Shashank Shatraboina
Machine Learning | Trustworthy AI
shashankshatraboina@gmail.com
About
I am a Computer Science graduate with a strong interest in Machine Learning, particularly in Trustworthy AI. I am interested in exploring how intelligent systems can be made more interpretable, reliable, and robust, with a focus on developing machine learning models that can be trusted in real-world applications. I aspire to pursue an MS in Computer Science to deepen my research interests and technical expertise in these areas.
I am currently a Research Intern at IIT Roorkee (CoDA Lab) under Dr. Sudip Roy. Previously, I was an Undergraduate Research Assistant at CMR Engineering College's ML Lab under Dr. Mrutyunjaya S. Yalawar and Dr. Praveen Chouksey.
Research & Publications
Manuscripts & Recent Research
An fMRI-Guided Deep Learning Framework for Rapid Semi-Automated Deep Brain Stimulation Optimization in Parkinson’s Disease
Shashank Shatraboina, Dr. Sudip Roy
Under Review, IEEE ICIPCN 2027
Cognitive-Aware Enterprise Search Using Hybrid Semantic Retrieval and Human-in-the-Loop Feedback
Shashank Shatraboina, Karthick Balakrishnan
Accepted for IEEE ICICNIS 2026
DefectLens: Interpretable Ensemble Convolutional Networks for Artwork Defect Detection
Raghuvamshi, Shashank Shatraboina, Dr. Kumara Swamy
Accepted for IEEE ICITSIF 2027
Selected Publications
A Deep Learning Framework for Automated Road Surface Damage Detection Using UAV Imagery
Shashank Shatraboina, Vinod Upadhyay, Mulla Akbar Shehazad, Dr. Praveen Chouksey
IEEE ICAUC - 2026
AI-Driven Medical Diagnosis: Integrating Fuzzy Logic, Machine Learning, and Deep Learning for Enhanced Clinical Accuracy
Shashank Shatraboina, Dr. Mrutyunjaya S Yalawar
IEEE ICCICA - 2025
A Study on EV Challenges and its barriers : A Review
Shashank Shatraboina, Dr. Mrutyunjaya S Yalawar
IEEE ICACRS - 2025
Federated and Collaborative Deep Learning Optimization in Cloud–Fog Computing
M. Shamila, Shatraboina Shashank, Bhaskar Vishwakarma, Dr. Zatin Gupta, Dr. Neha Khare, Dr. Shweta Bansal
IEEE ICETICS - 2026
Real-Time Cognitive and Academic Performance Tracking System for Adaptive E-Learning Applications
D Sai Niharika, Shashank Shatraboina, Dr. Pankaj Agrawal, Dr. Alok Jain, Dr. Ankur Choudhary, S R V Prasad Reddy
IEEE ICBDML - 2026
An Interpretable Machine Learning Model for Leukemia Diagnosis Using CNN-SVM and Explainable AI
Dr. Vandana Roy, Dr. R. P. Ram Kumar, Shashank Shatraboina, Dr. Prakhar Gautam, Dr. Sandeep Pandey, G. Kaushik
IEEE ICTBIG - 2025
Machine Learning Models for Monitoring Environmental Impact on Public Health
Dr. A. Akhila, Dr. Ankit Rawat, Dr. P. Deepthi, Shashank Shatraboina, Jitendra Prithviraj, Sanjay Yadav
IEEE ICTBIG - 2025
Evaluation of Various ML Models for the Identification of Epileptic Seizures
Dr. B. Kiran Kumar, Rekha Maithani, K. Adilakshmi, Shashank Shatraboina, Romit Bhalla, Mayank Nagar
IEEE ICTBIG - 2025
Development of an Automated Deep Learning Framework for Early Detection and Diagnosis of Epileptic Seizures from Brainwave Patterns
Dr. Sudeep Kumar Gupta, Dr. G.Durga Sowjanya, Dr. Laxmi Narayan Pandey, Dr. Rashi Saxena, Shatraboina Shashank, Vikash Verma
IEEE ICTBIG - 2025
Projects
AutoML Factory: End-to-End Automated ML Pipeline Platform
Architected an AutoML+MLOps platform automating preprocessing, feature engineering, and Optuna-based tuning – reducing manual ML effort by 80%. Achieved 10x faster iteration and 3.2x faster convergence via meta-learning warm-start, with real-time model comparison (accuracy, F1, ROC-AUC). Handles 10K+ concurrent requests at <100ms latency with 99.95% uptime.
