AI Researcher & Engineer · UC San Diego '29

Building intelligent
systems that learn

Freshman studying Artificial Intelligence at UC San Diego (GPA 4.0), working across machine learning research, embedded inference, computer vision, and full-stack AI systems.

Active LearningEMG / Biosignals Computer VisionLLM Fine-Tuning RAG SystemsEdge Deployment PyTorchReact.js + Flask
Shrivas Sudharsan
About

The person behind
the models

4.0
GPA at UC San Diego
6+
Research & project roles
~95%
Peak accuracy — EMG gesture classifier
15+
Certifications across ML, AI & data science

I'm a first-year Artificial Intelligence student at UC San Diego, working at the intersection of ML research, applied systems, and real-world deployment. From bioacoustic classification pipelines to EMG-based gesture interfaces, I care about AI that actually runs in the world — not just in notebooks.

My current research spans active learning for bioacoustic species identification (Engineers 4 Exploration), EMG-based ASL gesture recognition for neurotechnology (Triton NeuroTech), and autonomous drone systems in C++ (TritonUAS). I also mentor students on AI-driven projects through Curious Cardinals.

Before college I participated in ML research at the Cambridge Centre for International Research alongside Dr. Shadi Ghiasi, deployed a Raspberry Pi fire-detection system with a UC Irvine CS professor, and completed ML coursework through Stanford and Coursera.

Always looking for research collaborations and internship opportunities in ML systems, applied AI, and edge deployment.

Experience

Where I've worked
& researched

Jan 2026 — Present
Active Learning Research — Acoustic Species ID
UC San Diego: Engineers 4 Exploration
Building an active learning pipeline for multi-label bioacoustic classification using BirdNET transformer embeddings with LightGBM, Random Forest, SVM, and MLP classifiers. Achieved ~90% precision on dominant species classes. Applying uncertainty-based sampling to maximize model efficiency under limited annotation budgets across imbalanced long-tail distributions.
Active LearningBirdNETLightGBMMulti-label Classification
Jan 2026 — Present
NeuroTech ML Research — EMG
Triton NeuroTech at UC San Diego
Engineering EMG-based ASL gesture recognition models translating raw muscle biosignals into structured linguistic outputs. Extracted time-domain (RMS, MAV) and frequency-domain spectral features for robust multi-class classification. Achieved ~95% test accuracy with an optimized Random Forest classifier. Preparing pipeline for real-time edge deployment with low-latency inference.
EMG Signal ProcessingASL RecognitionNeurotechnologyEdge Deployment
Jan 2026 — Present
Software Team Member — Autonomous Drones
TritonUAS · La Jolla, CA
Developing low-level C++ communication between onboard drone systems and ground sensor computers. Implementing inter-process and network communication protocols for reliable data exchange across distributed robotic components. Writing performance-critical code for real-time sensing, resource management, and autonomous systems.
C++IPC / NetworkingAutonomous SystemsReal-time Systems
Mar 2026 - Present
Computer Vision Intern
Intuizi · Remote
Trained a YOLO-based satellite imagery detection model achieving 92.5% accuracy on swimming pool identification for large-scale geospatial analysis. Improved model robustness by annotating ambiguous visual edge cases to reduce false positive rate in production inference.
YOLOComputer VisionSatellite ImageryGeospatial ML
Jan 2026 — Present
AI Mentor
Curious Cardinals · Remote
Mentoring students on AI-driven coding projects from concept to working ML pipeline. Teaching ML fundamentals, model design, and debugging. Helping students translate abstract ideas into functional systems through iteration and experimentation.
AI EducationMentoringML Systems
Dec 2025 — Jan 2026
Machine Learning Researcher
RapidFire AI · Remote
Fine-tuned GPT-2 with LoRA adapters via SFT for customer-support generation (ROUGE-L=0.056, eval loss=1.15). Built a RAG pipeline on the FiQA financial dataset, optimizing chunk size, overlap, and reranking to achieve MRR=65.5%. Designed parallelized hyperparameter search with real-time metric visualization and early stopping.
LoRA / SFTRAGGPT-2LLM Fine-Tuning
Jun – Aug 2024
Artificial Intelligence Intern
Photon Insights · Hybrid
Conducted interview-driven user research and NLP-based sentiment analysis to identify product gaps. Recommended integration of a proactive AI forecasting feature. Benchmarked ML algorithms across multi-year financial time-series, competitor metrics, and news-driven datasets.
NLPSentiment AnalysisFinancial ML
May – Aug 2024
Embedded Systems Research
Pioneer Academics × UC Irvine CS Faculty
Collaborated with a UC Irvine CS professor to engineer a smart fire-detection camera system. Trained YOLO-based networks achieving 90.2% accuracy on fire and 85.7% on smoke. Deployed end-to-end on Raspberry Pi with on-device inference and IoT-based local alert transmission pipeline.
Embedded InferenceRaspberry PiIoTYOLO
Jun – Dec 2023
ML Research Program
Cambridge Centre for International Research
Participated in a formal ML research program alongside Dr. Shadi Ghiasi, a senior AI research specialist. Authored a research paper applying machine learning to ECG-based diabetes detection. Compared 16+ classical and ensemble models, improving Random Forest precision to 87.5% through feature engineering and signal processing. (Academic research program — not a peer-reviewed publication.)
ECG FeaturesHealthcare AIFeature Engineering
Projects

