Research in Human–Computer Interaction and Clinical Informatics
This ePortfolio documents my undergraduate research journey at TRU — from gesture-controlled robotics using Google MediaPipe to clinical data analysis with the MIMIC-III critical care database.
Research Ambassador, TRUUREAP — MIMIC-IIICCECE 2026 (May)Co-op · Moving Mountains LogisticsProject AURA · MediaPipe Robotics
Introduction
I am a fourth-year Bachelor of Science student in Computer Science at Thompson Rivers University (TRU), and I have spent the past two years actively engaged in undergraduate research across two distinct domains: clinical data informatics and human-computer interaction. These experiences — combined with my role as a Research Ambassador within TRU’s Undergraduate Research department — have given me a comprehensive understanding of the research process, from formulating a question to communicating findings to a broader audience, and they form the basis of my application for the Undergraduate Research Certificate.
My primary research project was conducted through the Undergraduate Research and Experience Award Program (UREAP), in which I investigated bias in healthcare machine learning models using the MIMIC-III (Medical Information Mart for Intensive Care III) critical care database — one of the most widely used de-identified clinical datasets in health informatics research. Working under the supervision of Dr. Anthony and Dr. Nisha, I designed and carried out a study titled “Developing a Machine Learning Model to Evaluate and Mitigate Bias in Healthcare AI Datasets” that involved processing over 49,000 patient records, applying XGBoost and ensemble methods with demographic reweighting, and interpreting results in the context of existing clinical literature. This project required me to engage seriously with the ethics and practicalities of working with sensitive medical data, and it pushed me to develop research skills I had not previously applied in a real-world setting.
My second major research contribution is a paper I authored on a gesture-controlled robotic arm system built using Google MediaPipe — a framework for real-time hand pose estimation. The project involved designing and building a working prototype that translates hand gestures detected via a webcam into servo motor commands, enabling touchless control of a physical robot arm. This paper was accepted for presentation at the Canadian Conference on Electrical and Computer Engineering (CCECE) 2026, taking place in May 2026 — representing my first peer-reviewed conference publication and public presentation of original research.
In addition to these projects, I serve as a Research Ambassador in TRU’s Undergraduate Research department, where I support the promotion and communication of research opportunities to undergraduate students across campus. This role has deepened my understanding of what undergraduate research looks like across disciplines and has reinforced the value of making research accessible and clearly communicated. Taken together, these experiences demonstrate my sustained engagement with research across its full cycle — from design to dissemination — and qualify me for the Undergraduate Research Certificate.
| 49,694 Patient Records |
0.97 Baseline AUROC |
62 Features |
CCECE 2026 Conference |
The Standards
Evidence demonstrating engagement across five research competency areas. Each standard has separate evidence even where drawn from the same project.
Reflective Essay
“I was too busy debugging to wonder why the bug existed in the first place.”
Before Research
For the first three years of my degree, I kept research at arm’s length. I saw myself as a builder — someone who writes code, ships features, and moves on to the next problem. Research felt like something that belonged to a different kind of student: the ones who read papers for fun, who lingered after lectures to ask theoretical questions. I assumed building and investigating were separate activities, and I had chosen my side.
The first crack in that assumption came through my role as a Research Ambassador at TRU. Helping students across faculties understand research opportunities forced me to articulate what research actually is — and I realized I could not. When a nursing student asked me how research in computer science works, I stumbled. That embarrassment stayed with me. I started sitting in on presentations, reading abstracts, paying attention. Slowly, I began to see research not as an alternative to building, but as the reason you build anything worth building.
The Turning Point
The UREAP project made this concrete. When I first accessed the MIMIC-III database — 49,000 ICU patient records, each representing someone who was critically ill — I treated it like a Kaggle competition. Extract features, train a model, optimize accuracy, done. My baseline XGBoost hit an AUROC of 0.97 and I thought I was finished.
But when Dr. Anthony asked me to break the results down by race, the picture fell apart.
The model achieved a 100% false negative rate for Hispanic and Latino patients — it missed every single death in that group. A model that looks excellent in aggregate can be catastrophically unfair underneath. That was the moment research stopped being an assignment and became something I needed to understand.
I spent the following months reproducing published studies on racial and gender bias in mortality prediction, running experiments on a remote Linux server that kept killing my processes when I tried to load too much data into memory. I learned to work in 500K-record chunks, to structure reproducible pipelines, to implement fairness metrics I had only read about in papers. The technical skills mattered, but the bigger shift was internal. I stopped asking “what is the accuracy?” and started asking “who does this model fail?”
Why It Matters
Project AURA taught me the other half of the lesson. Where the MIMIC-III work was about uncovering problems in existing systems, the robotic arm project was about creating something new and defending it to strangers. Writing a peer-reviewed paper for CCECE 2026 — co-authored with Gursahib, Yassh, Noori, Vansh, and supervised by Dr. Anthony — required a completely different discipline. Every claim needed evidence. Every design choice needed justification.
Project AURA — Results We Defended
| End-to-End Latency | sub-500ms |
| Gesture Recognition Accuracy | 95% |
| 1-Hour Autonomous Stability | 99.86% |
| Non-Technical Deploy Time | 2–3 min |
Writing those numbers into a paper that would be evaluated by experts was the hardest and most rewarding writing I have done.
These experiences have bled into the rest of my life in ways I did not expect. At my co-op with Moving Mountains Logistics, I catch myself applying research thinking to operational problems — asking for data before proposing solutions, questioning assumptions that seem obvious, considering edge cases that a “good enough” approach would ignore. I am not a different person than I was two years ago, but I ask better questions now, and I am more honest about the limits of my answers.
Looking Forward
I plan to pursue graduate study in applied machine learning or health informatics. The MIMIC-III project showed me that there is unfinished, genuinely important work in making AI systems fair for the patients who depend on them. Project AURA showed me that I can take an idea from prototype to publication. And the Research Ambassador role showed me that communicating research clearly is not a soft skill — it is the mechanism by which research becomes useful. I came into this certificate thinking I would document what I had already done. Instead, it clarified what I want to do next: build things that matter, investigate whether they actually work for everyone, and share what I find so others can do the same.
DEEPANSH SHARMA
Bachelor of Computing Science · Thompson Rivers University · Kamloops, BC
linkedin.com/in/deepanshsharmaa · deepanshsharma.trubox.ca
TRU is located on the traditional lands of the Tk’emlúps te Secwépemc within Secwepemcúlucw, the traditional and unceded territory of the Secwépemc peoples.