Sahely Bhadra

Computer Science and Engineering

Indian Institute of Technology, Palakkad, Kerala, India.

email : sahely@iitpkd.ac.in , Google scholar , LinkedIn .

phone: +91 4923 226 395


Research

Research interest:

Machine Learning (learning from noisy and incomplete data), optimization (robust optimization and convex optimization for large data), data analysis, network analysis, bioinformatics (micro-array data analysis and molecular network analysis) .

Summary:

I am currently working on various application of machine learning in network. I am also interested in modeling Kernel method for learning with multi view, noisy or incomplete data.

Awards:

Students:

PhD scholar :

Viivi Uurtio (co-supervising with Prof Juho Rousu of Aalto University, Finland)

Reji Rahmath K


Submitted Manuscript:

Viivi Uurtio, Sahely Bhadra, Juho Rousu. Sparse non-linear CCA through HSIC.

Timothy LaRock, Timothy Sakharov, Sahely Bhadra, Tina Eliassi-Rad . Limit of Learning in Incomplete Network .

Sahely Bhadra, Juho Rousu. Book chapter : Principal Metabolic Flux analysis.

Sahely Bhadra. Book Chapter : Multi view data completion


Publications:

Sahely Bhadra, Peter Blomberg, Sandra Castillo, and Juho Rousu. Principal Metabolic Flux Mode Analysis. Accepted for publishing in Bioinformatics. 2018.

Timothy Larock, Timothy Sakharov, Sahely Bhadra, and Tina Eliassi-Rad. Limit of Learning in Incomplete Network. Accepted for oral presentation in NetSci, 2018.

Timothy Larock, Timothy Sakharov, Sahely Bhadra, and Tina Eliassi-Rad. Learning to Complete Partially Observed Networks. Accepted for oral presentation in CompleteNet, 2018.

Sahely Bhadra, Samuel Kaski, and Juho Rousu. Multi-view Kernel Completion(link). Machine Learning 106 (5), 713-739, 2017

Sahely Bhadra, and Matthias Hein. Correction of Noisy Labels via Mutual Consistency Check (link). Neurocomputing (160): 34-52, 2015.

Aharon Ben-Tal, Sahely Bhadra, Chiranjib Bhattacharyya and Arkadi Nemirovski.Efficient Methods for Robust Classification Under Uncertainty in Kernel Matrices (link). Journal of Machine Learning Research 13 (Oct):2923.2954, 2012.

Sandeepkumar Satpal, Sahely Bhadra, S Sundararajan, Rajeev Rastogi, Prithviraj Sen. Web Information Extraction Using Markov Logic Networks (pdf). 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)2011.

Sandeepkumar Satpal, Sahely Bhadra, S Sundararajan, Rajeev Rastogi, Prithviraj Sen. Web Information Extraction Using Markov Logic Networks (Poster). International World Wide Web Conferences (WWW) 2011.

Aharon Ben-Tal, Sahely Bhadra, Chiranjib Bhattacharyya and J. Saketha Nath. Chance constrained uncertain classification via robust optimization (pdf). Mathematical Programming Series B, 2011.

Sahely Bhadra, Sourangshu Bhattacharrya , Chiranjib Bhattacharyya and Aharon Ben-Tal. Robust Formulations for Handling Uncertainty in Kernel Matrices(paper,demo). International Conference on Machine Learning (ICML) 2010.

Sahely Bhadra, J. Saketha Nath, Aharon Ben-Tal and Chiranjib Bhattacharyya. Interval Data Classification under Partial Information: A Chance-Constraint Approach (pdf). Achieved Best Runner up certificate in PAKDD-2009.

S. Bhadra , C. Bhattacharyya , N. Chandra , I.S. Mian. A Linear Programming Approach for Estimating the Structure of a Sparse Linear Genetic Network from Transcript Profiling Data (pdf, demo). Accepted for Journal of Algorithms for Molecular Biology, 2009.

Teaching Experiences

Current Course

CS4804: Convex Optimization

CS3700: Introduction to Database Systems ( theory and lab)

CS4801: Principal of Machine Learning

CS2110 Computer Programming Lab

Past Course

Convex Optimization for Big Data, spring 2016 in Aalto university along with Dr. Alexander Jung and Dr. Sabeur Aridhi.

Lectures and project supervision : Special course in Bioinformatics II (PCA in bioinformatics), 2016, Aalto University.

Teaching assistant-ship : ICS-E4030 - Kernel Methods in Machine Learning 2015 in Aalto University

Lectures and project supervision : Special course in Bioinformatics II (Learning from multiple sources), 2015, Aalto University.

Teaching assistant-ship : Machine Learning 2012-2013, Saarland University.

Other Professional Positions

  • Program committee member KDD 2017, IJCAI 2018
  • Represent IITPKD in WOMEN SCIENTIST & ENTREPRENEUR’S CONCLAVE in Indian International Science Festival 2017

Education

Research Positions

Postdoctoral research associate in Network Science Institute, Northeastern University, USA (January, 2017 - May 2017).

Postdoctoral researcher in Helsinki institute of information Technology, Aalto University, Finland (October, 2014 - December 2016).

Postdoctoral Researcher in Max-Planck-Institute for Informatik and Saarland University, Germany (September, 2012 - August, 2014).

Research Internship in NetApp, Bangalore (June, 2010 - May,2011).

Research Internship in Yahoo! Labs, Bangalore (May, 2009 - July, 2009).