Things I've built

01 — MULTIMODAL AI
Multimodal AI Reading Assistant
StartupIncubator UCSD · Feb 2026
Multimodal AI Reading Assistant screenshot
HOW IT WORKS
Chrome extension combining real-time eye-tracking gaze signals with an event-driven LLM + TTS pipeline. Gaze-to-DOM coordinate mapping fires contextual explanations based on exactly what you're reading. Debounce logic and async optimization minimize unnecessary API calls.
ElevenLabs TTS · Gaze-to-DOM mapping · Async optimization
Eye TrackingLLMChrome ExtensionTTSJavaScript
02 — LLM SYSTEMS
LLM Fine-Tuning & RAG Pipeline
RapidFire AI · Dec 2025 – Jan 2026
Fine-tuned GPT-2 with LoRA adapters via SFT for customer-support generation. Built a complete RAG pipeline on the FiQA financial QA dataset with optimized chunking, overlap, and reranking. Parallelized hyperparameter search with early stopping across SFT and RAG experiments.
ROUGE-L=0.056 · eval loss=1.15 · MRR=65.5%
GPT-2LoRA / SFTRAGFiQAPyTorch
03 — FULL-STACK
TritonHub Academic Dashboard
SanD Hacks · Jan 2026
TritonHub dashboard
HOW IT WORKS
Full-stack platform aggregating Canvas LMS and Gmail into a unified academic dashboard. Built the LLM integration layer that parses raw API data, applies a deterministic pre-filter to block junk without unnecessary model calls, and surfaces actionable updates in real time. React.js frontend with Flask backend, OAuth auth, and Supabase for multi-service data ingestion.
React.js · Flask · Supabase · OAuth · LLM Parsing
React.jsFlaskSupabaseCanvas APIGmail APILLM
Try it live →
04 — EMBEDDED AI
Smart Fire & Smoke Detection
Pioneer Academics × UC Irvine · 2024
YOLO-based neural network deployed end-to-end on a Raspberry Pi for real-time fire and smoke detection. Full IoT alert pipeline notifies local residents on detection. Developed in collaboration with a UC Irvine CS professor.
Fire: 90.2% · Smoke: 85.7% · On-device inference
YOLORaspberry PiIoTEdge Inference
05 — CLIMATE AI · 🥉 3RD PLACE DATAHACKS 2026
ClearMarine
DataHacks 2026 · Apr 2026
DEMO VIDEO
AI-powered ocean debris coordination platform built in 24hrs. Field sightings (voice STT + CV) triaged by Groq (LLaMA 3.1) into severity narratives; drift forecasted using real CORC Spray glider current data + HYCOM fallback. Live ops dashboard with AI-ranked crew dispatch across ships and shore teams, synced via Supabase Realtime.
Report → triage → drift forecast → dispatch → intercept
Groq / LLaMA 3.1 ElevenLabs Supabase Realtime Leaflet React Vercel
Live Demo → GitHub →
05 — HEALTHCARE ML
ECG-Based Diabetes Detection
Cambridge Centre for International Research · 2023
Comparative ML study across 16+ models for diabetes detection using ECG-derived features, conducted through a research program with Dr. Shadi Ghiasi. Applied feature engineering and signal processing to benchmark and optimize classical and ensemble methods.
Random Forest precision → 87.5% · 16+ models
ECG FeaturesRandom ForestHealthcare AISignal Processing
Education & Skills

