Published Papers

• Low-Cost Device Prototype for Automatic Medical Diagnosis Using Deep Learning Methods

  Neil Deshmukh (Moravian Academy)

  Updated Research Paper: Open-Access Link

  IEEE UEMCON’18 at Columbia University, New York, NY.

  • Best Machine Learning Paper at the 9th IEEE Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON).

  • Presented at the IEEE MIT Undergraduate Research Technology Conference (MIT URTC’18).

Accepted for Publication

• Semi-Supervised Natural Language Processing Approach for Fine-Grained Classification of Medical Reports

  Neil Deshmukh (Moravian Academy), Selin Gumustop*, Romane Gauriau*, Varun Buch*, Bradley Wright*, Christopher Bridge*, Ram Naidu*, Katherine Andriole*, Bernardo Bizzo* (*affiliated with MGH & BWH Center for Clinical Data Science)

  1. IEEE MIT URTC’19, Boston, MA

     • Presented at the IEEE MIT Undergraduate Research Technology Conference (MIT URTC'19) at MIT, Boston, MA on October 12, 2019.

     • Presented at the New in ML workshop on December 9, 2019 at NeurIPS 2019,Vancouver, BC, Canada.

• FD-Net with Auxiliary Time Steps: Fast Prediction of PDEs using Hessian-Free Trust-Region Methods

  Nur Sila Gulgec (Lehigh University), Zheng Shi (Lehigh University | IBM), Neil Deshmukh (Moravian Academy), Martin Takáč (Lehigh University)

  2019 NeurIPS: Conference on Neural Information Processing Systems, Vancouver, BC, Canada

  • Presented at the Neural Information Processing Systems: Beyond First-Order Methods in Machine Learning workshop on December 13th, 2019 at NeurIPS 2019,Vancouver, BC, Canada.

• Detecting Organ Failure in Motor Vehicle Trauma Patients: A Machine Learning Approach

  Neil Deshmukh (Moravian Academy), Abhijit Bhattaru (The College of New Jersey), Srija Makkapati (Princeton University), and Nathan Nakamitsu (University of California, Berkeley)

  IEEE MIT URTC’19, Boston, MA

  • Best Abstract winner in Decision Support and Monitoring Category at AIMed North America 2018. The abstract and related research was presented at the conference in Dana Point, CA.

  • Presented at the IEEE MIT Undergraduate Research Technology Conference (MIT URTC'19) with Ahijit Bhattaru at MIT, Boston, MA On October 12, 2019.

  • The paper will be published in IEEE Xplore.

  • Optimization techniques used during the research were presented at Lehigh University Modeling and Optimization: Theory and Applications (MOPTA'19) conference.

Working Papers

• Deep Learning in Predicting Molecular Dynamics with Periodic Boundary Conditions.

  Zheng Shi, Neil Deshmukh, Albert S. Berahas, Srinivas Rangarajan, Martin Takáč. Working Paper (2020)

• Deep Learning in Solving and Discovering PDE for Dynamic Systems.

  Zheng Shi, Nur Sila Gulgec, Neil Deshmukh, Albert S. Berahas, Shamim Pakzad, Martin Takáč. Working Paper (2020)