AI Tinker Lab Eco-Innovators

May 22, 2026

by Syed Taqi Trainings

AI Tinker Lab: Eco-Innovators | S2Cool Initiative

A Project of the S2Cool Initiative

AI Tinker Lab

Eco-Innovators

Cultivating young leaders to engineer a sustainable, climate-resilient future. A hands-on, 5-day interactive camp dedicated to inspiring the next generation to solve climate challenges using Artificial Intelligence, creativity, and green tech.

View Timetable

Quick Details

Camp Essentials

Date & Schedule

8 – 11 June, 2026 (Daily)

12 June: Capstone Day (10AM-4:30PM)

Location

NUST SEECS, Islamabad

Sector H-12 Campus

Ideal For

Young Eco-Innovators

Climate Tech Enthusiasts

Prerequisites

No prior coding/AI needed!

Just Curiosity & Passion

Camp Mission

What You Will Master

Empowering future leaders with the technical literacy and strategic insight to address major ecological and cooling issues globally.

Train Machine Learning

Interactively train computer vision and classification models to solve real-world smart energy efficiency and waste management problems.

Audit AI Biases

Inspect, test, and break AI datasets to discover biases and understand their ecological impact on physical management systems.

Formulate Conversational AI

Design and deploy specialized AI personas programmed to deliver localized climate action directives and energy conservation tips.

Harness Generative Art

Master prompt engineering techniques to synthesize high-impact generative art, comics, and stories on environmental sustainability.

Collaborative Tech Prototyping

Team up to brainstorm, formulate a Concept Canvas, and pitch your custom Green Tech solution at the physical exhibition.

Capstone Project

The Green Tech Solution Prototype

Throughout the 5-day lab, you won't just learn theory; you will assemble a functional, collaborative tech prototype that builds sequentially day by day, culminating in a live exhibition presentation.

Identify (Days 1 & 2)

Establish energy saving systems and automatic waste sorters while observing how AI algorithms see waste and power usage.

Communicate (Days 3 & 4)

Configure intelligent climate bots and prompt generative tools to illustrate and visualize climate challenges visually.

Build (Day 5)

Define training datasets, draft functional wireframes on a Concept Canvas, and assemble a prototype to pitch to judges.

Timeline Overview

Lab Schedule

Explore our detailed, activity-driven itinerary. Switch between daily modules using the dynamic controller below.

Smart Energy Controls

8th June, 2026 | 10:00 AM - 01:00 PM

Focus: Teachable Machines & Power Saving

10:00 – 10:20

Tinker Warm‑Up Human or Bot?

An interactive introductory session challenging participants to identify computational characteristics vs human logic.

10:20 – 11:15

Lab 1 Smart Energy Controller Project

Train an visual Teachable Machine (Google) model to automatically shut down power networks or detect energy patterns.

11:15 – 11:30

Snack & Talk AI in the Wild: Smart Grids

Fuel up with treats while learning how localized smart cooling and power grids utilize live algorithms.

11:30 – 12:30

Lab 2 Break Your Own Model

Adversarial tinkering! Learn how to purposely trick, fool, and patch your energy saving algorithm to understand critical flaws.

12:30 – 12:50

Tinker Notes Day 1 Retrospective Review

Quick gamified recap, documenting critical observations on energy logic into lab notebooks.

12:50 – 13:00

Clean-up Lab Reset & Wrap Up

Clearing the workbenches and setting down equipment for the next day's physical experiments.

Waste Sorting AI Systems

9th June, 2026 | 10:00 AM - 01:00 PM

Focus: Training & Data Bias

10:00 – 10:20

Tinker Warm‑Up Human Camera

A fun perceptual game illustrating how different focal points alter spatial data collection.

10:20 – 11:15

Lab 3 Eco-Sorter AI Lab

Build and optimize an image classification network engineered to instantly segment recycling vs waste materials.

11:15 – 11:30

Snack Time Class Tournament: Best Sorting AI

Testing participant-trained models against real tricky waste pieces. Who has the highest classification accuracy?

11:30 – 12:30

Lab 4 Bias Busters Investigation

Discover how skewed and limited datasets cause automatic sorters to fail, prompting real-world ecological hazards.

