The Data Science Institute at Bar-Ilan University

Open Master Thesis Position in Networks and NLP

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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

MA Student Required for Research Project about Sign Languages

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Seeking to recruit an MA student with python/data-science skills for work on a funded project led by Dr. Rose Stamp in the English Literature & Linguistics department. The project will include analysis of sign language and motion capture data using machine learning and python scripts.

50% position. Work may result in academic publications.

For details please contact Dr. Rose Stamp – rose.stamp@biu.ac.il

CFP – Machine Lawyering Conference: Human Sovereignty and Machine Efficiency in the Law

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Call For Papers
Machine Lawyering Conference: Human Sovereignty and Machine Efficiency in the Law

14 Jan 2021 – 16 Jan 2021, The Chinese University of Hong Kong, Hong Kong (or virtual)

Automation is efficient: data is gathered, processed and used to do things people cannot. Yet we have lived in a world run by and for humans, in which human sovereignty has seemed to be more important than efficiency of performance. Sovereignty and efficiency are beginning to show strong potential for conflict. For the law, this presents questions at every stage: the nature and protection of data, the manner in which it is communicated and stored, the models and algorithms according to which it is processed, the authority it is given to act, and the people whose labor it replaces. Conceptually, this evolution presents legal academics with questions ranging from the nature of society (human centered or efficiency centered?) and data to the shape of technical rules for the construction of algorithms and the supervision of automated execution.

The CUHK Law Faculty’s Centre for Financial Regulation and Economic Development (CFRED) created Machine Lawyering in 2017 to offer an umbrella under which all of the above issues can be explored. Participants in the first Machine Lawyering conference, January 2020, presented papers on issues from the consciousness of artificial intelligence to the ability of fintech applications to manipulate market prices and the use of automation in the practice of law. It created a very effective cross-pollination of ideas for all participants. Machine Lawyering’s second conference in 2021 will be equally broad.

We hope to hold the conference physically in Hong Kong, but will also work through virtual presentations, so please do not let uncertainty regarding travel dissuade you from submitting a paper. A number of best paper prizes (round trip economy to Hong Kong and three nights’ accommodation) will be offered.

These are the RELEVANT DATES:
Abstract (max 350 words) submission: 14 September 2020
Notification of acceptance: 16 October 2020
Paper submission for best paper prize 2 November 2020
Registration deadline for accepted authors: 7 December 2020
Draft paper submission for all authors: 8 January 2021

TOPICS: For the avoidance of doubt, papers on the following topics are within the conference scope:
– Algorithms and profiling (from KYC to oppression)
– Big Data and data analytics in finance, regulation, scholarship and society
– Competition law in the big data industries
– Cybersecurity
– Emerging alternative finance
– Facial recognition: special problems
– Intellectual property in automated systems
– Legal treatment of AI-driven operations and services
– Nature and regulation of payment systems (cryptoassets, stored value, mobile payment, non-bank systems)
– Personal data, including nature, collection, processing and use
– Social consequences of automation for the workforce
– Special problems of distributed ledger technology

SUBMISSION PROCEDURE: Please submit abstracts via email to Bonnie Leung at swleung@cuhk.edu.hk. Please provide an attached file with an anonymous, blind copy of your abstract, but indicate your name, contact details, and the proposed paper title in your cover email. The subject line of the email should state “Submission for Machine Lawyering Conference.” Further information is available on the Machine Lawyering website.

Research Assistant – Open Position

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Position closed

 

Seeking a research assistant for a project by Dr. Gabrielle Gayer, Prof. Offer Lieberman and Prof. Itzhak Gilboa — “אמידת כללים: טכניקות מבוססות-עצים כמודלים קוגניטיביים” .

Project includes analysis of large database of real-estate prices in Australia and applying prediction models to estimate prices via machine learning techniques such as decision trees and random forests.

65%-75% position for up to three years.

Proper background in programming and data science required.

If interested please contact Gabi at gabi.gayer@gmail.com.

