (just update your data, not the model)

🔹 Fine-Tuning
Training data → model training → LLM → response
👉 Best for learning behavior, tone, and domain-specific tasks
👉 More consistent but costly to update

Key Insight:

Use RAG when knowledge changes frequently

Use Fine-Tuning when behavior needs to be controlled

In real systems, combining both gives the best results

Modern AI is not just about models — it’s about system design and smart decisions

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