Jacob E. Chandran

Founder, Software Engineer

• Founded a personal software company specializing in educational applications of AI and custom AI systems.
• Fine-tuned large language models using parameter-efficient techniques including LoRA, QLoRA, DoRA and PEFT.
• Designed, built and deployed custom AI systems end to end, from data preparation and model fine-tuning to production deployment.

Software Engineer · Wilmington, DE

• Designed, built and maintained event-driven backend services using Apache Kafka and Python for real-time data streaming.
• Developed front-end applications in ReactJS integrated with Python backend services.
• Owned the full software development lifecycle: design, implementation, code review, testing and production deployment on Linux.

Machine Learning Intern, Software Engineer Program (SEP) · Wilmington, DE

• Designed, coded and tested new software to create Natural Language Processing solutions in the Business Intelligence and Autolytics division.
• Implemented an internal question answering service that converts user questions into SQL scripts; generated queries interface with the database to return text and graphical representations to the user.
• Applied Natural Language Processing with TensorFlow to convert text to SQL, ReactJS for the user interface, and Flask for a web framework with endpoints accepting user input from the website.
• Worked with distributed (multi-tiered) systems, algorithms, relational databases and object-oriented design, implemented in Java on Linux.

Computer Science Research Intern, International Science Institute · Israel

• Used MATLAB and ImageJ to map rod and cone photoreceptor structure in the mouse retina from two-photon calcium imaging data.
• Built MATLAB (Toolbox-3) simulations of retinal response to six visual stimuli, mapping receptive fields and temporal kinetics of retinal cells to compare cell subtypes.
• Developed MATLAB and ImageJ analysis pipelines to visualize cellular activity and segment retinal cell structure from microscopy images.
• Presented research findings and won the best research paper award.

Machine Intelligence Intern, ASPIRE Mentoring Program · Laurel, MD

• Trained in DeepLab for medical image segmentation and TensorFlow for deep convolutional neural networks, tuning CNN feature extraction to improve image classification accuracy.
• Installed and tested DeepLab (on Caffe) for medical image segmentation, and TensorFlow and Keras for image classification to detect age-related macular degeneration.
• Completed computer vision project “Effect of Visual Attributes on Classification Accuracy of Zero Shot Learning”.

B.S. Computer Science

Volunteer Teacher, Math and Physics · India

• Taught Mathematics, Science, Music (Piano) and Basketball to students in grades 2–12.
• Tutored and mentored students in grades 2–8 in Mathematics, Science, Music (Piano), Sports and extra-curricular activities.
• Presented a seminar on Neural Networks to high school students.