Arindam Paul


Professional Summary

Computer Scientist with 10+ years of research experience.

Interested in Machine Learning, Deep Learning, Natural Language Processing

Computer Skills

  • Proficient: Python, Keras/Tensorflow, Scikit-Learn, dash/plotly, statsmodels, scipy, Selenium, XGBoost/LightGBM
  • Familiar: FastAI/PyTorch, R, MATLAB, weka, SQL, html/css/javascript, MPI, PySpark, C, C++, Java


Northwestern University, Evanston, Illinois

Northwestern University, Evanston, Illinois

Birla Institute of Technology & Science, Pilani, Rajasthan India

Birla Institute of Technology & Science, Pilani, Rajasthan India
  • Bachelor of Engineering (Graduated with Honors) in Chemical Engineering, 2010
  • Thesis: Detecting Sybil Attacks in P2P networks using Psychometric Analysis
  • Advisor: Prof. K. Haribabu

Professional Experience

Data & Applied Scientist at American Family Insurance: Oct 2019-
  • Developing machine learning models for predicting motor vehicle risk
  • Creating insurance-based language models for insurance specific language interpretation

Summer Research Intern at Northwestern Mutual Life Insurance: Jun-Aug 2018
  • Developed distributed image to text conversion algorithms for detecting responses from scanned questionnaires
  • Developed an image noise reduction algorithm to denoise scanned and photocopied questionnaires

Summer Research Intern at Boeing Cybersecurity: Jun-Sep 2013
  • Generated synthetic user profiles with different demographic and interest features
  • Developed a machine learning model for predicting user demographics and interests from ads


  • McCormick Dean's Commendation Fellowship, 2018 Spring
  • Predictive Science & Engineering Design Cluster Fellowship, 2016-17
  • Segal Design Cluster Fellowship, 2014-15
  • Walter P. Murphy Fellowship, 2012-13



D. Borthakur, A. Paul, D. Kapil, M.J. Saikia. Yoga Pose Estimation Using Angle-Based Feature Extraction. Health, 2023

Y. Mao, M. Hasan, A. Paul, V. Gupta, K. Choudhary, F. M. Tavazza, W. Liao, A. Choudhary, P. Acar and A. Agrawal. An End-to-End AI-Driven Microstructure Optimization Framework for Elastic Properties of Titanium Beyond Cubic Crystal Systems. npj Computational Materials, 2023

A.Dimri, A.Paul, D.Girish, P.Lee, S.Afra and A. Jakubowski. A Multi-input Multi-label Claims Channeling System Using Insurance-Based Language Models Expert Systems With Applications. Expert Systems With Applications, 2022

Y. Mao, Z. Yang, D. Jha, A. Paul, W. Liao, A. Choudhary and A. Agrawal. Generative Adversarial Networks and Mixture Density Networks based Inverse Modeling for Microstructural Materials Design. Integrating Materials and Manufacturing Innovation Journal, 2022

K. Ness, A. Paul, L. Sun and Z. Zhang. Towards a generic physics-based machine learning model for geometry invariant thermal history prediction in additive manufacturing. Journal of Materials Processing Technology, 2022 (Special Issue on Artificial Intelligence in Advanced Manufacturing Processes -AiAMP)

R.Richards, and A. Paul. An Attention-driven LSTM Network for High Throughput Virtual Screening of Organic Photovoltaic Candidate Molecules. Solar Energy, 2021

A. Paul, W. Liao, A. Choudhary and A. Agrawal. Harnessing Psycho-lingual and Crowd-Sourced Dictionaries for Predicting Taboos in Written Emotional Disclosure in Anonymous Confession Boards. Journal of Health Informatics Research, 2021Download

A. Paul, A. Furmanchuk, W. Liao, A. Choudhary and A. Agrawal. Property Prediction of Organic Donor Molecules for Photovoltaic Applications using Extremely Randomized Trees. Journal of Molecular Informatics, 2019

A. Paul, P. Acar, W. Liao, A. Choudhary, V. Sundararaghavan and A. Agrawal. Microstructure Optimization with Constrained Design Objectives using Machine Learning-Based Feedback-Aware Data-Generation. Journal of Computational Materials Science, 2019

D.Jha, L.Ward, A. Paul, W. Liao, A. Choudhary, C. Wolverton and A. Agrawal. ElemNet: Deep Learning the Chemistry of Materials From Only Elemental Composition. Nature Scientific Reports, 2018

M.Mozaffar, A. Paul, R. Al-Bahrani, S. Wolff, A. Choudhary, A. Agrawal, K. Ehmann and J.Cao. Data-Driven Prediction of the High-Dimensional Thermal History in Directed Energy Deposition Processes via Recurrent Neural Networks. Manufacturing Letters, 2018

A. Paul, P. Acar, R. Liu, W. Liao, A. Choudhary, V. Sundararaghavan and A. Agrawal. Data Sampling Schemes for Microstructure Design with Vibrational Tuning Constraints. Journal of American Institute of Aeronautics and Astronautics, 2018

K Haribabu, C.Hota and A. Paul. GAUR: A Method to Detect Sybil Groups in Peer-to-Peer Overlays, International Journal of Grid and Utility Computing 2012, Vol.3

A. Paul, J.S. Challa, Y.Dada, V.Nerella, P.R. Srivastava and A.P.Singh. Integrated Software Quality Evaluation: A Fuzzy Multi-Criteria Approach, Journal of Information Processing Systems (JIPS) 2011 Volume 7


