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INDIAN INSTITUTE OF TECHNOLOGY PALAKKAD
Kanjikode | Palakkad | Kerala - 678623
0491 209 2001 (Office) | info@iitpkd.ac.in

Main Navigation

  • About Us
    • The Institute
      • Journey so far
      • Chairman BoG
      • Director
      • Director's Message
      • Governance
      • Advisory Council
      • Senate
    • Infrastructure & Support
      • Hostels
      • Guest House
      • Career Development Center
      • Institute Clinic
      • Wellness Hub
      • English Language Support
    • Quick Glance
      • Vision
      • Our Logo
      • Reports and Brochures
  • Academics
    • Departments & Centres
      • Biological Sciences and Engineering
      • Chemistry
      • Civil Engineering
      • Computer Science & Engineering
      • Data Science
      • Electrical Engineering
      • Environmental Sciences and Sustainable Engineering Centre
      • Humanities and Social Sciences
      • Mathematics
      • Mechanical Engineering
      • Physics
    • Programs
      • Course-based Programs
      • Research Programs
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    • People
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Dr. Sahely Bhadra
Associate Professor
, Computer Science And Engineering
Data Science
Research Area: Machine Learning, Research Area: Optmization, Research Area: Bioinformatics
View Website
  • Biosketch
    • Assistant Professor (Jun, 2017 -Till date)
    • Postdoctoral researcher
      • Max-Planck-Institute for Informatik and Saarland University, Germany (Sep, 2012 - Aug, 2014)
      • Helsinki Institute of Information Technology, Aalto University, Finland (Oct,2014 - Dec,2016)
      • Network Science Institute, Northeastern University, USA (Jan, 2017 - May 2017)
    • PhD in Computer Science (Aug, 2006 - Sep, 2012)
      • Indian Institute of Science (IISc), Bangalore
      • Adviser: Chiranjib Bhattacharyya
      • Thesis: Learning Robust Support Vector Machine Classifiers with Uncertain Observations
    • Software Engineer (Jul, 2004 - Jul, 2006)
      • Wipro Technology, Bangalore
    • B.Tech in Information Technology (Apr, 2000-May, 2004)
      • RCC Institute of Information Technology, Kalyani University, Kolkata
  • Research

    Research interest:

    Machine Learning (learning from noisy, incomplete data and multi-view data), optimization (robust optimization and convex optimization for large data), Time series data (anomaly detection), bio-informatics (micro-array data analysis and molecular network analysis).

    Awards:

                     Indo-Finish Mobility grand 2019-2020 from DST and Academy of Finland (June-July 2019).

                     IMPECS postdoc fellowship, 2012-2014.

                     IBM Ph.D. Fellowship Award 2010 - 2011.

                     Best Runner Up paper award in PAKDD, 2009.

    Research Grant:

    1.  Core Research Grand (CRG) from SERB, DST of around INR 3.5m on Project titled "Robust Multi-view Learning for Extreme Events Detection and Prediction in Time Series Data “. 2021-2024.
    2. Automatic Pathogen Detection in plants (as Co-investigator ) a project in TIH of IITPalakkad

     

     

  • Teaching

    Core Courses

    Optimization (MTech Data Science S1 , Research Scholar, Elective)[2020,2021,2022]

    Machine Learning (MTech Data Science S1 , Research Scholar, Elective) [2019,2020,2021,2022]

    Machine Learning Lab(MTech Data Science S1, Research Scholar, Elective)[2020,2021]

    Introduction to Database Systems (S6, Core, Theory)  [2018,2020]

    Introduction to Database Systems Lab (S6, Core, Laboratory) [2018,2021,2022]

    Computer Programming Lab (S3, Core, Laboratory) [2017]

     

    Elective Courses 

     Responsible AI (S7, Research, Elective) [2022]

    Topics in Machine Learning(S7, Research, Elective) [2018]

     Principles of Machine Learning (S5, Elective) [2017,2018]

    Convex Optimization (S6, elective)[2019]

  • Research Group

    PhD Students:

       Ms Abilasha (since August,2018)

       Ms Jishy (since August 2019, External registration)  

       Ms Vinitha Rajan (since August 2021) 

       Ms Vineetha (since August 2021)

       Mr Vishnu B (since January 2022)

       Mr Ankit (since August 2022)

     

    Graduated PhD Students:

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

    Graduated PhD Students:

         Shikha Mallick (July 2022)

    MTech project students:

    Ms Sneha (2020-2022) : Analysis of FRB data

    Ms Akshata (2020-2022) : Analysis of road network

    Ms Pallavi (2020-2022) :  Deep CCA doe graphs

    Mr Abhichal (2020-2022) : Automatic count of fruits

    BTech projects students:

         Ahmed Zaheer Dadarkar (2017-2021): Extreme Value prediction in Time series data

         Vipin Kumar Seth (2017-2021): Rainfall prediction in a small region around Palakkad 

