Hi, I'm
Mithun Shivakoti
Data Scientist & ML Engineer · ICLR · NeurIPS · IJCAI · ASU '26

About me
Who I Am
I'm a Data Science grad student at Arizona State University (graduating May 2026), with research published at ICLR, IJCAI, and NeurIPS — and hands-on production experience deploying ML systems at scale.
From shipping a DistilBERT voice-AI classifier at under 100ms latency, to building a RAG system serving 50,000+ businesses, I bridge the gap between research and real-world impact.
I'm actively looking for full-time Data Scientist and ML Engineer roles. Authorized to work in the US on OPT (STEM OPT eligible).
11+
Papers Published
4
Internships
May 2026
Graduating
OPT / STEM
Work Auth
Work
Experience
Industry internships and research positions.
Artificial Intelligence Intern
DriveHealth
Gilbert, United States
- ▸Deployed a DistilBERT-based NLP model for voice AI classification achieving 98% accuracy with less than 100 ms inference latency in production.
- ▸Integrated Human-in-the-Loop validation pipelines using Argilla and Label Studio, reducing model iteration cycles and improving annotation throughput.
- ▸Redesigned backend architecture by extracting user operations into a dedicated microservice with secure TCP communication and database isolation, enabling independent scaling and improved maintainability of the core ML platform.
Software Development Engineer Intern
SignalX
Hyderabad, India
- ▸Built an OCR model to automate captcha solving, scaling throughput from 70,000 to 700,000 daily.
- ▸Engineered an adverse media classification module (96% accuracy), improving corporate risk analysis speed.
- ▸Automated summarization of 30+ page reports into 1-page briefs, cutting analysis time by 90%.
- ▸Built and deployed a RAG system integrating Gemini 1.5 (GCP) and GPT-4 with vector-based document retrieval, delivering regulatory compliance assistance to 50,000+ businesses.
Machine Learning Engineer Intern
TE Connectivity
Bengaluru, India
- ▸Developed regression-based optimization pipeline (GPR + Ridge + ElasticNet) reducing signal loss to below 1%.
- ▸Designed modular experimentation pipelines improving reproducibility and accelerating model validation.
Junior Machine Learning Engineer Intern
Omdena
Colombo, Sri Lanka
- ▸Developed and evaluated supervised classification models for early autism risk detection using structured clinical data, achieving over 96% validation accuracy through feature engineering and cross-validation.
Background
Education
Arizona State University
Master of Science in Data Science
Tempe, AZ
Relevant Courses
Vellore Institute of Technology
Bachelor of Technology in Computer Science (AI)
Vellore, India
Relevant Courses
Recognition
Achievements
Competitive accolades from national and international hackathons.
Winner — Smart India Hackathon 2022
Top 1% from 200,000+ students nationwide.
Finalist — Singapore India Hackathon 2023
1 of 24 students selected from 200,000+ across India.
Finalist — UNESCO India Africa Hackathon 2022
1 of 200 students selected from 200,000+ across India.
Runner Up — Signal Integrity Optimization Contest 2023
2nd Prize among teams across India.
Top 15 / 500+ Teams — Engineering Clinics 2022
1 of 90 students selected from 3,000+ at VIT.
Research
Publications9
Abg-SciQA: A Dataset for Understanding and Resolving Ambiguity in Scientific Questions
T Chen, KR Liou, Mithun Shivakoti, A Gaur, P Kumari, M Guo, H Wei
DeepShade: Enable Shade Simulation by Text-conditioned Image Generation
L Da, X Liu, Mithun Shivakoti, TP Kutralingam, Y Yang, H Wei
ShadeBench: A Benchmark Dataset and Method for Shade Simulation in Sustainable Society
L Da, X Liu, Mithun Shivakoti, TP Kutralingam, Y Yang, H Wei
KNOXRT: Knowledge-Networked Optimization for eXploratory Real-time Training
S Mishra, K Jeeveth, Mithun Shivakoti, V Aravindan, R Singh
A Comparative Study on Prediction of Soil Health and Crop Recommendation Using Machine Learning Models
Mithun Shivakoti, RK Srinivasa
Prognoza: Parkinson's Disease Prediction Using Classification Algorithms
Mithun Shivakoti, SC Medaramatla, D Godavarthi, N Shivakoti
An Enhanced Laryngeal Tissue Classification Model Using Deep Learning Techniques
Mithun Shivakoti, SC Medaramatla, K Jeeveth, K Srinivasa Reddy
An Efficient Regression Method To Predict Soil pH Using RGB Values
Mithun Shivakoti, AR Srinivasa Reddy
System and Method for Predicting Water Quality
Mithun Shivakoti, Sagar Dhanraj Pande
Build
Projects
Things I've built — research, tools, and experiments.
Conditional diffusion model trained on satellite imagery & 3D simulations to predict time-dependent urban shadow patterns. SSIM ~0.84 (97.8% improvement over baseline). Applied to shade-aware route optimization. Published at IJCAI 2025.
Real-time cybersecurity threat detection integrating CNN-LSTM, CNN-GRU, CNN-GAN and tree-based ensembles. 99.48% accuracy using CNN-GRU + Random Forest ensemble.
Sliding-window concept drift detection with automated model retraining for edge ML systems. Handles shifting data distributions and emergent classes without manual intervention.
Smartphone-based soil health assessment via RGB image analysis. Deep learning predicts soil type and pH, saving farmers up to 75% of time vs. physical testing.
Vital Monitoring — Arduino Nicla Smart Mask
Real-time wearable data collection from smart masks, with a trained model predicting potential collapses by analyzing breathing patterns and heart rate. Integrated hardware sensors directly into the mask for continuous edge inference.
Spoof Call Detection for Police Control Room
ML + NLP model classifying incoming calls as human or system-generated spoof calls, cutting average police connection time from 25–30 seconds to 10 seconds. Includes a real-time call recording website for voice analysis.
Laryngeal Tissue Cancer Classification
Custom CNN-based deep learning model for early-stage laryngeal tissue cancer detection (95% accuracy). Classifies four distinct tissue types from medical imaging, enabling faster clinical diagnosis.
OS Viz — Operating Systems Visualizer
Interactive visualization platform for OS concepts, with an integrated Ubuntu terminal and animated algorithm walkthroughs. Makes complex OS internals accessible to a wide audience.
Toolkit
Skills
Technologies and tools I use to build AI/ML systems.
Languages
ML / DL Frameworks
Specializations
Data Engineering
MLOps & Cloud
Databases & Tools
Certifications
Oracle Cloud Infrastructure 2024 Generative AI Professional
Oracle
Artificial Intelligence Analyst
IBM
Fundamentals of Deep Learning
NVIDIA
Career Essentials in Generative AI
Microsoft
Say hello
Let's Work Together
Actively seeking full-time Data Scientist and ML Engineer roles. Open to industry, research, and applied AI positions.
Available for full-time roles. Authorized to work in the US on OPT (STEM OPT eligible).