Company Team And Maturity
Team Bios
Natan Vidra - Natan studied Electrical Engineering and Computer Science at Cornell, and worked as a Data Scientist / Software Engineer in Deloitte's Applied AI division. At Deloitte, Natan collaborated on a variety of AI / ML projects in the domains of NLP, Computer Vision and Big Data Analytics. Natan wrote the Deloitte Prompt Engineering Guide, and led the execution for ReadyAI, helping enterprise AI clients such as the IRS, DOD, and NIH go from 0 to 1 in their AI journey.
Anya Ross - Anya Ross is a Computer Science student at Cornell University. She combines technical expertise with problem-solving abilities critical for complex machine vision tasks. Her skills in software development and algorithmic thinking are valuable assets for the Navy's image processing requirements.
Neha Naveen - Neha Naveen is a Computer Science student at Cornell University. She brings strong programming skills and analytical thinking to the image object detection project. Her technical foundation makes her well-suited for developing robust object recognition algorithms needed for naval applications.
Deep Bench of Personnel
Ani Jain - Ani Jain is a Computer Science student at Cornell University with experience in software development. His technical background includes work with machine learning frameworks and programming languages essential for computer vision applications. Ani brings innovative approaches to the image object detection challenges faced in naval environments.
Wesley Zeng - Wesley Zeng is a Computer Science student at Cornell University specializing in algorithmic development and data structures. His technical skills include programming proficiency and experience with computational problem-solving methods applicable to object detection systems. Wesley's analytical abilities contribute significantly to the Navy's image recognition requirements.
Alan Zhao - Alan Zhao is a Computer Science student at Cornell University with strong fundamentals in software engineering and algorithm design. His programming expertise and analytical skills are particularly relevant to developing efficient image processing systems. Alan's technical capabilities enhance the team's ability to solve complex object detection challenges for naval applications.
Mohamed Zakaria Kheder - Mohamed Zakaria Kheder is studying Electrical and Computer Engineering at Cornell University. His background combines hardware knowledge with software implementation skills critical for deployment-ready vision systems. Mohamed's interdisciplinary expertise addresses both the algorithmic and practical implementation aspects of naval image recognition systems.
Collaborations With Cornell Autonomous Systems Labs
Daniel Lee - Daniel is a professor at Cornell Tech and a researcher at Cornell Autonomous Systems Labs with expertise in computer vision and object detection algorithms. His work focuses on developing robust vision systems for autonomous applications relevant to the Navy's image processing needs.
Eduardo Castillo - Eduardo specializes in deep learning approaches for object recognition in challenging visual environments at Cornell ASL. His research directly applies to the maritime object detection requirements of the Navy project.
Zwee Dao - Zwee brings expertise in efficient neural network architectures and deployment on limited-resource platforms. His work enables real-time object detection systems that can be deployed in naval environments with computational constraints.
Eva Esteban - Eva's research at Cornell ASL focuses on multi-modal sensor fusion for improved object detection accuracy. Her approaches combining visual and other sensor data significantly enhance detection reliability in variable maritime conditions.