The Data Science Institute at Bar-Ilan University אנחנו שמחים לבשר על קיום הכנס הראשון של המיזם הלאומי למדעי הנתונים – IDSI.
הכנס יתקיים בתאריכים 3-6/1/2022, במלון עין גדי.
תאריכים חשובים:
מועד אחרון להגשת אבסטרקטים: 25/8/21
סיום ההרשמה המוקדמת: 25/9/21
מצורף למייל קול קורא בדבר הכנס ולהגשת אבסטרקטים.
אתר הכנס ובו מידע על הכנס, אופן הרישום, הגשת אבסטרקטים ועוד:
https://idsi2022.net.technion.
פרטי הכנס גם מפורסמים באתר IDSI:
https://idsi.net.technion.ac.
The BIU AI machine learning (ML) and data science learning club aim at connecting researchers engaging in any type of ML (vision, NLP, speech, etc.) from BIU. Every week we will host researchers (mainly) from the Israeli academia and industry to further extend the knowledge of the members and to increase collaboration and innovation within BIU.
How to get information? There are several ways to get notified on learning club events:
Location and Time. The meetings are held on Sundays at 12 PM IDT. Exact details will be provided before each event.
Potential Lecturer? If you want to present your work in our learning club, please send an email to mailto:biu.learning.club@gmail.com.
(see here for calendar view)
The call for the VATAT scholarships for outstanding Postdoc students and VATAT scholarship for outstanding Data Science doctoral students in their first or second year was circulated. Details will be provided from the departments and in a separate email to the DSI members.
We are happy to share that this year the DSI will also grant scholarships for outstanding Data Science doctoral students in their first or second year, intended exclusively for the DSI members’ students. Details will come later in a separate email to the DSI members.
As part of the partnership between the Israel Data Science Initiative (IDSI) and the Helmholtz Information and Data Science Academy (HIDA) we recently circulated a call for the student exchange program. We are happy to share that we had two applications from BIU DSI members. We’ll keep updated with additional relevant HIDA programs and calls.
EUMAS 2021 Call for Papers: The 18th European Conference on Multi-Agent Systems (EUMAS ’21) is organized by Ariel Rosenfeld (Bar-Ilan) and Nimrod Talmon (BGU) and will be held (virtually) at June 28-29, 2021; the deadline for submissions is March 14, 2021. See details here: https://biu-ai.com/EUMAS21/
All relevant events are posted on the DSI website.
Workshop on State-of-the-Art NLP will be held on Thursday May 27th, 2021 at Bar-Ilan University for research faculty and research students in the social sciences and humanities who wish to use up-to-date Natural Language Processing methods in their research domains.
For more details see:
The BIU Learning club is an ongoing seminar on machine learning that takes place on Sundays featuring select speakers from Israel and abroad.
Upcoming talk by Roi Livni (Department of Electrical Engineering at Tel Aviv University)
When: Time: Sunday April 14th, 2021 12:00 PM – 13:00 PM.
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We would like to remind you that we (the DSI) maintain a list of data science courses that are given at BIU, which can be easily explored by different category types. The interactive list is available on our website:
How can we analyze and share data without jeopardizing privacy?
Dr. Or Sheffet from the Faculty of Engineering will be teaching a course on Differential Privacy.
The course studies the theory underlying differential privacy its connections to a vast array of research areas: statistics, learning theory, cryptography, computational complexity, convex geometry, mechanism design, and more.
Eng. 83908: Mon, 17:00-19:00, Online (Zoom).
Google offers a faculty credit program providing cloud credit to students. Faculty members can apply specifying the course details and will issue individual coupons (typically of $50) that students can redeem and apply to their accounts.. These coupons are instrumentless so there is no credit card needed when using these credits. If during the course a student runs out of credits, one can always issue them more. For more information please see receiving and redeeming coupons.