Hybrid Network Analysis for Financial Distress Prediction
Formulated a graph-based framework fusing corporate network topology (7 centrality metrics) with financial indicators, achieving 92% accuracy and 23% AUC improvement over traditional models with 15% fewer false positives. Engineered GraphSAGE embeddings + XGBoost on 50K+ corporate relationships (<200ms inference), demonstrating network entropy as a leading systemic risk indicator.
ML-Based Multi-Disease Prediction System
Developed an ensemble ML system for early detection of 4 pathologies (Diabetes, Cardiac, Parkinson's, Breast Cancer) across 5 benchmark datasets (N=2,557). Achieved 96.2% weighted diagnostic accuracy via XGBoost+SVM with RFE (breast: 97.4%, heart: 96.8%, Parkinson's: 96.2%, diabetes: 92.1%). Designed reproducible pipeline (EDA, feature selection, multi-classifier benchmarking) with documented extensibility for fuzzy logic integration in clinical decision support
Cinemaxx (Movie Recommendation Website)
Engineered a recommendation system implementing matrix factorization from scratch with explicit handling of data sparsity, achieving 12% RMSE improvement over baseline. Deployed as real-time engine using Truncated SVD + cosine similarity on 500K+ TMDb embeddings, with dynamic matrix caching reducing cold-start latency by 65% and achieving <180ms response times for 1K+ concurrent users.
Pothole Detection System
Engineered a UAV-based pothole detection system starting with ResNet-101 (210ms latency on drone-edge hardware). After identifying overfitting (training loss 0.12, validation loss 0.47), systematically implemented dropout + data augmentation, improving validation generalization by 15.3%. Switched to YOLOv8-tiny (47ms inference, <2% mAP loss), reducing false positives from 18% to 6% across 320 field images under varied lighting.
Research & Academic Excellence
- [Nov 2024] Bharat Ratna Sir M. Visvesvaraya Award recipient (IEI) — awarded at age 21 for research excellence
- [Feb 2025] Achieved a 166Q 166V GRE score
Academic Service (AI/ML Tracks)
- Reviewer for 10th ACM CSAE 2026
- Reviewer for 11th IEEE RICE 2026
- Reviewer for 8th IEEE ICCCMLA 2026
- Reviewer for IEEE GSEACT 2026
- Reviewer for IEEE CCIC 2026
- Reviewer for IEEE GSCon 2027
- Reviewer for Low-Altitude Vehicle Dynamics and Control Journal
Leadership & Service
- [Nov 2024 - Dec 2025] Mentored 77 students in DSA for campus placements.
- [Jan 2025 - Dec 2025] AI Club & Coding Club Lead Student Organizer
- [Dec 2023 – Oct 2024] NSS Blood Donation Initiative - mobilized 328 donors, partnered with TSCS & CMR Hospital
- [Mar 2019 - Dec 2019] Swachh Bharat Volunteer - cleanliness awareness campaigns
Vitæ
Full CV in PDF.
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IIT Roorkee Jan 2026 - PresentResearch Intern
CoDA Lab (Advisor: Dr. Sudip Roy)
Built an AI-driven fMRI framework for optimizing Deep Brain Stimulation in Parkinson’s Disease, achieving 96% accuracy and 0.98 AUC using deep learning on clinical neuroimaging data.
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eQOURSE Pvt.Ltd July 2025 - Nov 2025AI Trainee Intern
Designed AI/ML curriculum + assessments for school students, simplifying complex ML concepts into student-friendly format -
Wyreflow technologies Oct 2024 - Nov 2024Technical Tester / QA Intern
Worked on test cases, bug reporting, agile collaboration for performance & stability -
Code Clause Private Ltd Aug 2024 - Sep 2024Web Development Intern
Built JavaScript-driven web apps (music player + game) — focused on interactivity, state management, and responsive design -
CMR Engineering College Nov 2022 - May 2026B.Tech in Computer Science
CGPA: 8.10/10
Undergraduate Researcher (Oct 2023 - Jan 2026)
AI/ML Lab (Advisors: Dr. Mrutyunjaya S Yalawar, Dr. Praveen Chouksey)
Medical AI (Fuzzy Logic + ML/DL) | Pothole Detection (ResNet-101, 97%) | EV Analytics (battery + infrastructure)
Data Structures & Algorithms Trainer (Nov 2024 - Dec 2025)
Mentored 77 students in DSA + interview prep -
Sri Chaitanya Junior Kalasala June 2020 - Oct 2022Higher Secondary Education (Class XII) – Mathematics, Physics & Chemistry (MPC)
Marks: 927/1000 -
Sri Sai EM School Completed 2020Secondary School Certificate (Class X) - Distinction
CGPA: 10.0/10.0.