Education, skills
& certifications

Aug 2025 – Jun 2029
B.S. Artificial Intelligence · GPA 4.0
UC San Diego
Coursework: Machine Learning, Discrete Mathematics, Calculus, Python, Data Structures
Jun – Aug 2024
Summer Program in Neuroscience
UCLA
Studied brain anatomy and neurological disease with faculty mentorship. Explored AI-assisted stroke detection — directly shaped interest in neurotechnology.
Certifications
🤖
SFT Certification
RapidFire AI
Jan 2026 · Supervised Fine-Tuning
🔍
RAG Certification
RapidFire AI
Jan 2026 · Retrieval-Augmented Generation
🎓
Machine Learning Specialization
Stanford University
Aug 2023 · ID: TMU42NJ9XKQJ
📊
Supervised ML: Regression & Classification
Coursera
May 2023 · ID: H43JT6Y7F5SM
🧠
Advanced Learning Algorithms
Coursera
Jul 2023 · ID: YRDLUKRXXJ6U
🔄
Unsupervised Learning, Recommenders & RL
Coursera
Aug 2023 · ID: H43JT6Y7F5SM
🏥
Foundations of Healthcare Systems Engineering
Coursera
May 2023 · ID: N6BQ5TS7Q5S3
🐍
Python for Everybody Specialization
University of Michigan
Oct 2020
📈
Machine Learning with Python
IBM Skills Network
Aug 2020
📉
Data Analysis with Python
IBM Skills Network
Jul 2020
📊
Data Visualization with Python
IBM Skills Network
Jul 2020
🐍
Python for Data Science, AI & Development
IBM Skills Network
Jun 2020
🔬
Data Science Methodology
IBM Skills Network
May 2020
🛠️
Tools for Data Science
IBM Skills Network
May 2020
💡
What is Data Science?
IBM Skills Network
May 2020
Technical Skills
Languages
PythonC++JavaJavaScriptHTML/CSS
ML / Deep Learning
PyTorchTensorFlowScikit-learnLightGBMOpenCVYOLOBirdNET
AI Techniques
Active LearningRAGLoRA / SFTEMG Signal ProcessingEmbedded InferenceEdge DeploymentMultimodal AI
Web & Systems
React.jsFlaskREST APIsSupabaseRaspberry PiChrome ExtensionsC++ IPC
Data & Tools
NumPyPandasMatplotlibGitSQL
Beyond the Code

Leadership, community,
& everything else

AI is what I do technically — but this is what shaped how I think, lead, and show up for people.

🏆
National Winner — FlexFactor
NextFlex · Jun 2023
Led team to a national victory out of 350+ participating teams. Presented a full technology product design, business model, and pitch deck to government officials, industry leaders, and academics. Recognized for innovation, teamwork, and entrepreneurial thinking.
🧠
Neuroscience Summer Program
UCLA · Summer 2024
Studied brain anatomy, neurological disease, and AI-assisted stroke detection with UCLA faculty mentorship. Directly shaped interest in neurotechnology — which led to EMG/ASL research at Triton NeuroTech.
🌲
Co-Founder — Adopt a Park
Feb 2022 – Jun 2025 · 3+ years
Co-founded and led a community environmental initiative organizing volunteer efforts and park maintenance at Glenview Park, San Jose over more than three years.
⚜️
Patrol Leader — Boy Scouts of America
Aug 2018 – Jun 2025 · Star Scout · ~7 years
Served as Patrol Leader coordinating and mentoring teams across multi-day service and leadership activities. Led large-scale community service projects built around teamwork, resilience, and responsibility.
🤝
AI Mentor — Curious Cardinals
Jan 2026 – Present
Mentoring students on AI-driven projects from concept to working implementation. Teaching ML fundamentals while helping students debug, iterate, and think like engineers.
📜
Languages
English (native) · Sanskrit (working proficiency)
Native fluency in English. Working proficiency in Sanskrit — one of the world's oldest structured languages with deep connections to formal grammar and computational linguistics.
Contact

Let's work
together

I'm always open to research collaborations, internship opportunities, and conversations about ML systems, applied AI, and edge deployment. Feel free to reach out through any of the channels below.

✉️
Email
sudharsan.shrivas@gmail.com
↗ 💼
LinkedIn
linkedin.com/in/shrivas-sudharsan-a20398255
↗ 🐙
GitHub
github.com/shrivassudharsan1
↗
What I'm looking for

I'm currently a freshman at UC San Diego and actively seeking summer 2026 internships in ML engineering, AI research, or applied data science roles.

I'm especially interested in teams working on real-world ML deployment, multimodal systems, edge AI, or biosignal processing.

For research collaborations, I'm open to conversations at any stage — from early ideas to active projects looking for a contributor.