- 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
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).
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.
- 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.
- Automatic Pathogen Detection in plants (as Co-investigator ) a project in TIH of IITPalakkad
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) 
Responsible AI (S7, Research, Elective) 
Topics in Machine Learning(S7, Research, Elective) 
Principles of Machine Learning (S5, Elective) [2017,2018]
Convex Optimization (S6, elective)
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:
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
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
TitleOther Professional PositionsDescription
- 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
IEEE PAMI, Bioinformatics, PlosOneTitleInvited TalkDescription
'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
Shikha Mallick, Sahely Bhadra:Lecture Notes in Computer Science, 13976 ( Preceeding of Research in Computational Molecular Biology (RECOMB)) 104--119 (2023)Timothy LaRock, Timothy Sakharov, Sahely Bhadra, Tina Eliassi-Rad:Applied Network Science 5 (1) 60 (2020)Viivi Uurtio , Sahely Bhadra and Juho RousuProceedings of the 36th International Conference on Machine Learning(ICML) 6383--6391 (2019)Anish Mathew, Deepak P and Sahely BhadraICML 2019 Time Series Workshop (2019)Sahely BhadraP D., Jurek-Loughrey A. (eds) Linking and Mining Heterogeneous and Multi-view Data. Unsupervised and Semi-Supervised Learning. Springer, Cham 1-25 (2019)Viivi Uurtio, Sahely Bhadra, Juho RusuIEEE International Conference on Data Mining (ICDM'18) (2018)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)Timothy LaRock, Timothy Sakharov, Sahely Bhadra and Tina Eliassi-RadAccepted for 14th International Workshop on Mining and Learning with Graphs (MLG) (2018)Sahely Bhadra and Juho RousuSpringer Book : Data Mining for Systems Biology (2018)PMFA_Book_Chapter_springer.pdf (364.17 KB)Sahely Bhadra, Peter Blomberg, Sandra Castillo, and Juho Rousu.Bioinformatics 34 (14) 2409–2417 (2018)Sahely Bhadra, Samuel Kaski, Juho RousuMachine Learning 106 (5) 713-739 (2017)Sahely Bhadra, and Matthias HeinNeurocomputing 160 34-52 (2015)