 

 

 

 

מגשימים AI

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קול קורא למנטורים בתחום בינה מלאכותית: למידת מכונה ומדעי הנתונים

אמ;לק: אנחנו מחפשים את עזרתך להנחות מקצועית זוג תלמידי י”ב מצטיינים בפרויקט AI. שעה בשבוע בזום. (הרשמה)

(אנו משתמשים בלשון זכר לשם הקיצור, הפניה היא לזכר ונקבה כאחד.) ההנחיה מתאימה לתלמידי מאסטר ודוקטורט, פוסטדוקים וחברי סגל בתחום למידת מכונה ומדעי הנתונים.

מזה עשר שנים פועלת בישראל תוכנית לאומית בשם מגשימים להכשרת תלמידי תיכון בעלי יכולות גבוהות בתחום מדעי המחשב המגיעים מהפריפריה החברתית. תלמידים שעוברים את המיונים, עוברים הכשרה במקביל ללימודי התיכון בתחומי מדעי המחשב, רשתות, סייבר ותכנות. בכיתה י”ב הם מממשים פרוייקט מעשי בהיקף נרחב, שעליו הם מקבלים ציון בגרות. את הפרויקט מלווים “מנטורים” מקצועיים שמייעצים לחניכים בהיקף של שעה בשבוע. 70% מבוגרי התוכנית מתגייסים למערכי הסייבר במערכת הביטחון. בעבר, רוב הפרויקטים היו בתחומי הסייבר, אך כיום כשני שליש מהחניכים מעוניינים בפרויקטים בתחומי למידה ובינה מלאכותית. 

הדרישה הגוברת הזו לפרוייקטי י”ב  בתחום ה- AI מהווה הזדמנות מיוחדת להכשיר תלמידים. לכן, ביחד עם מגשימים, אנחנו בונים הרחבה של התוכנית והפרוייקטים לתחום. ישראל נמצאת היום בתנופה בתחומי הבינה המלאכותית, עם ביקוש עצום למומחיות בתחומי למידת מכונה ומדעי הנתונים ומחסור בידע נגיש. יש לנו הזדמנות נדירה שמשיגה מספר מטרות: להנגיש את הידע האקדמי לתלמידים, לפתח אצל סטודנטים חוקרים את היכולת להנחות פרוייקטים, לקדם פריפריה חברתית בישראל, וליצור ידע בעברית שיהיה נגיש למתחילים בתחומי ה- DS/ML. תוכנית מגשימים כבר הוכיחה שיש להם תהליך מנצח כולל איתור ושימור תלמידי מרקעים לא פשוטים, ואפשר לרתום אותה כדי לקדם AI בישראל, ואת ישראל ב- AI.  

אנחנו מחפשים מנטורים שיכולים להנחות מקצועית את החניכים במשך כשעה בשבוע בזום. התפקיד כולל הכוונה מקצועית, איפיון בעיית הלמידה, הכוונה באילו ארכיטקטורות ואלגוריתמים להשתמש וכיצד לבחון את המודלים שנלמדו.

עבורך, זוהי הזדמנות להתנדב ולתרום לחברה הישראלית, לחלוק את הידע שלך, להתנסות בהנחייה של פרויקטים בתחום הלמידה, לגדל דור חדש בתחום הלמידה והבינה המלאכותית, ולסייע במקום שבו למומחיות שלך אין תחליף. 

למתעניינים נספק מידע נוסף והנחיות.

מידע מפורט על תוכנית מגשימים סייבר נמצא כאן אתר התוכנית כאן.

אם זה יכול לעניין אותך, השנה או בשנים הבאות, אנא מלא את הטופס בקישור הבא.

פרופ’ גל צ’צ’יק 

פרופ’ שי מנור

דר’ חגי מרון

דר’ גל דלל

 

DSI Updates – July 2020

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(pdf version)

Official Recognition of the DSI 

During the previous semester the University Senate Central Committee (Vaada Merakezet) approved the establishment of the Data Science Institute at Bar-Ilan University. We are now an official Institute! 

