Shubhranshu Shekhar Publications Teaching About me
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Shubhranshu Shekhar

Ph.D. Student
Carnegie Mellon University
Email: shubhranshu [dot] cse [at] gmail [dot] com
Web: https://shubhranshu-shekhar.github.io/

Publications

  1. FairOD: Fairness-aware Outlier Detection.  Shubhranshu Shekhar, Neil Shah  and Leman Akoglu. In AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES) 2021.
  2. Entity Resolution in Dynamic Heterogeneous Networks.  Shubhranshu Shekhar, Deepak Pai  and Sriram Ravindran. In Workshop on Deep Learning for Graphs at The Web Conference 2020, Taipei, Taiwan.
  3. Incorporating Privileged Information to Unsupervised Anomaly Detection.  Shubhranshu Shekhar and Leman Akoglu. In ECML-PKDD 2018, Dublin, Ireland. Project Page    Best Student Machine Learning Paper Runner-up Award
  4. Spreading Activation Way of Knowledge Integration. Shubhranshu Shekhar, Sutanu Chakraborti and Deepak Khemani.  In MIKE 2015 Proceedings of the Third International Conference on Mining Intelligence and Knowledge Exploration, 2015.
  5. Linking Cases Up: An extension to Case Retrieval Network. Shubhranshu Shekhar, Sutanu Chakraborti and Deepak Khemani.  In proceedings of 22nd International Conference on Case-Based Reasoning (ICCBR), 2014.
  6. Business Networking in Social Networks. Dhanvin Mehta, Shubhranshu Shekhar and Balaraman Ravindran. In 6th IBM Collaborative Academia Research Exchange (I-CARE), non-archive, 2014.
  7. How popular are your tweets?. Avijit Saha, Janarthanan Rajendran, Shubhranshu Shekhar and Balaraman Ravindran. In Workshop on Crowdsourcing and Human Computation for Recommender Systems, held in conjunction with the 7th ACM Conference on Recommender Systems (RecSys), 2014.

Patents

  1. Machine Learning based on Post-Transaction Data. Moein Saleh, Xing Ji, Shubhranshu Shekhar. App. 16/198,445.
  2. Utilizing a time-dependent graph convolutional neural network for fraudulent transaction identification. Shubhranshu Shekhar, Deepak Pai and Sriram Ravindran. To be filed.

Teaching

Instructor, Carnegie Mellon University
1. 95-828 Machine Learning for Problem Solving, Heinz College
    Spring 2020: Most popular graduate ML course at Heinz College


Teaching Assistant, Carnegie Mellon University
1. 10-701 Introduction to Machine Learning, Machine Learning Department
    Fall 2018: Most popular graduate ML course at the university
2. 95-828 Machine Learning for Problem Solving, Heinz College
    Spring 2019: Most popular graduate ML course at Heinz College


Teaching Assistant, Department of Computer Science and Engineering, IIT Madras
Responsibilities: My work includes providing forum for discussions, proposing project topics for the course, guiding
                                and mentoring teams with their projects, and assisting with the conduct of the lectures.

1. Natural Language Processing (NLP)
    Jul-Nov 2014: The course is taught by Dr. Sutanu Chakraborti.
                               Delivered a lecture on Machine Translation way of solving NLP problems
    Jul-Nov 2013: The course was jointly taught by Dr. Sutanu Chakraborti and Dr. Balaraman Ravindran.
   
2. Memory Based Reasoning (MBR) in AI
    Jan-May 2014:
The course is taught by Dr. Sutanu Chakraborti.
                                Gave a lecture on Search in Large Metric Space
    Jan-May 2015:
Dr. Sutanu Chakraborti is teaching the course. 


Teaching Assistant (during undergraduate studies), School of Computer Science, National Institute of Science and Technology
1. Engineering Mathematics - I
2. Paradigms of Programming

About Me

 I am a PhD student in the joint Machine Learning and Public Policy program at Carnegie Mellon University’s Machine Learning Department and Heinz College. I am fortunate to be advised by Prof. Leman Akoglu and Prof. Christos Faloutsos. My research interests are broadly in the areas of Anomaly Detection, Data Mining and bio-medical applications of Machine Learning.

Before joining CMU, I was working as a Data Scientist with Flipkart. I worked on improving search quality with particular focus on query expansion and query recommendation. I am an
  early contributor to spark-transformers, an open source library for exporting Spark models.

Prior to joining Flipkart, I was an MS (Research) student in the Computer Science and Engineering department at Indian Institute of Technology Madras. I was associated with Artificial Intelligence and Databases (AIDB) Lab, working under the guidance of  Prof. Sutanu Chakraborti and Prof. Deepak Khemani .