Mr. Lalit Ashutosh

Associate Professor

Lalit Ashutosh is currently working as an Assistant Professor in the Department of Artificial Intelligence & Robotics, School of Engineering, Dayananda Sagar University, Bengaluru. He has completed his M.Tech in Information Technology from IIIT Allahabad, with a strong foundation in software development, robotics, and machine intelligence. He holds a B.Tech in Mechanical Engineering from Madan Mohan Malaviya University of Technology, Gorakhpur.

His research interests span Generative AI, Robotic Manipulation, Diffusion Models, Multimodal Learning, Medical AI, and Intelligent Systems. His postgraduate research focused on robotic grasp detection using diffusion-driven approaches. He developed a framework integrating a modified ResNet-50, UNet-based diffusion models, and physics-informed layers to achieve high-accuracy grasp prediction from RGB images.

His teaching interests include Machine Learning, Deep Learning, Computer Vision, Artificial Intelligence, Data Structures and Algorithms, Object-Oriented Programming. He previously served as a Teaching Assistant at IIIT Allahabad for courses such as Machine Learning, Deep Learning, and Computer Vision.

He has gained a well-rounded mix of industry and research experience across both corporate and academic settings. During his time at Cognizant Technology Solutions, he worked in the domain of software quality assurance for large-scale web applications. His responsibilities included designing and implementing test strategies, ensuring application reliability, and contributing to efficient deployment cycles. This experience enhanced his understanding of enterprise-level software systems, agile methodologies, quality control processes, and the importance of robust testing in modern software development pipelines.

Mr. Ashutosh has a strong command of core programming languages such as Python, C++, and Java, with applied knowledge in both software development and artificial intelligence. He is skilled in building machine learning models, developing intelligent applications, and implementing full-stack systems using modern technologies. His experience includes deep learning, diffusion models, computer vision, natural language processing, and backend development. He is also experienced with frameworks and platforms relevant to AI deployment and experimentation. In addition to his technical abilities, he has a solid understanding of software engineering principles, version control, and collaborative development practices. His skill set reflects a versatile profile suitable for research, teaching, and the development of real-world AI applications.