DSI 2020 Research Grants

General Research Grants

This was the first year in which the DSI awarded research grants in data science. The response to the call was very impressive, we received a wide range of proposals, with many collaborations, from 23 departments overall! In total, 57 proposals were submitted by 74 researchers, of which 41 were full (for Regular Grants) and 16 small (for small-scale Grants). The competitive review process consisted of a review committee made up of 10 members of the Bar-Ilan faculty from various fields. Each proposal was reviewed by 2-3 referees (some external). At the end of the very competitive process, a total  of NIS 950K was granted to 16 projects (9 large and 7 small) proposed by 36 researchers from 15 different departments, reflecting collaborations between different disciplines. 

The list of the granted research projects is available on the DSI website:  

DSI 2020 call for Research Grants – List of Accepted Grants

A call for the next academic year is expected towards the end of 2020.

Corona Research Grants

Due to the reduction in event activity this year, and triggered by the Corona virus pandemic, we have shifted some of this year’s event budget in favor of a call for research grants that aim to help with the challenges the world is facing due to the coronavirus (COVID-19) outbreak.

We have received 10 proposals that were submitted by 11 researchers from 8 departments, of which 5 (by 6 researchers from 3 different departments) were approved,  awarded NIS 98K in total. 

The details of the granted projects are available on the DSI website: 

DSI 2020 Call for Research Corona Grants – List of Accepted Corona Grants

We are happy to share that we are already seeing initial fruits from this work – The work of Dr. Milana Frenkel-Morgenstern has already resulted in a paper recently published in the Journal of the American Medical Informatics Association as well as coverage in the mass media.

Vatat Call for Phd and Postdoc scholarships

TASHAF is the second year in which the DSI facilitates the process of selecting Bar-Ilan’s candidates for the VATAT scholarships for outstanding Phd and Postdoc students. This year we received 4 Postdoc scholarship applications from 3 departments, 2 of which were selected and submitted to VATAT. For the Phd scholarships we received applications from 9 candidates from 5 departments, 5 of which were selected and submitted to VATAT.

We are happy to share that this year Bracha Laufer Goldstein from the Faculty of Engineering won the VATAT scholarships for outstanding Postdoc students (she is one of the three selected nationwide by VATAT to receive this scholarship!) The winners of the PhD scholarships for this year were not announced yet. 

Last year, two candidates from Bar-Ilan, Yuval Nirkin from the Faculty of Engineering and Yanai Elazar from the Department of Computer Science, received the VATAT scholarship for outstanding Data Science doctoral students.  

Future Calls 

Competitive Call (VATAT)

Israel’s Planning and Budgeting Committee (Vatat) has recently came out with a 4-year NIS 58 million competitive call for additional funding to the data science centers. The DSI is leading Bar-Ilan’s response (Due Oct 1,  2020) and is assembling the 3-6 projects that will constitute the response. We are hoping to put up a strong response competitive with the best proposals of other universities.

ISF – Data Science and Social Science track

ISF has recently opened a special ISF track for collaboration between Data Science Researchers and Researcher in Social Sciences. We’ll be glad to help with pairing interested researchers and helping with the submissions. 

Computing

  • The DSI maintains a cluster of over 10 servers that are available for computing needs of research projects of the DSI members. In addition to the support of Bar-Ilan’s computing center we are using professional support and operation services from a local company. On our agenda is putting up better maintenance and monitoring tools and processes as well as purchasing and integrating additional fast storage, setting up a scheduling system and adding additional compute power.  
  • Support – on a weekly basis we deal with multiple support issues related to the cluster. Yossi Kleiner, from the professional services company, has been helping with many of them. If you have support issues – anything from hardware and software failures to help with running docker containers or optimizing your deep learning code – please send an email to support@dsi.biu.ac.il.
  • We recently assembled an order of 13 (mostly GPU based) servers for 6 faculty members. The servers will be added to the DSI cluster and will be available for use by individual researchers and their labs. Down the road, once we have a proper scheduling system in place, we hope to implement a scavenger queue in which these resources will be available to others when idle, In this way we will effectively enlarge the available compute power for all through sharing of idle resources.  
  • Cloud Computing – Please note that the big cloud computing players have various offers including free cloud credit for academia:
    • Google Cloud – Apply here for research credits
    • Amazon AWS and Oracle Cloud Platform have similar free credit for projects – let us know if interested
    • Microsoft (Azure) – see offer for academia