Z. Yang, D. Jha, A. Paul, W. Liao, A. Choudhary and A. Agrawal. Generative adversarial networks with mixture density networks for inverse modeling in materials microstructural designs. Workshop on Machine Learning for Engineering Modeling, Simulation and Design at 2020 Conference on Neural Information Processing Systems (NeurIPS)

A. Paul, M.Mozaffar, Z. Yang, W. Liao, A. Choudhary, J. Cao and A. Agrawal. A real-time iterative approach for temperature profile prediction in additive manufacturing processes. 6th IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2019

A. Paul, D. Jha, R. Al-Bahrani, W. Liao, A. Choudhary and A. Agrawal. Transfer Learning Using Ensemble Neural Nets for Organic Solar Cell Screening. International Joint Conference on Neural Networks, 2019

A. Paul, D. Jha, R. Al-Bahrani, W. Liao, A. Choudhary and A. Agrawal. CheMixNet: Mixed DNN Architectures for Predicting Chemical Properties using Multiple Molecular Representations. Workshop on Machine Learning on Molecules and Materials at 2018 Conference on Neural Information Processing Systems (NeurIPS)

R. Liu, D. Palsetia, A. Paul, R. Al-Bahrani, D. Jha, W. Liao, A. Agrawal, and A. Choudhary. PinterNet: A Thematic Label Curation Tool for Large Image Datasets. Workshop on Open Science in Big Data at 2016 IEEE Bigdata Conference

A. Paul, A.Agrawal, W.Liao and A.Choudhary. AnonyMine: Mining anonymous social media posts using psycho-lingual and crowd-sourced dictionaries. Workshop on Sentiment Discovery and Opinion Mining at 22nd ACM Conference on Knowledge Discovery and Data Mining, 2016

J.Birnholtz, N.A.R. Merola, and A. Paul. "Is it Weird to Still Be a Virgin?": Anonymous, Locally Targeted Questions on Facebook Confession Boards. ACM Conference on Human Factors in Computing Systems, 2015

A. Paul, Varuni G., J.S. Challa and Y. Sharma. HADCLEAN: A Hybrid Approach for Data Cleaning Techniques in Data Warehouses, IEEE International Conference on Information Retrieval and Knowledge Management(CAMP), 2012

A. Paul, J.S. Challa,Y. Dada, V. Nerella, P.R. Srivastava. Quantification of Software Quality Parameters using Fuzzy Multi-Criteria Approach, IEEE International Conference on Process Automation Control and Computing (PACC), 2011

A. Paul, K Haribabu and C. Hota. Detecting Sybils in Peer-to-Peer Overlays using Psychometric Analysis Methods, IEEE International Conference on Advanced Information Networking and Applications(AINA), 2011


  • President(2014-16), Northwestern University Cricket Club
  • President(2016-18) and Treasurer(2015-16), Northwestern SpeakEasy Toastmasters Club
  • Facilitator(2016-17), Northwestern Multicultural Dialogue Group
  • Student Coordinator(2016-17), Northwestern Predictive Science & Engineering Design)
  • STEM Liaison(2014-2015), Northwestern Ethnic Students Group

Teaching and Outreach

  • Instructor, Transferable Skills Workshop on Machine Learning
  • Lecturer (and TA) for Introduction to Programming, Northwestern, Winter 2015
  • Lecturer (and TA) for Introduction to Programming, Northwestern,Winter and Spring 2014
  • TA for Data Structures, Northwestern,Fall 2015
  • Guest Lecturer for Social Media Mining, Northwestern,Spring 2016
  • TA for Database Systems, BITS Pilani, Spring 2012
  • Instructor and Mentor, Brave Initiatives

Awards & Achievements

  • Among 10 doctoral students across Northwestern selected for summer-long Research Communication Seminar Course, 2016
  • All India Rank 1 in BITS HDSAT (admission test for graduate programs at BITS Pilani)
  • All India Rank 64 & State Rank 9 in National Science Olympiad among more than half million participants during freshmen year of high-school
  • Recipient of BITS Pilani Merit-cum-Need Scholarship during last 3 years of undergraduate study


Selected Course Projects

  • Developed a Sentiment Analysis Tool to find the most interesting or controversial events at the 2013 Golden Globe Awards from user-Tweets (Python)
  • Developed a tool which uses Natural Language Processing techniques to find the most interesting or controversial events at the 2013 Golden Globe Awards from user-Tweets (Python)
  • Developed Sudoku & Othello solver using constraint satisfaction and min-max algorithms using efficient tree-based data structures and algorithms (C++)
  • Implemented a fully distributed event detection mechanism by utilizing a Kademlia-based DHT overlay network (Go)
  • Developed a web application to track a portfolio of a user’s stocks. Used data mining techniques to analyze and predict stock and portfolio performance using historical data. (Perl, SQL)

Selected Side Projects

  • Developed a tool which creates a recommendation system using ElasticSearch(Lucene) for shopping based on ”I just bought” Amazon tweets of users (Python)
  • Developed a real-time tool starts an alarm when a designated bus is ’x’ (customizable) min away from the closest bus stop by scraping CTA bus tracker webpage (Python)
  • Developed a web-automation & scraping tool which collects past news articles from the web. Used OCR recognition for getting the text from old articles (Python)

References (on request)

  • Dr. Alok Choudhary - Professor of EECS (Northwestern University)
  • Dr. Ankit Agrawal - Research Associate Professor of EECS (Northwestern University)
  • Dr. K. Haribabu - Assistant Professor of CSIS (BITS Pilani)