12:30 – 12:50

Tinker Notes Bias Retrospective

Assembling data parameters for fair algorithms and planning our training guidelines.

12:50 – 13:00

Clean-up Lab Maintenance

Sorting physical materials and preparing storage partitions.

Climate Bots & Conversational AI

10th June, 2026 | 10:00 AM - 01:00 PM

Focus: Persona Formulation

10:00 – 10:20

Tinker Warm‑Up Instruction Chain

A fast-paced interactive simulation revealing logic chains, natural language processing, and system prompts.

10:20 – 11:15

Lab 5 Persona Bot Workshop

Write customized system prompts to create unique LLM-based assistants embodying expert ecological personas.

11:15 – 11:30

Snack Time Bot Showcase Shareout

Fun showcase sharing the funniest, smartest, or most peculiar environmental advice synthesized by student bots.

11:30 – 12:30

Lab 6 Bot Fair & Break-In Challenge

Swap seats to interact with classmate bots. Can you craft prompts to trick another group's bot into recommending bad policies?

12:30 – 12:50

Tinker Notes Prompt Logic Review

Refocusing on reliable instruction pipelines and system integrity guards.

12:50 – 13:00

Clean-up Device Check & Logging

Logging out of lab systems safely and resetting workstations.

Eco-Imagination & Generative Art

11th June, 2026 | 10:00 AM - 01:00 PM

Focus: Art & Creative Solutions

10:00 – 10:20

Tinker Warm‑Up Exquisite Prompt Game

Collaborative structural writing game demonstrating how syntax nuances change generative AI outputs.

10:20 – 11:15

Lab 7 Prompt Crafting & Composition

Harnessing generative diffusion engines to design stunning environmental "Climate Hero" concepts and imagery.

11:15 – 11:30

Snack Time Instant Environmental Gallery

Curating digital displays of modern artworks on large screens to showcase collective prompt ideas.

11:30 – 12:30

Lab 8 3-Panel Eco-Comic Challenge

Deploy narrative tools to storyboard a multi-panel visual comic depicting an AI system resolving a critical energy crisis.

12:30 – 12:50

Tinker Notes Opinion Line Review

A dynamic physical standup discussing deep generative authorship ethics.

12:50 – 13:00

Clean-up Project Pitch Prep

Organizing materials for the upcoming Grand Capstone day.

Green Tech Showcase

12th June, 2026 | 10:00 AM - 04:30 PM (Special Extended Day)

Capstone & Pitch Exhibition

10:00 – 10:20

Tinker Warm‑Up Problem Carousel

Mapping local cooling and environmental issues directly onto whiteboards.

10:20 – 11:15

Lab 9 Team Assembly & Concept Canvas

Form multi-disciplinary groups, draft solution frameworks, map input data requirements, and outline AI actions.

11:15 – 11:30

Pitch Check Rapid Pitch Feedback

Present high-level concepts to trainers for actionable optimizations before building.

11:30 – 15:00

Lab 10 Assemble the Working Mock-up

Design custom wireframes, configure functioning bots, organize mock datasets, and craft structural pitches. (Includes lunch breaks)

15:00 – 16:00

Exhibition Grand Tinker Fair

Presenting live interactive designs to NUST mentors, families, and academic reviewers.

16:00 – 16:30

Camp Closing Certificate Ceremony & High-Fives

Official distribution of S2Cool certifications and program closing address.

Technology Matrix

The Innovator's Toolkit

A modern toolkit of software suite parameters and AI modeling frameworks kids will master during the camp.

Teachable Machine

Google image & visual recognition dataset structuring platform.

Custom Persona Bots

Natural Language processing system instruction engineering (LLMs).

Generative AI Engines

Pixel synthesis, storyboards, and composition prompt styling.

Concept Canvases

Interactive planning boards to design data inputs and logic paths.

Warm‑Up Challenge

Are You an Eco‑Innovator?

Test your eco-tech intuition with our quick interactive quiz. Find out how AI assists in sustainable cooling! Click an option to test your skills live.

What is the main advantage of using AI in "Smart Cooling" grids?

Camp Faculty

Meet Your Instructors

Learn from prominent scholars, researchers, and technical architects leading NUST computer vision projects.

