Dr Nasir Mukhtar@nasirxmukhtar
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Events attended
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Submissions made
20+ years of experience
About me
Prof. Dr. Nasir Mukhtar is currently serving as Head of the Department of Poultry Science and as a Global Consultant and Sector Specialist at Poulta Inc., USA (a Silicon Valley–based startup). He is also a Consultant at Instaflect AI. He has over 8 years of direct industry experience in the poultry sector and more than 16 years of academic experience, having served as a Professor in multiple leadership and academic positions. Dr. Mukhtar is the Vice President of the World’s Poultry Science Association (WPSA), Asia–Pacific Region, Former Secretary General of WPSA Pakistan, and the current Secretary General of WPSA UAE Branch. He also serves as the Global Group Leader of the SSFPF of WPSA. He has organized 16 international poultry conferences and conducted numerous professional training programs worldwide. He has successfully supervised 6 PhD scholars and 18 Master’s students. Academically, he holds a BBA, BSc (Hons) in Animal Husbandry, MSc (Hons) in Poultry Science, a PhD in Animal Nutrition, and a Postdoctoral Fellowship in Poultry Science from the Roslin Institute, University of Edinburgh, Scotland. Dr. Mukhtar is the author of 69 research articles and several books in the field of poultry and animal nutrition.
🤓 Latest Submissions
Chicken Twin
Simulation Logic (Particle-Level Detail) The simulation runs on a high-frequency loop (60Hz) using a state-update-render cycle. Entity Mobility: Every bird is an object instance with independent vectors for position, velocity, and acceleration. The "Boids" Influence: Bird movement uses a simplified flocking algorithm containing three forces: Cohesion: Steering toward the average position of the flock. Separation: Steering to avoid crowding (collision avoidance). Wander: A Perlin-noise based "random walk" that simulates natural curiosity. Disease Vectors: Diseases are non-linear state machines. Once a bird is infected, its internalTemperature rises at 0.05°C per minute, and its mobilityFactor decays, leading to perceptible lethargy. Robotic Engineering (ROBO-SM) The robot uses a Telescoping Brother-Node Hierarchy for the arm. Physics Constraint: Unlike simple scaling, the segments are individually addressed meshes that maintain their diameter while extending, ensuring visual stability. Interpolation: Movement uses ease-in-out quintic interpolation to simulate the mass and momentum of industrial servos. Mission Sequence: SCAN → INTERCEPT → DESCEND → SECURE → RETRACT → DEPOSIT. Backend Juggernaut (monitor.py) The Python backend acts as the "Cognitive Core." WebSocket Telemetry: It broadcasts a serialized JSON stream containing every bird's coordinate and risk score. Persistent Memory: Saves session data to a local server-side database, allowing for high-speed replay with 100% frame fidelity. Safety Net: The Fallback AI (browser-side) takes over if the Python core loses heartbeat, ensuring 100% uptime for live demos.
15 Feb 2026
