Applying for UT-Austin Engineering Honors, ECE Honors, Turing Scholars, ECB, and CSB
Stabilizers regulate power from the main electricity line on the street to the circuit box. I learned all about this device after the old, poorly-built one exploded.
I cover the application requirements and competition landscape for the varied engineering and CS honors programs, along with the combined McCombs School of Business ECB and CSB honors. I finish with a brief discussion of honors essay tips and provide three honors essay examples.
The easiest way to reach me is by email kevin@texadmissions.com and to complete this questionnaire for a free email admissions assessment and to discuss pricing and services.
UT-Austin STEM Honors Competition Stats
First, I want to stress that these honors programs are unimaginably competitive. They are comparable to the nation's top STEM programs at Stanford, Princeton, and MIT. Students admitted to these UT Honors programs often get multiple offers from top 20 universities.
When I worked for UT in the early 2010s, back when UT received fewer than 1,000 CS applicants, the admitted Turing Scholars CS honors students still had perfect academics. A statistic from a Turing admitted student information session a few years ago shared that they deny 85% of their valedictorians. It’s exceedingly rare to gain admission to these programs if you rank outside the top 5% of your senior class or have anything less than straight A’s.
Competitive applicants will rank in the top 1% and score a 1550 on the SAT with a 780 or 800 on the SAT math. You must also have an exceptional STEM resume with deep experiences relevant to your major. That means nobody should expect to get into these programs, partly because most of them are also very small, similar to the other College of Natural Science honors programs like Dean’s Scholars and Health Science Scholars.
Most of you are not competitive - regular stem admission is the goal
I have many clients try for these each year, and despite my cautions and warnings that they are highly unlikely to get in, they apply anyway “just to see if they get in.” Then they’re devastated about inevitably not gaining admission, which distorts their benefits and gratitude for at least getting into regular CS or ECE, which also have admissions rates below 10%. So, there can be real emotional and psychological downsides to applying for honors when it’s likely out of reach. At the risk of sounding overly discouraging, most of you shouldn’t even bother applying to these CS and engineering honors programs. Nevertheless, applying for honors has no impact on regular admissions chances.
honors is one of many ways to have productive ut education
Honors is just one way among many to succeed. Honors also isn't a guarantee of success. UT-Austin is a world-class institution where you can receive a great education that opens doors for your future. The effort you put in, your motivation to push your boundaries, and the network you create matter more for your success and well-being than whether you're in honors or not. If you are not offered admission to a Freshman Honors program, there are many options after you arrive on campus especially when you finish your first year.
How to apply to UT-Austin Engineering Honors, ECE Honors, Turing Scholars, ECB, and CSB
Engineering Honors is the most straightforward. Refreshingly, they do not require any additional essays or requirements. You simply check the box on the Common App, and any applicant who selects an engineering major as their first choice is eligible.
At least in previous admissions cycles, Engineering Honors used a mechanical process based on the Office of Admissions scores to admit their students. Engineering Honors has always waited until the Office of Admissions finishes their admissions review and outcome distribution process. Basically, they admit the top ten percent or so of admitted Cockrell engineering applicants, perhaps with some distinction for the applicants' first choice major so that there is some major diversity within the program. They also offer scholarships to many, or perhaps all, of admitted Engineering Honors students.
Applicants who select Electrical and Computer Engineering as their first-choice major are eligible for both Engineering Honors and ECE Honors. If they select Business as their second choice, they can apply for the combined ECB honors program. Of all the UT Honors programs, Engineering Honors and ECE Honors make the least difference for the student experience.
Unlike the more involved Plan II, Business Honors, or Dean’s Scholars, ECE and Engineering Honors have few course or curriculum requirements. Some of my ECE clients get into ECE Honors but not engineering honors, and others get into engineering honors but not ECE honors. I honestly don’t know why there is a discrepancy other than to say that decisions are made from separate honors offices. The offices also do not coordinate when they release decisions, with most offers coming out at the end of February.
Like ECE Honors, Turing CS Scholars also doesn’t make a significant difference for the student experience. I find that families place a hugely disproportionate weight on honors admission or not, which is unfortunate because more than 95% of Turing applicants will get denied. Then they feel disappointed about the non-honors UT CS offer. Nevertheless, if you wish to be eligible for Turing, you must select CS as your first-choice major.
I will discuss the combined ECB and CSB honors programs since they have identical requirements. CSB was created about a decade ago, and ECB more recently. Students in these programs complete the Business Honors major and take case-study-based classes. You can select business first and CS or ECE second and vice versa, but you should select the first choice major that you most want. If you don’t get business or CS as your first choice major, you won’t get the second choice either because CS, business, and ECE are never given as a second major.