Prof. Dr. Muhammad Moazam Fraz (TI)

Professor & Associate Dean

NUST SEECS

Dr. Fahad Ahmed Satti

Assistant Professor

NUST SEECS

Dr. Zuhair Zafar

Faculty Member & Scholar

NUST SEECS

Dr. Muhammad Bilal Ali

Faculty Member & Researcher

NUST SEECS

Have Questions? Contact Us

Get in touch with the project coordination team at NUST SEECS if you need administrative information or details on seat reservations.

Location

SEECS NUST, Sector H-12, Islamabad, Pakistan

Email Address

vision@seecs.edu.pk

Phone Support

(051) 8862155

Event Pictures

Resilient Futures: AI & Remote Sensing for Sustainable Agriculture and Urban Well-Being in Pakistan

March 22, 2026

by Syed Taqi Uncategorized

Date

9th October 2025 (Thursday)
Venue:
Seminar Hall, PG Block, SEECS

Resilient Futures: GeoAI for Farms & SLUMs, Data-Driven Planning for Efficient Cooling in Communities and Agriculture is an applied training that equips participants with practical GeoAI, remote sensing, and resilience analytics skills to identify heat hotspots, assess vulnerability, and plan sustainable cooling interventions. Anchored in the S2Cool project mission, the training connects geospatial intelligence to real-world use-cases across agriculture and dense settlements—supporting evidence-based decisions that improve thermal comfort, reduce energy intensity, protect livelihoods, and strengthen climate resilience.

Interpret and generate heat, vulnerability, and cooling-demand maps using GeoAI for prioritizing S2Cool-aligned interventions

Apply remote sensing indicators (e.g., temperature, vegetation/crop stress, water proxies) to support climate-smart farming and reduce post-harvest losses through targeted cooling needs assessment

Understand smart farm mechanization pathways and where automation/IoT can improve productivity and resource efficiency (energy and water)

Assess climate risks (heatwaves, floods, reliability risks) and integrate resilience considerations into cooling and infrastructure decisions

Define practical sustainability metrics linked to S2Cool outcomes (energy efficiency, emissions reduction, affordability, access, reliability)

Workshop Timeline

9:00 AM – 10:00 AM

GeoAI for Heat, Vulnerability, and Cooling-Demand Mapping

Prof. Dr. Karsten Berns RPTU, Germany

10:00 AM – 12:00 PM

Remote Sensing for Climate-Smart Farms

Dr Muhammad Sheraz DFKI, Germany

12:00 PM – 01:00 PM

Smart Farm Mechanization

Dr. Muhammad Sultan BZU, Multan

☕ 01:00 PM – 01:30 PM — Refreshments & Break

02:00 PM – 03:00 PM

GeoAI for Informal Settlements: Cooling & Health

Dr. M. Khurram Ehsan Bahria University

03:00 PM – 04:00 PM

Climate Risk and Resilience Analytics

Dr Zuhair Zafar SEECS, NUST

04:00 PM – 05:00 PM

Climate & Water Sustainability

Ms. Quratulain Ahmed Ministry of Climate Change

This activity is funded by the DAAD Germany , through the Project ID: 57708351 , titled “ SLUM-i: A Remote Sensing Based Intelligent Framework for Detection and Predictive Growth Analysis of Slums for Sustainable Socio-Economic Development of Pakistan “

Testimonials

“

Dr. Sheraz’s session on remote sensing for crop stress was incredibly practical. I now see how we can use water proxies to reduce post-harvest losses significantly.

Bilal Ahmed Agritech Specialist

“

The GeoAI for Informal Settlements talk by Dr. Khurram was an eye-opener. It perfectly mapped out how we can improve livability in dense areas through data.

Sana Mir Urban Planner

“

Learning about smart farm mechanization from Dr. Sultan gave me a new perspective on energy efficiency. The S2Cool mission is exactly what the industry needs.

Omar Khan Agricultural Engineer

“

Ms. Quratulain bridged the gap between policy and technical execution. The session on Climate & Water Sustainability was vital for our adaptation strategies.

Ayesha Khan Policy Analyst

“

Dr. Zuhair’s analytics on heatwaves and floods provided the hard data we needed. This training equips you to make evidence-based infrastructure decisions.