The Smart Transportation Center (BIU + Technoin) is running a project that requires implementing a text classification system for academic articles. They are looking for a student to work on the project on an hourly basis. Estimated 100 hours over the next 3-4 months (budget of 7,000 NIS). For context see Initial Report on Knowledge Gap Identification – Big Data and Data Analytics Committee. Anyone interested can send an email to: oren.glickman@biu.ac.il
Nvidia Deep Learning Institute (DLI) is looking for PhD students/academic faculty members who wish to be Ambassadors – certified on Nvidia courses, and who may run Nvidia courses free of charge at the universities (note – these courses are usually paid courses). Up until now there were 6 ambassadors from 3 universities in Israel, and the desire is to expand the local ambassador numbers. Running these courses at the university can be a great benefit for students and faculty – where courses vary from Fundamentals of DL to areas like NLP, Video Analytics, and more. Courses usually run as 1 day seminars.
For more information on Nvidia DLI and the Ambassador program see these two links below:
Core Data Science (https://research.fb.com/teams/core-data-science/) at Facebook Research is accepting applications for an intern position with the team in Tel Aviv for the summer of 2021. For the Tel Aviv based internship they are looking for PhD students and postdocs with experience in ML, Statistics, or CS, including PhD students from other fields that have hands-on experience with those research areas. The internship program consists of 12-16 weeks of full-time paid work. The internships are planned for summer 2021, though there’s some flexibility.
Applications can be made via https://www.facebook.com/careers/jobs/360382118322817/
The Data Science Institute at Bar-Ilan University
For further information or to unsubscribe from future updates – dsi@biu.ac.il
http://dsi.biu.ac.il/wp-content/uploads/2021/01/DSI-Updates-December-2020-.pdf
DSI Updates – Q4, 2020
We are happy to share that this year we had 3 winners:
VATAT scholarships for outstanding Postdoc students (1 out of 3 total nationwide!):
VATAT scholarship for outstanding Data Science doctoral students (2 out of 10 total nationwide!):
Recently, Bar-Ilan’s response to the Vatat Competitive Call for additional funding to the data science centers in all universities was completed and submitted by the DSI. The response to the Call, with a 4-year NIS 58 million national budget for all universities (up to NIS 16 million per institution), consisted of six strong projects proposed by 15 faculty members (PIs and Co-PIs of the submitted proposal), spread across various departments and units (CS Department, Faculty of Engineering, Math. Department, Brain Research Center, Faculty of Life Science, Faculty of Medicine, Faculty of Law and Psychology Department). We are hoping to be informed soon that Bar-Ilan won significant support, which will allow additional collaborations, enlarging the BIU DS community and enhancing computing infrastructure.
ISF opened this year, as part of its Personal Research Grants Program, a special track of Data Science in Social Sciences. BIU had 3 submissions from PIs in Engineering, Information Science, Criminology, Education and Law.
The DSI will soon come out with calls for research grants and event grants in the field of data science as well as scholarships for data science research students. We are inviting all the community members to take part and submit their proposals as the DSI Calls come out.
ELLIS (European Laboratory for Learning and Intelligent Systems) is a European grassroots initiative in AI with a focus on scientific excellence, innovation and societal impact. It aims to create a European AI Laboratory inspired by models such as EMBL (European Molecular Biology Laboratory) and the Vector Institute (Toronto).
We plan to apply to have BIU a member university of ELLIS. In meantime, we encourage all DSI faculty members to become an ELLIS member (does not require BIU to be a member). Note that there are other benefits including an ELLIS PhD Program. Existing Bar-Ilan members: Prof. Ido Dagan, Prof. Yoav Goldberg and Prof. Gal Chechik.
Vatat recently shared a report summarizing its Data Science Steering committee’s findings. We would like to thank Prof. Gal Chechik for representing Bar-Ilan in the committee and for a work well done!
Part of the report was based on a survey of 685 faculty members in Israel. Bar-Ilan stands out with over 100 faculty members from Bar-Ilan who participated in the survey. Bar-Ilan is also clearly the most diverse set of faculty members spanning over a very wide range of faculties and departments.
All relevant events are posted on the DSI website.
The BIU Learning club is an ongoing seminar on machine learning that takes place on Sundays featuring select speakers from Israel and abroad.
Upcoming talk: On Size Generalization in Graph Neural Networks and Lottery Tickets
When: Time: Sunday Jan 10th, 2021 12:00 PM – 13:00 PM.