Education

  • During this past academic year the DSI facilitated and helped opening new data science  courses and programs – 
    • Chemistry and Data Science Programs (Undergraduate and M.Sc.) including a joint program in Chemoinformatics with the University of Strasbourg
    • Programs in Mathematical Finance and Data Science (M.A.), and Brain Science and Data Science (Undergraduate) – awaiting approval
    • Python and Data Science courses for STEM students offered by the Mathematics Department – These courses were attended by more than 150 students from various departments, including Life Sciences, Mathematics, Brain Research Center, Geography and Chemistry.
    • Two new Data Science courses offered by Humanities and Jewish Studies open to other departments 
    • Planning to continue courses and support during upcoming academic year 
  • See our interactive list of Data Science related courses and advise your students to observe it when planning their registration for the next academic year.

DSI Members: Congratulations, Awards and Grants 

Best Paper Awards

  • Congratulations to Prof. Gal Chechik from the Brain Research Center and Dr. Ethan Fetaya from the Faculty of Engineering for winning the Outstanding Article Award at the ICML International Conference in Machine Learning. 

The article “On learning sets of symmetric objects” received the Outstanding Article Award (along with one more article) at the ICML International Conference in Machine Learning. 4990 articles were submitted to the conference, of which 1088 were accepted for publication and two outstanding articles were selected.
The lead author of the study is Haggai Maron from the NVIDIA Research Center in Israel. The other co-authors are Dr. Or Litani from Stanford, and Dr. Ethan Fetaya from the Faculty of Engineering and Prof. Gal Chechik from the Gonda Center for Brain Research at Bar Ilan University.
The article deals with the architecture of deep networks that learn to classify groups of structured objects. The architecture takes into account the structure of the group, as well as the structure of the objects. The article demonstrates what network architectures can capture such structures, and shows the empirical benefits of the method in a wide range of learning problems on groups, images, and graphs. This is a problem in a new field called geometric deep learning. For those interested, Ethan Fetaya gave a Learning Club talk on this work on Sunday 26.07 and a workshop on the subject will be held on August 2.

Awards

  • Congratulations to Prof. Sarit Kraus from the Computer Science Department on winning the ACM Athena Lecturer title on behalf of the ACM Association. 
  • Congratulations to Prof. Daniel Levy from the Department of Economics on his appointment as President of the Israel Economic Association.
  • Congratulations to Dr. Yogev Kivity from the Psychology Department for winning the Alon Scholarship. 
  • Congratulations to Dr. Yogev Kivity from the Psychology Department for winning the Taylor & Francis – Society for Psychotherapy Research (SPR) Emerging Young Scholars Award for the third time in a row.
  • Congratulations to Dr. Dana Atzil from the Psychology Department for winning the Outstanding Award for Young Outstanding Researcher (Award Early Career award) from the International Association for the Study of Psychotherapy (Research Psychotherapy for Society).
  • Congratulations to Prof. Noa Aharony from the Department of Information Science on her appointment as Israel’s representative to the COST program on the European Network for Gender Balance in Informatics.