Fahad Hassan Infrastructure Consultant

“

Prof. Berns made GeoAI concepts so accessible. I can now apply cooling-demand mapping techniques directly to my thesis research on heat hotspots.

Zainab Malik GIS Researcher

“

Dr. Sheraz’s session on remote sensing for crop stress was incredibly practical. I now see how we can use water proxies to reduce post-harvest losses significantly.

Bilal Ahmed Agritech Specialist

“

The GeoAI for Informal Settlements talk by Dr. Khurram was an eye-opener. It perfectly mapped out how we can improve livability in dense areas through data.

Sana Mir Urban Planner

“

Learning about smart farm mechanization from Dr. Sultan gave me a new perspective on energy efficiency. The S2Cool mission is exactly what the industry needs.

Omar Khan Agricultural Engineer

Contact us

Location
SEECS NUST, H-12 Islamabad

Email
vision@seecs.edu.pk

Phone Number
(051) 8862162

Ba-Ikhtiyar Jawan Knowledge Sharing Seminar: AI-Enabled Digitization of TVET and Personalized Vocational Learning

February 16, 2026

by Syed Taqi Trainings

Ba-Ikhtiyar Jawan Seminar

A Project of Ba-Ikhtiyar Jawan

Knowledge Sharing Seminar

AI-Enabled Digitization of TVET
and Personalized Vocational Learning

Exploring how AI, multilingual content, and digitized curricula can accelerate vocational training outcomes in Pakistan, featuring live system demonstrations.

Date & Time 3rd March 2026 09:00 AM - 17:00 PM

Location SEECS Seminar Hall NUST Campus

Focus Area Auto-Electrician Trade Curriculum Digitization

Attendees TVET Stakeholders Academia, Industry, Policy

Seminar Objectives

Share Progress: Present Ba-Ikhtiyar Jawan progress and practical approaches to curriculum digitization and multimodal learning for TVET.

Live Demonstrations: Showcase AI solutions for manual translation, personalized learning, and Urdu tutoring for underserved learners.

Collect Input: Gather stakeholder feedback to strengthen industry alignment and deployability in offline/edge settings.

Build Roadmaps: Produce actionable recommendations and a short roadmap for partnerships and strategic scaling.

Featured Project Demonstrations

Live showcases of three AI-powered learning systems developed to accelerate and localize technical training.

Demo 1: Multilingual Personalized Vocational Training

Adapts learning pathways via learner profiling and recommendation intelligence. Uses bilingual datasets to support automated creation of culturally relevant quizzes, tutorials, and microlearning modules across multiple delivery modes.

Demo 2: HunarmandAI Intelligent Tutoring

Designed for underserved, low-literacy Urdu speakers. Features multimodal text/speech interaction and fine-tuned language models for interactive learning, contributing curated low-resource Urdu datasets to the vocational domain.

Demo 3: Robust Perception-to-Instruction Pipelines

Converts degraded, scanned industrial manuals into reliable instructional content. Uses instruction-tuned language models to preserve procedural meaning, technical terminology, and usability even under heavy OCR noise.

Program Schedule

Theme: Digitization of TVET through AI-driven adaptive tools, multilingual tutoring, and robust machine translation pipelines.

Morning Session: Keynotes & Overviews

Foundations of TVET Digitization

09:00 – 09:30

Registration & Networking Tea Organizing Team

09:30 – 09:45

Opening, Objectives & Seminar Overview Moderator

09:45 – 10:15

Keynote AI-Driven Transformation in TVET (Why Now, What Works) Dr Fahad A Satti, Faculty, NUST SEECS

10:15 – 10:35

Ba-Ikhtiyar Jawan Snapshot Digitized bilingual curricula, AI tools, and global knowledge exchange by the Project Lead

10:35 – 10:50

Tea Break

10:50 – 11:20

Knowledge Talk Curriculum Digitization for Auto-Electrician Trade Dr Naseer Bajwa, Faculty, NUST SEECS

Mid-Day: Live System Demonstrations

Showcasing Practical AI Implementations

11:20 – 12:00

DEMO 1 Robust Perception-to-Instruction Pipelines Machine Translation & instruction preservation under OCR noise from Industrial Manuals. (Project Demo Team)