Speaker: Gilad Yehudai from Weizmann Institute of Science
The LawData Lab has a series of events during the year, including conferences and a lab seminar, in which a number of guest speakers will be hosted. Meetings are held at Zoom. The next two events are a conference, with the Israel Tech Policy Institute, about the use of AI and algorithmic decision-making in governmental services on 26.1.21; and an international conference, with the the Jean Monnet Centre of Excellence on Digital Governance, about digital governance during Covid-19 on 17-18.2.21.
Unfortunately, during Covid we were not able to hold an on-campus community event. In the meantime, we would like to share the following story shared by Prof. Roy Gelbard (DS member, The School of Business Administration):
Dr. Anna Khalemsky, a PhD student of Roy has recently graduated (congrats Anna!). Her recent Molecular Informatics publication – “Dynamic Classification for Materials-Informatics: Mining the Solar Cell Space” by Abraham Yosipof, Anna Khalemsky, Roy Gelbard and Hanoch Senderowitz was a direct result of the institute’s second dinner. Anna presented her work as a poster as well as Avi (Dr. Abraham Yosipof, at the time a Phd Student at Chemistry Dept. under supervision by Prof. Hanouch Senderowitz) in the dinner event. The joint exposure resulted in exchanging ideas and collaboration resulting in development of a new methodology and the joint publication.
Hopefully, we will be able to all meet face to face this spring and foster more collaborations!
The University of Haifa’s Data Science Research Center offers a series of workshops for faculty members and research students who have no background in the field of data science. As part of our collaboration with the center, they have opened the workshops to DSI faculty members and their grand students. The workshop consists of 7-8 sessions (zoom), each session lasts 3 hours. To register for the workshop Introduction to Data Science without programming, fill in the following details: https://forms.gle/qES5ayNur95TmgSK6.
Please mark the date of the lecture that best suits you.
The BIU Innovation Lab for Law, Data-Science and Digital Ethics at Bar Ilan-University Faculty of Law focuses on two primary tracks: (1) data-driven legal research using various data-science methods (e.g., ML, NLP, social network analysis); (2) normative and ethical analysis, focusing on legal and regulatory aspects of big data, data analytics and AI, and on ensuring proper data governance. The lab is based on an interdisciplinary collaboration between legal researchers from the BIU Faculty of Law and data scientists from the BIU Data Science Institute and other affiliated BIU departments. It is also based on an international collaboration as part of the Jean Monnet Centre of Excellence on Digital Governance (DIGOV). It additionally works with partners from technology companies and other industry and government actors. This year, Dr. Keren Yalin-Mor, who has a background in both law and computer science, joined the lab as lab manager.
The first academic center of its kind for the study of the treatment, rehabilitation and prevention of addiction has been inaugurated at Bar-Ilan University. The center, headed by Prof. Natti Ronel from the Department of Criminology, is a joint venture of Bar-Ilan and the Retorno organization, which was founded 30 years ago by Rabbi Eitan Eckstein and operates in Beit Shemesh.
The new Bar-Ilan Retorno Center envisions two main directions: The first is the application of data science by the therapeutic community: as data from a variety of sources accumulates (e.g., weather, meal menu, community events), the community will be able to adapt treatment to the needs of the particular patient, as is done in personalized medicine, and to adapt itself to the needs of all patients. Data science will also allow for the creation of a growing body of research knowledge. The second research direction is to encourage Retorno employees to initiate and conduct research, as research physicians do at a university hospital. The Bar-Ilan Retorno Center will operate as an “impact center” in accordance with Bar-Ilan University’s preeminent research approach, which addresses the challenges of the future, integrating various fields of knowledge in multidisciplinary research.
Opening event at Retorno with Prof. Yaffa Zilbershats and Prof. Arie Zaban – see news article: https://www.inn.co.il/news/450062
Among the goals of the DSI is to strengthen and extend the data science course and program offerings at Bar-Ilan. As part of this goal, we have initiated a committee headed by the Bar-Ilan Rector, with representatives from the core data science departments. The first goal of the committee is to increase, improve and consolidate the applied data science course and program offerings in STEM departments. In parallel to this initiative, the DSI is continuing its support in this academic year for including python as the programming course of choice in multiple STEM departments, including Chemistry, Brain Science, Math and Engineering.
