Thejas B U
As an AI Software Engineer, I am driven by a deep ambition to achieve mastery in complex technical domains, approaching challenges with a logical and determined mindset. I thrive on autonomous problem-solving, constantly seeking to refine my skills and deliver innovative, high-quality solutions.
Experience
AI Software Engineer
Saigeware Technologies · Feb 2023 – Present
- Developed a cohort of 120,000 cardiovascular and cerebrovascular patients from Mayo Clinic's EMR database, resulting in 310,000 admissions.
- Utilized SQL to implement inclusion and exclusion criteria aligned with business requirements.
- Developed an XGBoost-based readmission risk model with ~82% accuracy and precision (0.74) and recall (0.75).
- Significantly outperformed LACE plus scores in predicting both short-term (30-day) and long-term (6-month) readmissions.
- Developed an alert system to monitor patient vitals and detect out-of-range values using a window-based outlier detection algorithm.
- Implemented automated notifications to alert patients and providers of abnormal readings.
- Developed a baseline risk prediction model using phenotypic markers from GT+.
- Trained the model with TensorFlow and XGBoost to predict patient susceptibility to specific risks based on collected marker
- Developed physical and mental wellness scores by integrating health data (steps, calories, SPO2, heart rate, HRV, and voice).
- Utilized fuzzy logic algorithms to model and quantify wellness levels.
- Designed a risk clustering model to determine the main causes of hearing loss and tinnitus in patients.
- Implemented a separate model to predict mental wellness outcomes, including depression, burnout, and anxiety, and their progression over time.
- Implemented a data quality assurance system to evaluate input data and detect drift over time.
- The system also facilitated monitoring of machine learning model performance in production.
- Used YOLOv7 and YOLOv8 to extract and segment visual data, feeding the results into the baseline risk prediction pipeline
- Automated the generation of PDF reports using Python for the Remote Patient Monitoring (RPM) program.
- Reports include patient vitals, episode-based summaries via ChatGPT API, and outlier analysis, which are e-faxed to providers for insurance claims.
- Creating agents using Google ADK and Langchain to generate Audiological insights using various Audiological test results and demographical data.
- Creating a vector store using Chroma DB to retrieve data that relates to Audiological conditions and patient outcomes such as mental wellness, cognitive wellness and auditory health.
Data Science Intern
Saigeware Technologies · Nov 2022 – Feb 2023
- Developing classification models using Scikit Learn and TensorFlow for identifying disease risk in people
- Setting up data pipelines that process the real time data and extract necessary features from the data.
- The data pipelines were deployed on GCP.
- Developing an Android application that connects to a Bluetooth device using Android BLE to collect real time data from end users.
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Education
BE, Computer Science and Engineering
R V College of Engineering · 2018 — 2022
12th Class, PCMC
St. Joseph's Pre-University College · 2016 — 2018
10th Class, General Studies
The New Cambridge English School · 2015 — 2016
Projects
Contact details
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What drives their work
The Architect
You design and construct robust systems and models from their very foundations.
Thejas's superpower
You excel at transforming raw data and complex requirements into innovative, production-ready AI solutions that deliver tangible business value.
How Thejas works
You are well-suited for teams that require deep technical expertise in AI/ML, end-to-end product development, and a proactive approach to problem-solving in complex domains.
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