12:00 – 12:30

DEMO 2 Multilingual Personalized Vocational Training Using Recommendation Intelligence for Youth Empowerment. (Project Demo Team)

12:30 – 13:00

DEMO 3 HunarmandAI Intelligent Tutoring Culturally-Aware Tutoring for Low-Literacy Urdu Speakers. (Project Demo Team)

13:00 – 13:45

Lunch & Networking

Afternoon: Industry Alignment & Strategy

Panels, Working Groups, and Roadmaps

13:45 – 14:20

Expert Talk Industry Alignment & Employability Local and Gulf market readiness by Dr Seemab Latif, Founder and CEO, AAWAZ AI Solutions

14:20 – 15:05

Panel Discussion + Q&A Academia, Industry, and TVET bodies discussion. (Moderator + Panellists)

15:05 – 15:20

Tea Break

15:20 – 16:05

Working Groups Breakout Tracks (3 tracks) 1) Curriculum gaps, 2) Digital delivery, 3) Industry readiness. (Facilitators)

16:05 – 16:40

Group Readouts + Consolidated Recommendations Moderator

16:40 – 17:00

Closing Roadmap, Partnerships & Next Steps by Project Lead

Expected Outcomes

Shared Understanding: Practical pathways for AI-enabled TVET digitization established among all stakeholders.
Deployability Feedback: Direct stakeholder feedback captured on curriculum digitization and the real-world readiness of project tools.

Actionable Roadmaps: Recommendations formulated into a short roadmap for future implementation and strategic partnerships.
Dissemination: Production of valuable materials including a concise, shared seminar proceedings report.

Organizers

The leadership and organizing committee behind the Ba-Ikhtiyar Jawan Seminar.

Prof Dr. Muhammad Moazam Fraz

Professor & Associate Dean

SEECS, NUST

Dr. Junaid Younus

Assistant Professor

SEECS, NUST

Dr. Muhammad Imran Malik

Associate Professor & HoD Dept. of Computer Science

SEECS, NUST

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Applied AI and Data Science for Environmental Sustainability & Cooling Solutions

February 1, 2026

by Syed Taqi Trainings

A Project of the S2Cool Initiative

4-Day Intensive Training

Applied AI & Data Science for
Environmental Sustainability & Cooling Solutions

Build an LLM-powered RAG assistant and deploy Computer Vision models. A hands-on workshop dedicated to solving climate challenges.

Date & Time 16 – 19 February, 2026 09:00 -16:30 & 14:00 - 17:00

Location Lecture: Classroom 28, 3rd Floor, Academic Block-1 Lab: Computing Lab 07, UG Block

Audience Analysts, Engineers, Researchers

Prerequisites Python, ML Basics Command Line + Git

Learning Objectives

By the end of Day 4, participants will be able to:

Build an LLM-powered RAG assistant for climate/sustainability/cooling knowledge and reporting.

Train and evaluate computer vision models for environmental monitoring (heat islands, deforestation, land cover).

Productionize models with MLOps/LLOps: Experiment tracking, model registry, CI/CD, monitoring, containerization, scalable inference.

Write clean, testable AI software: Modular pipelines, APIs, packaging, performance basics.

Complete Timetable

Detailed breakdown of lectures and hands-on labs.

Day 1: LLMs & Generative AI

Climate Data Science Focus

Instructor: Dr. Muhammad Moazam Fraz

09:00 – 10:30	Lecture 1 (90m) LLMs, climate domain framing, RAG foundations
10:45 – 12:15	Lecture 2 (90m) Embeddings, retrieval, evaluation, safety/grounding
13:30 – 16:30	Lab (180m) Build Climate+Cooling RAG assistant v1 Hands-on implementation of the concepts learned.

