About

Lukas Mueller

I love computer science and STEM, and am always trying to push the limits of my own skills. Recently I graduated Summa Cum Laude with a degree in Computer Science, and decided that it would be worthwhile to pursue a concentration in software engineering as well. During my education I gained significant experience producing functional code using a variety of programming languages. I learned how to create applications that interact with relational or non-relational databases, implement data structures to optimize for time-complexity or space-complexity, perform code testing using a variety of methods, and create secure code that addresses common vulnerabilities and adheres to coding best practices. I also learned how to perform database analysis, implement data visualization, and produce informational artifacts that are essential to collaboration in the software development lifecycle, systems design, and requirements driven development.

My favorite subject matter includes work related to artificial intelligence or data sciencem, so creating an AI-driven database-linked data-visualization dashboard seemed inevitable. However, I think its crucial to recognize that the areas which are fundamental to my discipline are actually the most indispensable and transferable for any of my future endeavors. Using this criteria, the three most important areas of focus during my computer science degree were software design and engineering, algorithms and data structures, and databases. Specifically, the skills I believe to be the most valuable were requirements analysis, analysis of code for time and space complexity, and database management. While these skills are sometimes auxiliary to computer programming, they are crucial to the development of software that is useful, efficient, and dynamic.

My expected career is closely tied to computer science, as my intention is to become a machine learning engineer. In addition to what was learned in Current and Emerging Trends in Computer Science: Artificial Intelligence, I have pursued additional related education above and beyond what was learned at SNHU. In such a career I will need to be able to effectively manipulate large data sets, create documentation that clearly conveys essential information, and implement software design approaches that efficiently address project requirements. My current career plan involves obtaining a MS in Artificial Intelligence or Data Science, while opportunistically augmenting my skills with extracurricular efforts or employment-based projects. The advancement of my own knowledge and experience should inevitably lead to a career where I can apply my skills to the advancement of human knowledge, preferably in the STEM fields.

While I intend to specialize in machine learning, I will be exposed to the wider field of artificial intelligence, of which machine learning is a single subcategory. As a computer scientist, I have learned that the methods used to solve a problem should be chosen based on their efficacy and efficiency. I will continue to hold these values while studying artificial intelligence, and will use my knowledge to make more intelligent decisions when selecting approaches to solve modern problems in the fields of computation, technology, and science.

Early in life I was accepted to UCSD where I studied cognitive science. I also gained a strong foundation in STEM related disciplines such as physics, chemistry, biology and mathematics, with almost no emphasis on computer related disciplines. Due to numerous antagonistic circumstances, I was unable to finish my degree. Before returning to school I came to a conclusion that I had not thought of during my earlier years: in the modern era, most significant advancement of human knowledge in STEM fields will require the use of advanced technologies and methods. Even then, I envisioned using tools such as artificial intelligence to bring greater clarity to data rich disciplines such as biology and neuroscience. However, someone like myself would need to develop a strong foundation in computer science to be able to make substantial contributions in this way. While getting an AS in IT Management (Computer Science was not offered as a degree at my local community college), I began to focus on computer programming, finding the most satisfaction in creating applications that could be used by people that did not know how to code. After graduation I began to pursue a BS in Computer Science at SNHU, eventually adding a concentration in Software Engineering. Throughout the program, I was amazed to discover that computer science involved many different aspects which could lead to the production of quality software that was more robust, efficient, secure, and valuable to potential users. The lessons I have learned have helped me to become a better developer, not only because of the refinement of raw technical skills, but also because I have gained a better understanding of what I should value in a software solution. While my perception of software engineering has evolved from brute force efforts to get code running to thoughtful and efficient application of meaningful strategies, I still have a strong desire to create artificially intelligent software that helps to advance scientific knowledge and STEM fields. During my education I have gained additional knowledge about artificial intelligence through online learning platforms, and now have a better understanding of the variety of methods and approaches used by machine learning engineers. While such means and methods are admittedly complicated, I have not been deterred from my long-term goals. I suppose that the biggest difference in my perception about the direction of my future efforts is that I once thought that I would use AI solutions to personally make discoveries in science, but I now realize that making tools that other scientists can use to make such discoveries is more than adequate. Part of the power of well made software is that it can empower other people to accelerate their own efforts. My original goal was to make significant contributions to the sciences using advanced tools, but I am starting to realize that any such advancements do not need to recognize me, personally, for my goal to be realized. It is enough to serve others by creating software that can be used to facilitate discovery and good works. That being said, after graduation I plan on pursuing a MS in AI or Data Science, in order to sharpen my skills for my chosen career as a Machine Learning Engineer. Until I am sufficiently skilled, I plan on pursuing employment opportunities related to software engineering and development, but will also be qualified for jobs involving IT administration and security. I am not presently focused on maximizing my career earnings, but am more concerned with acquiring the knowledge and experience I will need to be a quality AI engineer. Ultimately, the most limited resource is always time. I look forward to a long and rewarding career in a field that has the potential to make revolutionary advances in a wide variety of disciplines.

Here is a glimpse of just some of my skills and accomplishments:

Data Science

Information Security

Other noteworthy IT

You can find the source code for Jekyll at GitHub