ECB and CSB are arguably the most competitive honors programs, partly because the applicant pool is the strongest among any program. Many students have deep, dedicated experiences in business OR STEM, but very few have both. You need exceptional national and international-level accomplishments in both areas. Many of my clients get into Turing, Engineering Honors, or ECE honors, but I have only one or two who have a realistic shot of getting into CSB or ECB each year. I’ve only ever had one student admitted to them, an ECB client in Fall 2025.
UT-Austin STEM Honors Essay Tips and Examples
The prompts for Turing, ECE Honors, ECB, and CSB is basically the same. You have 500 words to share about your relevant experiences and how these honors programs can help you achieve your goals:
Describe your significant activities, employment, and achievements, particularly those relevant to the study of computer science. Also describe your educational and career goals.
The most important thing is to not overlap too much with your regular admissions essays since the Honors departments will have access to your common app. However, since the honors departments review each of their programs separately, it’s okay for there to be overlap between your Turing and CSB honors essays or the ECE and ECB essays.
Your honors essays must add new information beyond the regular admissions essays.
Either develop different experiences not mentioned elsewhere or provide other angles to experiences discussed in the Common App. Since these apps are read by honors staff rather than the more general Office of Admissions, it’s okay to dive deep into technical processes and utilize jargon. You can expect that your readers will have some background technical familiarity.
Your honors essay should utilize a “stick to the facts” approach rather than the storytelling with rhetorical devices approach that’s more appropriate for your Common App main essay. Your objective is to argue convincingly that you have the experiences and aptitudes to excel in UT honors classes and that you will contribute to the honors communities.
UT turing Honors Essay Example (Princeton CS RD Admit)
I attended my first hackathon, TAMUHack, during my junior year with two other teammates. We coded an innovative learning platform in 24 hours and pitched it to judges. Features allowed students to upload lecture videos and receive a suite of learning tools. These tools include condensed notes, practice quizzes, and a Q&A bot trained on the video's context.
Despite my prior focus on front-end development and Java, I quickly learned new programming languages, including Python and ReactJS. Learning Python quickly and only from the documentation was challenging yet extremely rewarding. Additionally, I learned how to integrate GPT-3 into our project, curating prompts that generated quizzes and notes in a JSON format. I also employed Flask to send server requests and render the generated content to the front end.
Building the project’s frontend posed a challenge. Although I understood web development using HTML, CSS, and JavaScript, we opted for React JS for Tutor AI’s front end. With the help of mentors and online tutorials, I helped build a fully functional website. We presented Tutor AI to the judges, explaining its goals, different tech stacks, and potential impact. We won the best beginner hackathon project among over 800 participants. This experience taught me how to implement a variety of programming languages and technologies while introducing me to varied CS disciplines and fields like AI and FinTech.
My next hackathon experience was at KleinHacks. Four teammates and I competed in the AI category and developed an intelligent AI grader called IntelliGrade AI. We designed it to help users improve essays, product pitches, advertisements, and other types of content. Users upload any content onto the website and either upload a rubric, the intended audience of the content, or the material’s purpose. IntelliGrade AI provided suggestions to improve the content and assign it a numerical score. We tinkered with the GPT-3 API until it worked reliably.
My previous experience in TAMUHack helped with integrating Flask into our project to make server requests. My primary responsibility involved creating a frontend with a seamless user interface, which I built from scratch using an unfamiliar Python-based framework called Pynecone. Navigating the documentation led to many dead ends, but I leaned on my teammates to help lay out the site design and implement our vision in Pynecone. We earned first in the AI category and first overall.
These hackathon experiences, involving both frontend and backend development, have provided me with a well-rounded understanding of CS. At UT, I hope to continue my computer science studies to master full-stack development, computer algorithms, and the theoretical subsets of CS. I hope to pursue an AI and machine learning career to help develop innovative solutions that address real-world challenges. CS classes like Practical Machine Learning and Competitive Programming will complement undergraduate research through the Machine Learning Lab and the TAUR Lab. I’m excited to explore statistical machine learning and natural language processing to prepare me for my future career.
UT turing Honors Essay Example
My first task in Dr. T’s Lab required converting Per4ML Lab’s generated CSV data into an organized HDF5 format, using YAML configuration files. I also analyzed code from the lab’s GitHub repository that produced a low-end visualization and learned the Plotly library to produce clean and functional UIs in Python.
During my sophomore year, I identified correlations in T Lab’s massive datasets by implementing UC Riverside’s Dr. Ver Steeg’s LinearSieve machine learning algorithm. We read Dr. Ver Steeg’s research papers and Python scripts to understand how to pipeline datasets to the algorithm. After generating results, I used NetworkX and Matplotlib libraries to produce informative Node Graph and Parallel Coordinates visualizations. I color-coded for identification and adjusted line thicknesses/node sizes to demonstrate the magnitude of correlations within the data. We compiled these visualizations in a poster presentation for TXST’s REU program.