         Ipsita Singh  (2016-2020): Learning Graph Embedding for Graph Classification

         Adrian McDonald Tariang (2015-2019):  Automated Newspaper Typesetting based on News Values and Prior Editorial Style

         Akshat Choube(2015-2019): Study of Multiview Face Synthesis Using Generative Adversarial Networks (GANs)

         Anish MM (2015-2019): Unsupervised Lower Dimensional Representation Learning for Time Series Data

         Prabal  Vashisht (2015-2019): Multi-view data interpretation and completion using Deep Networks

     

  • Additional Information
    Title
    Other Professional Positions
    Description

    Organizing:

    • Workshop on Smart and Precise Agriculture in PAKDD 2021. 
    • One-day Symposium on Data Science in IIT Palakkad 2020.

    • Young Researchers’ Symposium Chairs in CODS COMAD 2019

    Program committee member:

    NIPS , IJCAI , ICML, AAAI, DSAA , KDD etc

    Reviewer:

    IEEE PAMI, Bioinformatics, PlosOne

    Title
    Invited Talk
    Description

    'Principle Flux mode analysis', Indo-German Frontiers of Engineering Conference (INDOGFOE 2021) Symposium, by IIT KGP, 24 February - 26 February 2021

    'Linear Models for Classification', The ACM India summer school on ML and Data Science, by IITM, 4th June - 13th June 2018.

    'Machine Learning in Bioinformatics and Health care',  ICMR workshop " Harnessing the power of oncology data analytics for early diagnosis and treatment" 15th February - 16th February 2018

    Title
    Tutorial
    Description

    Problems with Partially Observed (Incomplete) Networks: Biases, Skewed Results, and Solutions (with Tina Eliassi-Rad and   Sucheta Soundarajan ) [SIAM SDM 2018] Abstract, Slides, and Resources

  • Publications
    Warping resilient robust anomaly detection formultivariate time series
    S. Abilasha, · Sahely Bhadra
    Machine Learning (2025)
    CDGCN: Conditional de novo Drug Generative Model Using Graph Convolution Networks.
    Shikha Mallick, Sahely Bhadra:
    Lecture Notes in Computer Science, 13976 ( Preceeding of Research in Computational Molecular Biology (RECOMB)) 104--119 (2023)
    Understanding the limitations of network online learning.
    Timothy LaRock, Timothy Sakharov, Sahely Bhadra, Tina Eliassi-Rad:
    Applied Network Science 5 (1) 60 (2020)
    Large-Scale Sparse Kernel Canonical Correlation Analysis
    Viivi Uurtio , Sahely Bhadra and Juho Rousu
    Proceedings of the 36th International Conference on Machine Learning(ICML) 6383--6391 (2019)
    Warping Resilient Time Series Embeddings
    Anish Mathew, Deepak P and Sahely Bhadra
    ICML 2019 Time Series Workshop (2019)
    Book Chapter: Multi-View Data Completion
    Sahely Bhadra
    P D., Jurek-Loughrey A. (eds) Linking and Mining Heterogeneous and Multi-view Data. Unsupervised and Semi-Supervised Learning. Springer, Cham 1-25 (2019)
    Sparse Non-Linear CCA through Hilbert-Schmidt Independence Criterion
    Viivi Uurtio, Sahely Bhadra, Juho Rusu
    IEEE International Conference on Data Mining (ICDM'18) (2018)
    Limits of Learning in Incomplete Networks
    Timothy Larock, Timothy Sakhrov, Sahely Bhadra and Tina Eliassi - Rad.
    International School and Conference of Network Science (NetSci) (2018)
    larock_netsci18.pdf (7.61 MB)
    Reducing Network Incompleteness Through Online Learning: A Feasibility Study
    Timothy LaRock, Timothy Sakharov, Sahely Bhadra and Tina Eliassi-Rad
    Accepted for 14th International Workshop on Mining and Learning with Graphs (MLG) (2018)
    Book Chapter: Analysis of Fluxomic Experiments with Principal Metabolic Flux Mode Analysis
    Sahely Bhadra and Juho Rousu
    Springer Book : Data Mining for Systems Biology (2018)
    PMFA_Book_Chapter_springer.pdf (364.17 KB)
    Principal Metabolic Flux Mode Analysis
    Sahely Bhadra, Peter Blomberg, Sandra Castillo, and Juho Rousu.
    Bioinformatics 34 (14) 2409–2417 (2018)
    Multi-view kernel completion
    Sahely Bhadra, Samuel Kaski, Juho Rousu
    Machine Learning 106 (5) 713-739 (2017)
    Correction of Noisy Labels via Mutual Consistency Check
    Sahely Bhadra, and Matthias Hein
    Neurocomputing 160 34-52 (2015)

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