We would like to remind you that we (the DSI) maintain a list of data science courses that are given at BIU, which can be easily explored by different category types. The interactive list is available on our website:
For more details, please reach out to: Prof. Izhar Bar-Gad (Brain Research Center).
For details please contact Dr. Rose Stamp – rose.stamp@biu.ac.il.
Nvidia Deep Learning Institute (DLI) is looking for PhD students/academic faculty members who wish to be Ambassadors – certified on Nvidia courses, and who may run Nvidia courses free of charge at the universities (note – these courses are usually paid courses). Up until now there were 6 ambassadors from 3 universities in Israel, and the desire is to expand the local ambassador numbers. Running these courses at the university can be a great benefit for students and faculty – where courses vary from Fundamentals of DL to areas like NLP, Video Analytics, and more. Courses usually run as 1 day seminars.
For more information on Nvidia DLI and the Ambassador program see these two links below:
The Core Data Science team at Facebook Research is accepting applications for an intern position in London & Tel Aviv. They are looking for PhD students and postdocs with experience in one or more of the following fields: ML, Statistics, Computational Social Science, CS, Algorithmic Game Theory, Operations Research and adjacent areas. The internship programme consists of 12-16 weeks of full time paid work. Apply here:
The Data Science Institute at Bar-Ilan University
For further information or to unsubscribe from future updates – dsi@biu.ac.il
The Council for Higher Education’s Planning and Budgeting Committee (VATAT) shared a report summarizing its Data Science Steering committee’s findings.
Report is available here:
We would like to thank Prof. Gal Chechik for representing Bar-Ilan in the committee and for a work well done!
Containers101: Containers, Docker, Kubernetes
When: Tue 26/1/2020 14:00-16:00 (Zoom).
Registration: https://forms.gle/aNBiqc1dG1XshLp3A
If you are starting your journey into the containerized world, the first thing you’ll come across is Docker. This Webinar will give you a quick start: it will provide you with the tools to play with Docker. Also you will get a glimpse to orchestration solutions like Kubernetes and Openshift.
Docker container technology separates applications from the underlying Operating System and infrastructure. Containers technology virtualizes the Operating System (OS), and thanks to it only the application, and specific dependencies like libraries and binaries are being packaged in the image. Starting such an image is much faster omitting start of an OS. In addition the image now is very portable among various host servers running the Docker engine.
In this webinar you will learn the fundamentals and basic concepts of Containers, Docker, Kubernetes and OpenShift. The overview will be followed by a hands-on lab where you will get to build Docker images and run them.
Developers and those interested in DevOps, IT, containers and application deployment.
Jaffa Sztejnbok – Developer Advocate @ IBM
1. Go and get an IBM Cloud Account – needed for the workshop https://ibm.biz/Bdq7se
<!!> The workshop is practical, bring your laptops <!!>
For further details contact: dsi@biu.ac.il
The European Laboratory for Learning and Intelligent Systems offers an interdisciplinary PhD program. The ELLIS PhD program is a key element of the ELLIS initiative and its goal is to foster and educate the best talent in machine learning related research areas by pairing outstanding students with leading academic and industrial researchers in Europe.
The program supports excellent PhDs across Europe by giving them access to leading research through boot camps, summer schools and workshops of the ELLIS programs. Every PhD student is supervised by one ELLIS fellow/scholar and one ELLIS member from a different country and conducts a 1 year exchange at the other location.
ELLIS seeks to increase diversity and the number of women in areas where they are underrepresented and we explicitly encourage women to apply. We are committed to employing more handicapped individuals and especially encourage them to apply.
Application website: apply.ellis.eu (portal will open on October 1st, 2020)
Application deadline: December 1st, 2020, 23:59 CEST
There are a couple of open graduate students (PhD or MSc) positions in the Neural Interfaces lab lead by Prof. Izhar Bar-Gad:
Research definition: Unsupervised learning algorithms for identifying repeating behavioral motifs from the video.
Required background: Computer vision, Machine learning.
