Last date of receipt of application is
List of selected participants will be displayed in the website on
Applicants are requested to visit the website for regular updates about the workshop.
Data science has become ubiquitous in modern society. A staggering amount of data is being generated and stored each day all over the world. This data is mostly related to social media, travel, communication, transactions, treatment, education, etc. The size and number of this “big” data have been increasing exponentially and will continue to grow at an accelerating rate for the foreseeable future. On a macroscopic level, most of this generated data is unused and might be discarded after sometime. Effective analysis of these huge collections of apparently insignificant data can be very beneficial for companies, governments, medical organisations, etc. Despite the advancements in the broad field of computer science, storing, managing, processing and mining this “big” data is still a significant challenge. Machine learning plays an important role when it comes to making this “big” data useful. It creates a platform which helps to extract, understand and learn the underlying structure of this data. Traditional machine learning methods are not suitable for handling big data, hence they need to be adapted or new methods need to be evolved to tackle this situation. All this needs to be done for the “value” that this “big” data holds. This value will have a significant impact on a wide range of domains including health care, research, web services, finance & business informatics, scientific computing, and many others.
The aim of this workshop is to gather experts in Data Science and Machine Learning, and facilitate the participants to get both theoretical and hands-on experience on different aspects of this subject. The workshop will provide a forum for exchanging ideas and information on current research studies, challenges, system developments, and practical experiences in this emerging field of Data Science and Machine Learning.
An application form is enclosed with this announcement. It may also be downloaded from the website. Interested candidates should send the scanned copy of filled-in application form and demand draft by e-mail within 10 March, 2017. Selected candidates should send their applications by post by 13 March, 2017. Envelope super-scribed as “DSML'17” containing the filled in application form along with the requisite demand draft or bank transfer details should be sent to: The Coordinator, DSML'17, Center for Soft Computing Research, Indian Statistical Institute, 203, B. T. Road, Kolkata 700108.
Click here to download the Application Form
By Demand Draft - drawn in favour of INDIAN STATISTICAL INSTITUTE payable at KOLKATA. Please write your NAME and CURRENT AFFILIATION on back of the Draft.
By Online Transfer - BANK ACCOUNT NUMBER: 0071050000118,NAME OF THE BANK: UNITED BANK OF INDIA,
ACCOUNT HOLDER NAME: INDIAN STATISTICAL INSTITUTE,
MICR CODE: 700027046, NEFT/RTGS IFSC CODE: UTBI 0 DLB140,
SWIFT CODE: UTBIINBBOBC,
BANK ACCOUNT NUMBER: 0071050000118, NAME OF THE BANK: UNITED BANK OF INDIA, ACCOUNT HOLDER NAME: INDIAN STATISTICAL INSTITUTE, MICR CODE: 700027046, NEFT/RTGS IFSC CODE: UTBI 0 DLB140, SWIFT CODE: UTBIINBBOBC
Center for Soft Computing Research
203 B. T. Road, Kolkata - 700108, India
Option 1 (recommended): Taxis are readily available outside station. Tell them to drive to Indian Statistical Institute (Before Dunlop bridge crossing)
Option 2: By train: go to Dumdum junction (just 2 stations from Sealdah in local trains). Outside Dumdum station, auto ricksaws are available to go to Sinthee more. From Sinthee more, you can find bus or auto towards ISI.
Option 3: By bus: Outside Sealdah station, you can find many buses towards ISI. Among them 230 and 234 are very frequent.
Option 1 (recommended): Prepaid taxis are readily available outside station. Tell them to drive to Indian Statistical Institute (Near Dunlop bridge crossing)
Option 2: By train: go to Bali junction (just 3 stations from Howrah in local trains). Go outside Bali station, walk a little bit and take the stairs to go up the overbridge. There auto ricksaws are available to go to Dunlop more. From Dunlop more, you can either walk for 5 minutes or find bus or auto towards ISI. Otherwise you can take buses also from the overbridge to ISI (Belurmath-Garia etc).
Option 3: By bus: Outside Howrah station, you can find many buses towards ISI. There are some mini-buses (Belgharia-Howrah, etc) and some buses in Barrackpore-Howrah route, which can take you to ISI.
Option 1 (recommended): Prepaid taxis are readily available from airport. Tell them to drive to Indian Statistical Institute (Near Dunlop bridge crossing)