Scholar
Akshata Kishore Moharir
Google Scholar ID: jHAEGDEAAAAJ
Lead Data Scientist, Microsoft
Citations & Impact
Citations
22
H-index
3
i10-index
0
Publications
19
Co-authors
4
list available
Publications
Resume (English only)
Academic Achievements
- Presented at 2024 ICML on “Position: Opportunities Exist for Machine Learning in Magnetic Fusion Energy”.
- Presenting at 2024 NeurIPS on : “Towards Commercialization of Tokamaks: Time Series Viewmakers for Robust Disruption Prediction”.
- Presented at IEEE CONNECT conference on “Explainable and visually interpretable machine learning for flight sciences”.
- Presented at IEEE INOCON conference on “Learning Interpretable Rules Contributing to Maximal Fuel Rate Consumptions in an Aircraft using Rule Based Algorithms”.
- “Comparison of Diagnostic machine learning models with physics-based models for predicting the lithium-ion battery degradation behavior” presented at IEEE WinTechCon, 2018.
- Presented at 13th WIML conference (NeurIPS: Dec 2018) on “Application Hybrid Extreme Rotation Forests on aircraft Predictive Maintenance”.
- Paper “Fault prediction in aircraft engines using Regularized Greedy Forests” presented at National Machine learning and artificial intelligence conference hosted by IIM Bengaluru.
- Paper “Application of Rotation Forest for Aircraft Engines Fault Diagnosis” presented for International Conference on Business Intelligence hosted by IIM, Bengaluru, IISC, Bengaluru.
Education
- Masters of Science, Analytics, University of Maryland College Park (Oct 2022 - Present); Bachelors of Engineering, Computer Science, Visvesvaraya Technological University
Background
- A seasoned Lead Data Scientist with 10+ years of experience, dedicated to transforming complex business challenges into innovative solutions across diverse industries such as Support, Gaming, Retail, Aviation, Education, and Transportation. Expertise in Generative AI, Responsible AI practices, Predictive Modeling, Explainable AI, Natural Language Processing, Fraud Detection, and Predictive Maintenance.
Miscellany
- Strong in analyzing data, developing practical AI services, and communicating complex results to non-technical audiences.