Day 2: Computer Vision

Environmental Monitoring

Instructor: Dr. Nazia Pervaiz

09:00 – 10:30	Lecture 1 (90m) Remote sensing + CV tasks for sustainability
10:45 – 12:15	Lecture 2 (90m) Segmentation/classification, metrics, robustness
13:30 – 16:30	Lab (180m) Heat island / land cover / deforestation model + inference

Day 3: MLOps/LLOps & Deployment

From Prototype to Production

Instructor: Dr. Fahad Satti

09:00 – 10:30	Lecture 1 (90m) MLOps lifecycle, experiment tracking, reproducibility
10:45 – 12:15	Lecture 2 (90m) CI/CD, model registry, monitoring, scaling (Ray/Spark)
13:30 – 16:30	Lab (180m) Containerize + deploy APIs + MLflow registry + basic monitoring

Day 4: Programming for AI

Clean Code, Pipelines, APIs

Instructor: Dr. Rabia Irfan

09:00 – 10:30	Lecture 1 (90m) Clean architecture for AI systems + testing strategy
10:45 – 12:15	Lecture 2 (90m) Data pipelines, APIs, packaging, performance basics
13:30 – 16:30	Lab (180m) Refactor to production-ready repo + tests + final demo

Meet the Trainers

Dr. Muhammad Moazam Fraz

Dr. Nazia Pervaiz

Dr. Fahad Satti

Dr. Rabia Irfan

Integrated Capstone Project

"CoolSmart Climate & Cooling Intelligence Platform"

A deployable prototype that helps decision-makers identify heat-risk zones, understand sustainability drivers, and generate evidence-grounded cooling interventions. The project evolves across all 4 days.

LLM / GenAI (Day 1)

Climate & cooling RAG assistant: Summarize climate risks and cooling strategies.
Generate sustainability briefs with citations.
Q&A over IPCC/standards/cooling guidelines and local notes.
Outputs structured JSON for downstream dashboards/workflows.

Computer Vision (Day 2)

Environmental monitoring module: Detect urban heat island risk proxies (LST + built-up/vegetation).
Optional extension: deforestation or land cover change.
Outputs masks/tiles + risk scores for neighborhoods/areas.

MLOps & Production (Day 3 & 4)

Experiment tracking + model registry (MLflow).
FastAPI microservice endpoints:
/cv/predict (tile → mask + stats)
/rag/ask (question → cited answer)
Containerized deployment + telemetry logs.
Optional scalable batch inference (Ray).
Clean architecture, tests, packaging, configs.
Performance tuning (caching, batching) + Final demo case study.

Open-Source Tech Stack

Python & Jupyter pandas & numpy PyTorch Hugging Face LangChain/LlamaIndex OpenCV MLflow Docker FastAPI

Event Pictures

Contact us

Location
SEECS NUST, H-12 Islamabad

Email
vision@seecs.edu.pk

Phone Number
(051) 8862162

Multilingual Personalized Vocational Training Using Recommendation Intelligence for Youth Empowerment

January 5, 2026

by Syed Taqi Intelligent Systems

Multilingual Personalized Vocational Training Using Recommendation Intelligence for Youth Empowerment

Multilingual Personalized Vocational Training Using Recommendation Intelligence for Youth Empowerment is a project that reimagines how skill development can be delivered to young learners across diverse cultural and linguistic backgrounds. In many regions, especially where resources are scarce, vocational training is still restricted by language barriers, outdated content, and rigid, one-size-fits-all teaching methods. This project directly tackles those limitations by building a platform that adapts to each learner. Using multilingual support in Urdu and English, the system makes high-quality vocational training accessible to students who might otherwise be excluded, preparing them with practical skills for employability.

The proposed system includes an intelligent recommendation engine that creates personalized learning pathways. Instead of presenting the same modules to every student, the system actively learns from each individual’s background, prior knowledge, language preferences, and engagement style. By combining learner profiling and collaborative filtering, the platform suggests the right content at the right time, whether that’s a step-by-step tutorial, a microlearning module, or an adaptive quiz. To strengthen inclusivity, the project also curates bilingual vocational materials originally in German, translating and localizing them into Urdu and English. This approach not only ensures cultural and linguistic relevance but also makes previously inaccessible resources usable for learners in underrepresented communities.

Beyond being a technical prototype, the project is designed with real-world impact in mind. Its adaptive architecture means that as learners progress, the system automatically adjusts difficulty, pacing, and even content format (text, audio, video) to fit their needs. The result is a dynamic and empowering experience that helps learners stay engaged and retain skills more effectively. By aligning training modules with national vocational standards (TEVTA & NAVTTC) and incorporating industry-relevant updates like hybrid and electric vehicle repair, the platform equips students with knowledge that matches labor market demands. More importantly, it levels the playing field, giving marginalized youth an equal opportunity to acquire skills and pursue livelihoods, while also opening new avenues for research into human-centered AI and the future of personalized learning technologies.

