Viren Velacheri
Ace College Admissions with a University of Texas at Austin Honors Graduate
Studied at Carnegie Mellon
Works at Cvent
Available tomorrow at 10:30 AM UTC
Questions? Start chatting with this coach before you get started.
Viren's Offerings
Custom hourly · $79/hr
Get help with Application Strategy, Editing, and .
Viren also coaches for Master’s Programs and MBA. View all.
Viren’s College Qualifications
My approach to coaching comes from lived experience, not theory. I recently navigated the graduate admissions process and earned offers from the following top programs: The University of Toronto Masters of Science in Applied Computing, Carnegie Mellon Master of Science in Artificial Intelligence Engineering, Columbia Dual MBA/Executive MS: Engineering & Applied Science, UC Berkeley Electric Engineering & Computer Sciences Master of Engineering, and Carnegie Mellon Master of Science in Machine Learning program. I have confirmed my decision to attend the Machine Learning program at Carnegie Mellon this fall. Before that, I graduated Summa Cum Laude from UT Austin with a 3.96 GPA in Computer Science. I know firsthand what it takes to build a compelling application because I have done it across both technical and business programs. My strength is narrative strategy. I help you identify the through line in your experiences, position your story for the specific program type you are targeting, and write essays that are punchy, defensible, and free of inflated claims. Beyond admissions, I bring real-world credibility as someone that has worked at startups, big companies, and nonprofits as well as research experience. I will give you honest assessments, not validation, and I will work with you draft by draft until every word earns its place.
Viren can help with:
Application Strategy
Editing
Essays
General Exploration
Interviews
Recommendations
Resume
School Selection
Secondary Review
Supplementary Materials
Viren also coaches for Master’s Programs and MBA. View all.
About Viren
Here is something most people do not learn about me right away: I was born deaf, and no one caught it until a chance family trip to India when I was five. A surgery gave me my hearing, but it did not give me confidence. I was the quiet kid who got picked last at recess. Soccer changed that. I found I had a feel for the ball, kept at it, and eventually became the player my teammates looked for. That pattern has repeated my whole life. I get pulled toward things that scare me a little, then chip away until they feel like mine. It is why I joined Toastmasters as a nervous speaker and stayed long enough to lead clubs. It is why I started a company. Away from work, I am a fitness and basketball person at heart, and I do my best thinking on a run or at the hoop. If you have ever felt like the underdog, we will get along.
Why do I coach?
I coach because the right people showed up at the right moments. A soccer coach who rebuilt my game, a teacher who pulled me out of my shell, and family who pushed me toward rooms that scared me. None of them flattered me. They told me the truth and believed I could grow, and that combination is what moved me forward. I try to be that person for you. Most coaching promises encouragement, but what actually helped me was honest, specific feedback from someone in my corner. So that is what I give. I will tell you when an essay is not working yet, show you why, and stay with it until your story is sharp and unmistakably yours. Admissions can make you doubt whether you are enough. My job is to remind you that you are, then help you prove it on the page.
Work Experience
Founding Engineer
Paloa Labs
March 2026 - Present
* Designed and shipped a multi-model video understanding pipeline combining a three-pass VLM approach with Claude and Kimi K2.5, YOLOv8 ball trajectory tracking, ByteTrack player re-identification, and scoreboard OCR cross-validation. * Reduced processing cost and latency to roughly $2.60 and 21 minutes per one-hour game, making full-game analysis affordable at scale. * Built internal annotation tooling and benchmark datasets to evaluate detection accuracy across the pipeline. * Led technical strategy and research partnerships, including advisor outreach to computer vision faculty at UT Austin.
Area Managing Director
Toastmasters International
June 2025 - June 2026
- Lead and support a network of 7 Toastmasters clubs to achieve communication and leadership excellence - Conduct regular club visits to assess performance and provide strategic guidance - Facilitate club officer training sessions to enhance leadership capabilities - Organize area-level speech contests to boost member engagement and visibility - Collaborate with district leadership to mentor club officers and foster growth - Monitor club progress toward Distinguished Club Program (DCP) goals - Strengthen the overall member experience through personalized support and resources
Research Associate
ThirdAI Corp
December 2024 - July 2025
• Assessed the performance of current RAG pipeline flow and created a few different benchmarks • Documented findings and trade-offs to inform architecture decisions to make retrieval mechanism more accurate • Designed three structured benchmark categories for retrieval evaluation, covering single-document, multi-document single-answer, and multi-document multi-answer scenarios. • Curated custom datasets of varying difficulty to simulate real-world retrieval behavior and improve robustness of evaluation. • Implemented custom retrieval quality and latency metrics to establish quantitative baselines and identify systemic weaknesses. • Conducted comprehensive evaluation of eight transformer-based Named Entity Recognition models, analyzing precision, recall, F1 score, and CPU inference latency under strict <10 ms constraints. • Trialed, compared, and documented the performance of BERT-based and other transformer architectures for NER and retrieval-heavy workflows. • Self-hosted and tested vision-language models to evaluate document processing workflows, identifying bottlenecks and proposing improvements. • Authored detailed technical reports synthesizing design trade-offs, benchmark results, and architectural recommendations used in internal decision-making. • Contributed original ideas and proposed enhancements to the retrieval and document-processing pipeline, collaborating closely with senior researchers. • Delivered all contributions while managing a demanding full-time engineering role, demonstrating strong initiative, discipline, and technical curiosity.(Python, MLflow, NeuralDB, Notion) Python and MLOps
Board Member and Audit Committee Member
Learning Bridge
November 2024 - Present
- Collaborated with fellow committee members to successfully raise over $50,000 in donations during the 2023–2024 fiscal year. - Designed and implemented a centralized database to streamline data management by consolidating information from multiple spreadsheets. - Conduct daily outreach efforts to individuals—including friends, family, and community members—for fundraising, volunteer engagement, and program support. - Assist in writing and reviewing grant proposals to secure funding from foundations and partner organizations. - Actively attend and support organizational events, contributing to planning, coordination, and day-of execution to ensure community engagement and program visibility.