Research definition: Unsupervised learning algorithms for identifying repeating behavioral motifs from the kinematic signals.
Required background: Machine learning, Time series analysis.
For more details, please reach out to:
Izhar Bar-Gad, Ph.D.
Professor, Neural Interfaces lab
Gonda Brain Research Center
Bar Ilan University
Email: izhar.bar-gad@biu.ac.il
NICE Text analytics is looking for a Masters student for a part-time position.
For details:
http://jobs.jobvite.com/careers/nice-systems-old/job/o01udfws?__jvst=Job+Board&__jvsd=LinkedIn
We are seeking a CS or Math Master Student to do his/her thesis on a funded project on .
The Network Properties of Word Embeddings project is funded by Data Science Institute.
Participating Faculty members:
Prof. Reuven Cohen, Department of Mathematics, reuven@math.biu.ac.il
Prof. Yoav Goldberg, Department of Computer Science, yogo@cs.biu.ac.il
Dr. Simcha (Simi) Haber, Department of Mathematics, simi@biu.ac.il
Description of research work:
This work combines two strength areas of Bar-Ilan University – Network Science and Natural Language Processing – to study the network properties of word embeddings.
Word embedding — the mapping of words into numerical vector spaces — has seen tremendous success in numerous NLP tasks in recent years ([1]). Multiple methods for learning word embeddings from textual corpora have also be proposed. The resulting representations typically preserve semantic, syntactic and other properties of words. Once represented as vectors in an Euclidean space of dimension n (typically n is in the range of 50 to 500), it is natural to consider the implied graph or network of the words. In such a graph, two words are adjacent based on their distance as vectors or other similarity metric. Graphs and networks are widely used in Natural Language Processing including word graphs (e.g. [2], [3]), and it has been shown that word graphs share statistical features as other complex networks ([5]). However, the network properties of word embedding graphs have not been investigated until now.
The work will involve analyzing and comparing network properties of various word-embedding based networks – across word embedding algorithms and parameters, corpora and language and in addition study the relationship between these network properties and linguistics properties. When analyzing and comparing the word networks we will look at common network graph properties and algorithms – such as various centrality measures, clustering algorithms, page rank etc ([4]). We will also investigate properties of individual nodes (words), edges (relationships between words) and components (groups of words).
There are multiple word embedding techniques commonly used for NLP applications – e.g. Word2Vec or GloVe. The techniques vary in the underlying algorithm, the objective function and the context used for words in the text. Other parameters such as window size or embedding size also have an effect on the resulting word vectors. We will compare the networks resulting from the different algorithms and parameters.
Different textual dataset (corpora) result in different embeddings vectors as words have different usage patterns in, say, a general and quite formal corpus such as wikipedia to, say, Twitter tweets. Naturally, we will compare the different network properties across languages as well. In all cases (algorithm, corpus and language), universal network properties will be searched (e.g. whether certain centrality or other measures indifferent to language or algorithm). For measure or properties that do differ across different embedding graphs we will investigate if one can attribute or tie the differences to linguistic properties (e.g., does a certain measure correlate to the morphological richness of a language or do languages from same linguistic families have similar network properties).
This interdisciplinary work brings together experts from two different data science fields (NLP and Network Science) who will co-advise an MSc student. We expect to publish the results of this project in top venues of both fields of study.
[1] Speech and Language Processing (3rd ed.). Dan Jurafsky and James H. Martin.2019. Chapter 6: Vector Semantics and Embeddings.
[2] Graph-Based Methods for Natural Language Processing and Understanding – A Survey and Analysis. Mills, Michael T. and Bourbakis, Nikolaos G. IEEE Transactions on Systems, Man, and Cybernetics: Systems. (2014).
[3] A survey of graphs in natural language processing. NASTASE, V., MIHALCEA, R., & RADEV, D. Natural Language Engineering, 21(5), 665-698. (2015).
[4] Graph Theory. Adrian Bondy And U.S.R. Murty. Springer, 2017.
[5] The small world of human language. Ferreri and Sole. Proceedings of the Royal Society B: Biological Sciences 268(1482):2261-5. 2001.
If interested please contact Dr. Simi) Haber – simi@biu.ac.il