Dr. Kashfia Sailunaz is is a Postdoctoral Research Fellow in Computer Science at Dalhousie University, Nova Scotia, Canada (Linkedin). Her current research focuses on the application of Artificial Intelligence and Computer Vision in the domains of precision livestock management and sustainable agriculture. She is also supervising undergraduate and graduate students on several interdisciplinary projects on from these domains. Her works include the development of image/video-based AI systems for monitoring animal health and welfare. She is also contributing to the development of an AI-driven decision support system for reducing greenhouse gas (GHG) emissions in Atlantic Canada.

Prajesh Padmanabhan is a Joint Doctoral Program student at Dalhousie University and Tamil Nadu Agricultural University, specialising in Geoinformatics (Linkedin). His PhD research focuses on leveraging remote sensing, geospatial data, and AI to assess the impacts of climate change on dairy and poultry agriculture, with an emphasis on  eveloping satellite-driven greenhouse gas benchmarking models for sustainable practices. Previously, Prajesh has worked on projects involving spatial- based crop phenology assessment, agricultural disaster monitoring, and water resource management.

Shubhangi Mahato is a Master’s student in Computer Science at Dalhousie University, Canada (Linkedin). Her interdisciplinary research bridges artificial intelligence and precision agriculture, focusing on non-invasive biometric identification of dairy cattle through computer vision and machine learning. Her thesis, Dairy DigiD, explores AI-powered facial recognition systems for cow identification to enhance herd management and animal welfare. She was selected for and completed the Dal Innovates Lab2Market Launch program in 2024, where she translated her academic research into a potential venture and evaluated its real-world commercial viability. She has showcased her work at both international and local forums, including Falling Walls Lab Atlantic Canada, the MacRae Library Student Research Poster Competition, and Atlantic Dairy Focus 2025. Her work contributes to the development of ethical, scalable technologies for real-world livestock health and behavior assessment.

Venkatraman Manikandan is a Master’s student in Computer Science at Dalhousie University, Canada (Linkedin). His interdisciplinary research bridges the fields of artificial intelligence and precision agriculture, with a focus on decoding poultry vocalizations for animal welfare monitoring. Working at the intersection of natural language processing, acoustic modeling, and sustainable farming technologies, his thesis explores the use of Transformer Models and classical machine learning models. Venkatraman has presented his work at international forums such as Falling Walls Lab Atlantic and was recognized at the national level by Egg Farmers of Canada/ Les Producteurs d’œufs du Canada in Ottawa for innovation in agricultural AI. His work aims to advance non-invasive, scalable tools for real-world animal health and behavior assessment.

Yashan Dhaliwal is a fourth-year undergraduate student pursuing his BSc Bioveterinary Science (honors) degree at Dalhousie Agricultural Campus, Truro  (Linkedin). He began his research journey at Mooanalytica as a Research Assistant in a project that employed AI to detect lameness in dairy cows early on through their facial expressions. In the third year of his undergraduate degree, he published his first research article – “Bimodal Data Analysis for Early Detection of Lameness in Dairy Cows Using Artificial Intelligence” – as first author, a remarkable accomplishment made possible by his dedication, hardwork and appropriate mentorship from his supervisor, Dr. Suresh Neethirajan.

Shreya Rao is a student in the Computer Science Masters program at Dalhousie University, Canada (Linkedin). Her thesis focuses on the development of a Digital Twin system for Precision dairy nutrition which aims to deliver personalized and sustainable feeding strategies for individual dairy cows. By integrating video sensor data, behavioral analytics and metabolic modeling, her work supports real-time decision-making in livestock management and in turn enhances animal health, productivity and environmental outcomes. Shreya has presented her research at academic and public platforms, including the UN SDG Poster Showcase and Dalhousie’s McRae Library Research where her work was recognized for its innovation and societal relevance. Her interdisciplinary approach brings together data science, digital agriculture and animal welfare with the broader goal of advancing scalable solutions for sustainable farming.