Software Engineer 2
Cvent
August 2024 - Present
• Architected cross-service optimization reducing system latency by 35% and cutting incident recovery time by 50%+ through Datadog monitoring. • Doubled team productivity using AI frameworks; selected by management to join principal engineer-led team of 2 for feature initiative impacting 10K+ users. Datadog, Spring Boot and +3 skills
President
Toastmasters International
June 2024 - July 2025
- Lead a diverse group of 30+ individuals and facilitate weekly meetings. - Come up with new ideas/objectives to bolster standing of the club
Student Researcher
University of Texas Austin
February 2024 - July 2024
• Analyzed dynamic communication network optimization techniques, including multi-objective genetic algorithms, deep reinforcement learning, and graph neural networks (GNNs). • Authored detailed analytical mappings of data-flow, equations, and optimization trade-offs, proposing improvements for scalable real-world deployments (e.g., 5G, Starlink) and outlining a hybrid RL + GNN optimization framework.
Vice President of Public Relations
Toastmasters International
July 2023 - June 2024
- Publicized club weekly on social media platforms (LinkedIn, Facebook, Youtube, etc) and prepared daily newsletter. - Boosted club membership by 25%
Software Engineer
Cvent
August 2022 - August 2024
• Project: Architected changes in PostgreSQL that improved data consistency between legacy and new service databases by over 20%. Implemented multiple REST API endpoints for the use of 1,200 early adopter clients. Developed some of the latest user-facing components and features that helped improve front-end performance by 15%. Tuned multiple SQL stored procedures to improve execution time by almost 50%. Conducted unit and integration test refactoring that increased total coverage by 10%. (Spring Boot, PostgreSQL, React, C#, Couchbase, Postman, Mockito, Karate, Selenium, Datadog, Splunk) Spring Boot, React.js and +15 skills
Supplemental Instruction Leader
University of Texas Austin
August 2021 - May 2022
Every week I held 2 one hour sessions where I come up with different lesson plans based on what the students learned the previous week. I was the SI Instructor for the CS 314 Data Structures class, one of the intro courses in the UT CS program
Software Engineer Intern
Cvent
June 2021 - August 2021
Project: Developed REST API endpoints for a service that impacts 21K+ users. Created and optimized SQL queries to improve performance of some of the back-end features by over 30%. Built a React app that was launched to 1,200 early adopter clients. Wrote 10+ unit and integration tests. (Spring Boot, PostgreSQL, React, Postman, Mockito, Karate, Selenium, Splunk)
GPU Power and Performance Engineer Intern
Samsung Semiconductor
June 2021 - August 2021
• Project: I developed Python-based power analysis automation suite, reducing report generation time by 40% and improving consistency across runs. Cut the analysis time that is typically dependent on a bunch of manual commands being run from 3 - 4 hours to 45 minutes ( 78%). Learned a lot about pre-silicon power measurement, power analysis, and optimization across GPU systems
Undergraduate Teaching Assistant
University of Texas Austin
August 2020 - December 2020
I was a teaching assistant for Computer Architecture class. Held office hours twice a week to help out students with assignments, lectures, etc and hosted a weekly discussion section as well. Helped in grading tests, quizzes, and assignments as well as in creating daily practice problems for students.
Software Engineer Intern
University of Texas Austin
June 2020 - December 2020
• Project: Led and developed mobile DevOps pipeline from scratch for COVID-19 tracking mobile phone app (called Protect Texas Together) where over 10K+ people downloaded it from both Google and Apple Stores. Implemented some of the user-facing functionality as well. (Bitrise, Fastlane, React-Native, Django)
Fellowship
University of Texas Austin
June 2020 - August 2020
Worked on creating a medical device scanner with a Raspberry Pi that can sniff the network and get an inventory of all the medical devices in the network for a healthcare provider (hospital, clinic, etc). Wrote a Python script that gets an inventory of all the devices on my network and creates a spreadsheet listing their details (IP addresses, MAC addresses, vendor/company details, and the name of the device).
Software Developer Intern
iHeartMedia
June 2019 - August 2019
Project: Built a cloud-based internal reporting system in Java’s Spring framework with 3 other interns that was based on statistics related to 800K+ artists. Involved creating multiple REST API endpoints and the utilization of AWS Simple Queue Service, Microservices, and an SQL database. Pioneered idea of creating a sleek user-friendly interface for S3 bucket that holds the generated reports. New system performed 50% better than legacy system. (Spring Boot, AWS Simple Queue Service, AWS Microservices, SQL, AWS S3)
Education
Carnegie Mellon
Master of Science, Machine Learning
2027
University of Texas at Austin
Bachelor's degree, Computer Science
2018 - 2022
Grade: 3.9641 Activities and societies: President's Award for Global Learning, ISSS (Information and Systems Security Society), ACM (Association of Computing Machinery), Supplemental Instruction Program Leader Graduated with Honors (Summa Cum Laude) with a concentration in Machine Learning and Artificial Intelligence
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