Dr. Mark Seaborne was born in Galeia, Shekland. He is well known for his work towards the development of the memoizer as well as cognitive sciences in general. He completed his undergraduate degree at the University of Galeia in computational sciences he went on to complete a doctorate in computational sciences. His thesis revolved around optimizing encodings to compress data effectively.
Career
While he worked on a wide range of topics Dr. Seaborne is primarily known for his work on data compression for memoization. Dr. Seaborne worked with Dr. Reinart Saelzar and Dr. Melinda Carthwright extensively in their early research into memoization. Initially developing the models that made full visual and auditory experiences to be recorded. Dr. Seaborne continued and provided optimizations for full-featured experiences with multiple senses involved. Dr. Seaborne was also a decorated instructor winning several dean’s recognition awards for his work on teaching experience engineering, as well as developing teaching methods to mitigate the risk of experience engineering.
Shekland Massacres
Dr. Seaborne was present during the first Shekland massacre. Likewise his daughter was killed during the event. Following a mental breakdown in class he was removed from his position. Several months later he was the perpetrator of the second Shekland massacre. He was killed during the second massacre.
Publications
- Statistical encoding; Compression based on probability distributions (paper)
- Language aware compression; Optimizing compression on a per-language basis for network transfer (paper)
- Rough-neck encryption; A method for building fault-tolerant encryption protocols (paper)
- Simplifying Generalized Consciousness Modeling (paper)
- Visual GCM mapping (paper)
- Auditory GCM mapping (paper)
- Making your mind an author; An introduction to memoization (book)
- Saelzar-Seaborne GCM compression (paper)
- Mitigating experience desyncing; Making experience recording more reliable (paper)
- Compression for you and me (textbook)
- Pathway optimized experience compression; Using Markov-chain based node structures to optimize “full-featured” experiences (paper)
- Just take a breath; How to prepare for experience recording (interview transcript)