During the following summer, we collaborated with ABC Laboratory’s Dr. W, the subject-matter expert, to analyze correlations in Dr. T’s data using Circos. This visualization typically displays genomic similarities, where data bins are arranged in a circle connected by chords to highlight correlations.
However, apart from the Plotly documentation for Circos, we found few third-party resources online. I developed a basic understanding of the documentation and created a rudimentary visualization before implementing specific features to improve my visualization. I worked directly with Dr. W, who provided precise, constructive feedback to tweak the visualization, redefine our bins, and adjust the chord width to represent correlation magnitude. We submitted a research paper and poster with our results to the SC23 international conference.
Afterwards, I created a UI that eased interaction with LLMs by allowing users to upload CSV data to a chosen model, enter queries about their dataset, or select a pre-programmed option to summarize their dataset. I learned the CUDA/Pytorch and Transformers tools but encountered novel memory-storage errors. To resolve this, I wrote my code in the unfamiliar Jupyter Notebook and Google Colab software.
This past summer, I fine-tuned LLMs to better respond to queries regarding high-performance computing. I built pipelines to scrape research papers and manuals from Intel, IBM, and Nvidia from Arxiv, Google Scholar, and Google Search Engine. I conducted prompt engineering by inputting the documents into Llama 3 to generate datasets with questions, relevant keywords, context, and answers. Using these datasets, I finetuned Llama, Bert, and GPT LLMs, implementing Quantized Low-Rank Adaptation for optimization. I evaluated the finetuned LLMs using Natural Language Processing metrics like BLEU score. Currently, I am collaborating with Dr. T and her team to compile our findings in a research paper.
I am excited to enroll in Turing because I can collaborate with experienced doctoral candidates and professors conducting cutting-edge research. A smaller program within the larger university will help me make friends, build community, and form relationships with professors beyond my undergraduate degree. My long-term goals are to apply my ML skills and make autonomous software like self-driving cars smarter and more useful.
UT ECE Honors Essay Example
I have been interested in Artificial Intelligence since middle school when I took an introductory course in AI through the Duke Talent Identification Program. Afterward, I completed another two AI courses from IBM and Veritas AI. At school, I completed Computer Science 1 (Python programming), Computer Science 2 (C++ programming), and Computer Science 3 (Python data science). Since my school does not offer it, I self-studied and passed the AP Computer Science A (Java programming) exam.
I also sought opportunities to deepen my knowledge in specific areas of interest, such as space exploration and engineering. I completed the following courses through Johns Hopkins CTY: Colonizing Space: How to Build an Extraterrestrial City, Everything is Connected: Solutions for a Warming World, Engineering Design, and Aeronautical Engineering. Afterward, I explored AI applications in engineering areas like robotics, aircraft, and space exploration.
Since AI is becoming essential in many areas of engineering, such as robotics, aircraft, space exploration, and many others, I started to explore its applications. This led me to complete three research programs. I conducted original research on AI applied to astronomy, where I created machine learning algorithms in Python to identify and classify stars and quasars.
Then, I explored my AI interests by utilizing reinforcement learning as an end-to-end controller for autonomously controlling a drone. Recently, I became interested in AI image recognition technology. I'm conducting original research on deep learning applied to computer vision, developing and training a deep learning model to estimate objects' depth from a flat image accurately.
This summer, I participated in the NASA STEM Enhancement in Earth Science (SEES) Internship, where I analyzed satellite atmospheric PM2.5 pollution data and public transit data. I created Python scripts to investigate the impact of public transportation on urban air quality in five cities, determining the correlation between PM2.5 and transportation variables for each city.
I’m excited about the opportunity to take courses like ECE319H Introduction to Embedded Systems Honors to learn to develop the software of electronic components of complex systems employed in many industries, including automotive and aerospace industries, ECE370N Introduction to Robotics and Mechatronics to learn about actuators, sensors, adaptive control, and vision and pattern recognition, and ECE361E Machine Learning and Data Analytics for Edge Artificial Intelligence, to learn how to implement deep learning on edge devices, such as autonomous vehicles.
I'm interested in conducting research in UT’s Center for Autonomy’s Control and Learning for Autonomous Robotics Group. It includes scientists, electrical, computer, and aerospace engineers, and undergraduate students who work together to design high-performance interactive autonomous systems that involve robotics, control theory, machine learning, and game theory.
Finally, I hope to graduate with a Robotics Minor and to pursue the Integrated Bachelor of Science/Master of Science in Engineering program to earn my bachelor's and master’s in five years while writing a thesis.