ISF 2020/21 grant winners

  • ISF Personal Research 2020/21 grant winners:
    • Prof. Sarit Kraus, Computer Science Dept.  “Coordination between Defenders in Defensive Games”.
    • Dr. Or Sheffet, Faculty of Engineering. “Privacy Data Analysis: New Models, New Algorithms and New Applications”. 
    • Prof. Yoram Louzoun, Mathematics Dept. “Algorithms for Improving Survival After Bone Marrow Transplant”. 
    • Dr. Burov Stanislav (Stas), Dept. of Physics. “Non-Gaussian Universality of Transformed Medium Transport”. 
    • Dr. Adam Zaidel, Brain Research Center. “Perception of Self-Movement in Rats and Humans: Behavior, Relationship, and the Neural Base.” 
    • Prof. Cyrille Cohen, Faculty of Life Sciences “T Cell Metabolism Engineering to Strengthen the Immune Treatment of Cancer”. 
    • Prof. Shulamit Michaeli, Faculty of Life Sciences, “rRNA Work and the Importance of rRNA Modifications to the Ribosome Function and Unique Translation in both Life Forms”. 
    • Dr. Yaakov Maman, Faculty of Medicine. “Deciphering the Genomic Language Underlying the Specificity of DNA Editing Mechanisms for Regions Encoding Antigen Receptors”.  
      • As well as an Equipment for New Faculty Members grant.
    • Orit Shefi, Faculty of Engineering. “Nerve Cell Engineering at the Single Cell Level”. 
    • Dr. Rose Stamp, Department of English Literature and Linguistics. “Corpus-based Sociolinguistic Research of Sign Languages in Israel”. 
      • As well as an Equipment for New Faculty Members grant – “Linguistic Analysis of Sign Language Using Motion Capture Technology”.
      • Note – this is a follow up funding on a DSI 2020 research grant. 
    • Dr. Jonathan Rubin, Department of Land of Israel Studies and Archaeology. “Acceptance of Latin Descriptions of the Holy Land from the Twelfth and Thirteenth Centuries”. 
      • Note – this is a follow up funding on a DSI 2020 research grant.
    • Prof. Liat Ayalon, School of Social Work. “Age and Interracial Tension in the Age of Climate Change”. 
    • Prof. Rachel Dekel, School of Social Work. “United Front: A Multi-Systematic Random Psychophysiological Assessment of Targeted Couple Intervention in Post-Traumatic Syndrome”. 
    • Prof. Yuval Feldman, Faculty of Law.  “Behavioral Regulation of Fraud: How, When and Why Using Declarations Can Reduce Cheating and Increase Trust and Regulatory Effectiveness”. 
    • Dr. Elana Zion Golumbic, “Time Attention Fluctuations: Cognitive and Brain Mechanisms at the Basis of Language Processing in a Multilingual Environment”. 
    • Dr. Yogev Kiviti, Department of Psychology. “Fluctuations in Mentalizing Ability and their Contribution to the Difficulties of Regulating Emotions in the Daily Lives of People with Borderline Personality Disorder.” 
      • As well as an Equipment for New Faculty Members grant – “Laboratory for Dyad Observational Psychophysiological Assessment and Outpatient Assessment System”..
      • Note – this is a follow up funding on a DSI 2020 research grant.
  • ISF Grant for Research Workshops
    • Prof. Amihood Amir, Computer Science Department. “Research Innovations in the Field of Algorithms for their Strings”. 
  • ISF Grant for Personal Focus Medicine for 2020/21 
    • Dr. Tomer Kalisky, Faculty of Engineering. “Creating a Model for Tubulopathy Using Patient-Compatible Renal Organs for the Purpose of Customized Renal Therapy – Mitochondrial Pancreatic Syndrome as Proof of Feasibility”. 
    • Prof. Erez Levanon, Faculty of Life Sciences. “A Computational and Experimental Approach to Customized Medicine for the Diagnosis and Treatment of Rare Genetic Diseases”. 
  • ISF Grant for a Research Program Focused on Curbing the CoronaVirus (SARS-CoV-2) for 2020/21 
    • Prof. Gur Yaari, Faculty of Engineering. “Development of a System to Create a Passive Vaccine for the SARS-CoV-2 Virus, Including Future Strains and Future Epidemics”. 