Faculty

Dr. Muhammad Moazam Fraz

Dr. Muhammad Moazam Fraz
Dr. Junaid Younas

Dr. Junaid Younas

Students

Isra Mansoor
Muhammad Abdullah

Publications

- Abdullah, M., Mansoor, I., Rey, V.F. and Fraz, M.M., 2025, December. A Multi-LLM Pipeline for Retrieval-Grounded, Bloom’s Taxonomy-Aligned Question Generation. In 2025 5th International Conference on Digital Futures and Transformative Technologies (ICoDT2) (pp. 1-6). IEEE. https://doi.org/10.1109/ICoDT269104.2025.11360748

Research Published in FIT 2025

December 15, 2025

by Syed Taqi News

★

Publication Success

Congratulations!

Published in FIT 2025

Pixel-Based Glacial Change Monitoring Across Hindu Kush, Karakoram, & Himalayan Ranges

Authored By

Muhammad Sameer Amjad

•

Muhammad Jamshaid Ghaffar

•

Usama Athar

Read on IEEE Xplore

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Keynote in University of Wah by Dr. Muhammad Naseer Bajwa

December 10, 2025

by Syed Taqi News

Event Highlight

Dr. Muhammad Naseer Bajwa Delivers Keynote on Trustworthy AI in Medical Diagnosis at CACIO-2025

December 17, 2025 | University of Wah, Wah Cantt

Dr. Muhammad Naseer Bajwa delivered a compelling keynote address at the 5th UW-POFs Joint Conference on Academia’s Collaboration with Industrial Organisation (CACIO-2025) held on December 17th at the University of Wah.

The talk focused on the critical application of Trustworthy AI in medical diagnosis, with a particular emphasis on advancements in ophthalmology.

Keynote Topic “Let’s See Through A-Eye”

The keynote highlighted how explainability, reliability, and uncertainty awareness in AI systems can enhance clinical decision-making and build trust among healthcare professionals. The session also discussed challenges and opportunities in translating AI research into real-world medical practice through academia–industry collaboration.

The conference provided a valuable platform for dialogue between researchers, clinicians, and industry representatives on leveraging emerging technologies for societal impact.

Research Published in ICET 2025

November 27, 2025

by Syed Taqi News

★

Publication Success

Congratulations!

Published in ICET 2025

Semi-Supervised Contrastive Representation Learning for Sunflower Phenology Estimation

Authored By

Saleha Zainab Fatima

•

Munazza Raees

•

Usama Athar

This research was conducted at MachVis as part of the project:

From Drones to Decisions: LLM-Based Crop Health Insights from RGB and Multispectral Data ↗

Read on IEEE Xplore

Research Published in IGARSS 2025

November 25, 2025

by Syed Taqi News

★

Publication Success

Congratulations!

Published in IGARSS 2025

Combining UAV Multispectral Data & Crop Morphological Features for Sunflower Oil Content Estimation

Authored By

Muhammad Ali

•

Usama Athar

This research was conducted at MachVis as part of the project:

Multi-Trait, Multi-Season Framework for Accurate Sunflower Yield and Oil Content Estimation ↗

Read on IEEE Xplore

Bridging Skills and Technology: AI-Driven Transformation in Technical and Vocational Education

November 15, 2025

by Syed Taqi Trainings

Date

26th and 27th November 2025 (Thursday)
Venue:

As part of the Ba-Ikhtiyar Jawan Project, partners including NUST, DAAD, RPTU and German collaborators are hosting a one-day workshop on “Bridging Skills and Technology: AI-Driven Transformation in Technical and Vocational Education.” This collaborative event will bring together experts from vocational training, higher education, and the technology industry to explore the integration of AI in skill development. Key discussions and project updates will focus on Generative AI, the development of bilingual Urdu-English small language models for specific domains, machine translation of vocational content, and the creation of personalized learning systems. Through a series of expert talks, project demonstrations, and a concluding panel discussion, the workshop aims to strengthen partnerships between academia and industry and define a clear roadmap for modernizing Pakistan’s vocational training landscape.