Mayuri Kate is a Master’s student in Computer Science at Dalhousie University, specializing in the application of artificial intelligence in agriculture (Linkedin). Her research focuses on understanding cow vocalizations using large language models, aiming to give cows a “digital voice” that can help farmers better monitor animal welfare. She is exploring how AI can detect signs of stress, illness, or reproductive readiness in dairy cows by analyzing patterns in their vocal behavior. She has shared this work in poster competitions, highlighting its potential to transform livestock care through sound-based monitoring. In parallel, Mayuri is also contributing to the adaptation of the Cool Farm Tool in Atlantic Canada, exploring ways to integrate AI for smarter, greener farming practices. Her work contributes to making farms both more intelligent and environmentally sustainable.

Sibi Chakravarthy Parivendan is a Master’s student in Computer Science at Dalhousie University, Canada (Linkedin). His interdisciplinary research focuses on developing computer vision systems for monitoring dairy cows, with a particular emphasis on identifying interactions between cows, constructing social networks, and conducting social network analysis—bridging the fields of precision livestock farming and artificial intelligence. He has presented his work at Dalhousie’s MacRae Library Research Poster Session, highlighting its potential to automate and advance dairy cattle monitoring. As a broader research vision, he is interested in promoting the establishment of standardized benchmarks for cattle monitoring technologies, aiming to reduce stagnation in the field and provide future researchers with a solid baseline to build upon rather than starting from scratch.

Shiv Patel is a Master’s student in Computer Science at Dalhousie University, Canada (Linkedin). His current research focuses on CowPain Check, an AI-based mobile platform aimed at the automated detection of pain in dairy cows through facial expression analysis. His work integrates facial action units, Deep learning models, and explainable AI techniques to improve animal welfare monitoring in real-time farm environments. Shiv’s research contributes to precision livestock farming by offering non-invasive, scalable tools for early pain detection in cattle.

Mackenzie Tapp  is an undergraduate computer science student at Dalhousie University (Linkedin). She began working with MooAnalytica as a co-op work placement. She has worked exploring how to adapt Cool Farm Tool, a European farm carbon footprint tool to farmers in Atlantic Canada. Additionally, she has worked with pose detection models as a part of a larger project about social network analysis with dairy cows. She has presented posters on her research at several events including Dalhousie’s Sustainable Development Goals Expo and The Atlantic Dairy Conference. 

Eduardo Garcia is an undergraduate student in the Mitacs program at Dalhousie University. He is working on an AI-driven digital twin platform for precision nutrition in dairy cows. His research combines computer vision, temporal convolutional neural networks, and dairy nutrition modeling. The work aims to transform everyday barn video into real-time feed optimization and early health alerts, reducing feed waste, greenhouse gas emissions, and metabolic disease, all without the need for wearable sensors.

Harini Shree Bhaskaran, PhD Student (Linkedin) – Digital Twins for Livestock Farming

Alumni  

Shuqiang Zhang, MSc Student & Research Associate, 2025, Exploring how to adapt Cool Farm Tool, a European farm carbon footprint tool to farmers in Atlantic Canada.

Hanqing Bi, MSc Student & Research Associate, 2024 (Linkedin). Utilizing Satellite Data and Machine Learning for Benchmarking Methane Emissions in the Canadian Dairy Industry

Bubacarr Jobarteh, MSc Student, 2024 (Linkedin) – Leveraging Satellite Data for Greenhouse Gas Mitigation in Canadian Poultry Farming

Harini Shree Bhaskaran – MCS Thesis, 2024 – Development of a Cloud-Based IoT System for Livestock Health Monitoring Using AWS and Python (Link) 

Pratik Mukund Parmar – MACS Degree – (Linkedin)

Umang Mehta – MACS Degree (Linkedin)

Christopher Gonzalez – High School Student, Halifax West High School