Home CioAxis ICMLDS 2019: 3rd International Conference on Machine Learning and Data Science conducted at MEC, Hyderabad

ICMLDS 2019: 3rd International Conference on Machine Learning and Data Science conducted at MEC, Hyderabad


Researchers and practitioners deliberated on Algorithms, Systems, Applied and Research aspects of Machine Learning and Data Science

The 3rd International Conference on Machine Learning and Data Science (ICMLDS 2019) technically co-sponsored by ACM Digital Library was held at Mahindra Ecole Centrale (MEC), Hyderabad.

The two-day conference (held on 16th & 17th of December 2019) focused on topics that are of interest to computer and computational scientists and engineers. ICMLDS-2019 brought together researchers and practitioners from academia, industry, and government to deliberate on the algorithms, systems, applied, and research aspects of Machine Learning and Data Science. The conference featured multiple eminent speakers, and presentations of peer reviewed original research papers and exhibits.

Mr. Navin Mittal, Commissioner, Collegiate Education & Technical Education, Government of Telangana, inaugurated the conference. Prof. Prafulla Kalapatapu, from the Computer Science department at MEC and Prof. Sartaj Sahni, Distinguished Professor of Computer Science, University of Florida, were the General Co-chairs of the conference.

Delivering the welcome address, Dr. Yajulu Medury, Director, Mahindra Ecole Centrale said, “MEC is proud to be hosting the third ICMLDS and we are happy that some of the biggest names in the industry are partnering with the conference. Machine Learning, Big Data and Data Sciences are so much a part of our lives today that we barely even notice them or realize the breakthrough scientific research that made them possible. We at MEC are committed to partnering research in the segment and have set up a specialized Artificial Intelligence and Machine Learning Research Centre on campus”.

In his inauguration address, Mr. Navin Mittal, focused on the coming together of a truly international community for the ICMLDS 2019 including many renowned global experts of Machine Learning and Data Sciences. He reiterated that the whole field is getting increasingly integrated in our lives. Giving examples from the Technical Education Departments’ focus, he said that the answer scripts of students are being run through an AI engine as a pilot and digitized the complete process. He also stated that in Government of India’s Smart Cities Project, increased use of ML & Data Integration is helping us avoid wastage and is instrumental in keeping us safe.

The main speakers over the two days included Prof Viktor K. Prasanna, University of Southern California, Sri Ram D. Sriram, Chief, National Institute of Standards and Technology (NIST), Prof Srinivas Aluru, Georgia Institute of Technology, Prof Rama Govindaraju, Director of Engineering, Google AI, Prof Ananth Kalyanaraman, Pullman, WA, Prof Dhabaleswar K. Panda, The Ohio State University, Prof Laxmidhar Behera, IIT Kanpur, Prof Sanjay Ranka, University of Florida, Mr. Ananda Deshmukh, Lead AI, TechM, Prof Arya K Bhattacharya, Dean Research, Mahindra Ecole Centrale, among others.

The various tracts of Machine Learning included Model Selection, Evolutionary Parameter Estimation, Graphs and Social networks, Non-parametric Model for Sparse Networks, Large Scale Machine Learning, Learning Paradigms, Deep Learning, Recommender Systems, Applications and Evaluation of Learning Systems.

In Data Science, the focus was on all aspects including Algorithms, Novel Theoretical and Computational Models, Data and Information Quality, Data Integration and Fusion, Data Acquisition, Integration, Cleaning, Mining, Data Wrangling, Data Cleaning, Data Curation, Data Munching, Data Analysis, Statistical Insights and Decision Making, Data Science technologies, tools, frameworks, platforms and APIs and Applications.

A large number of research papers were submitted to the conference and a few were chosen to be presented at the conference after a stringent technical review process.

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