We are sure there are many more notable member awards, grants and achievements that we missed. Please keep us informed with any noteworthy tidbits as we’d love to share with the rest of the community, pass on to biu management and PR and include in our periodical reports. 

Research Spotlights

  • Prof. Sharon Gannot from the Faculty of Engineering has three new interesting data science projects:

Open Positions

  • Student position – suitable for advanced Computer Science or Engineering students. Students will be paid on an hourly basis, for application development as part of a study in the department of Psychology – for details see: 
Application Development Project for a Study in the Department of Psychology
  • Prof. Sharon Gannot is looking for talented and committed PhD students and/or Post-Doctoral trainees with strong background in statistical signal processing and machine learning. Experience in audio signal processing and high programming skills will be considered as an advantage. See here for more details. 

Once again, if you have any open positions (e.g. student or research assistant positions) you’d like us to help with staffing, please let us know and we’ll be happy to assist. 

The Data Science Institute at Bar-Ilan University.
For further information or to unsubscribe from future updates – dsi@biu.ac.il

Application Development Project for a Study in the Department of Psychology

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The Dynamic Processes of Psychopathology and Psychotherapy Lab (https://dplab-biu.wixsite.com/dplab) is looking for a software programmer for a short-term project. The lab is housed in the Department of Psychology at Bar Ilan University and directed by Dr. Yogev Kivity (https://psychology.biu.ac.il/en/node/1684).

The lab is currently designing a study that will make use of Garmin Vivosmart 4 wearable device (https://buy.garmin.com/en-US/US/p/605739) to record participants’ continuous physiological arousal (heart rate) as part of a study of emotion regulation in daily life. We would like to develop an application using Garmin’s Application Programming Interface (API: https://developer.garmin.com/health-api/overview/) to extract raw data from the lab’s devices that are not accessible using the device’s existing application. The project will include getting familiar with the device and the API, understanding the lab’s needs (through interaction with the study principle investigator), creating a project description, writing the application along with appropriate documentation, training lab personnel on its use and conducting rudimentary quality assurance checks.
The project is especially suitable for advanced Computer Science or Engineering students. Students will be paid on an hourly basis at a pre-agreed rate. For inquiries and application please contact Dr. Yogev Kivity (yogev.kivity@biu.ac.il) and include your CV and a short description of your interests and relevant experience.

 

ICML Best Paper Award

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Big congratulations to Gal Chechik and Ethan Fetaya for winning the ICML best paper award! 

ICML is the top International Conference on Machine Learning   – this year 4990 papers were submitted, 1088 were accepted of which 2 were chosen for best paper! 

The first author of the work was Haggai Maron from NVIDIA research center in Israel. Work was done in collaboration with Dr. Or Litani from Stanford. 

“On Learning Sets of Symmetric Elements” is available in following link – 

https://proceedings.icml.cc/static/paper_files/icml/2020/1625-Paper.pdf

A workshop on the topic of Geometric Deep Learning will take place on Aug 2

iGDL 2020: Israeli Geometric Deep Learning Workshop

DSI 2020 Call for Research Corona Grants – List of Accepted Corona Grants

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Prof. Hanoch Senderowitz

Implementation and Application of a Deep-Docking platform for the Identification of Drug Compounds Targeting the main Cov-2 Proteins

NIS 21,000

Dr. Milana Frenkel-Morgenstern

Text mining and 3D molecular modelling to identify antiviral and anti-pneumonia drugs in order to fight COVID19 viral infection

NIS 15,000

Prof. Yoram Louzoun

Network and learning based estimates of epidemics spread in inhomogeneous populations

NIS 18,000

Dr. Simi Haber 

Dr. Baruch Barzel

COVID-19. Viral spread on temporal social networks

NIS 20,000

Prof. Reuven Cohen

Dr. Simi Haber

Efficient Quarantine in Social Networks

NIS 24,000