IDSI 2023

Data Science at the Dead Sea

CONFERENCE PROGRAM

Sunday ,8.1.2023


08:30-11:00	Registration \| Welcome (Avni Hall)
11:00-11:20	Opening Remarks \| Paul Feigin (Avni Hall)
11:20-12:20	K1 - Keynote Speaker \| Informed and augmented learning for empowering the engineering of critical urban systems \| Prof. Francisco Chinesta, Chair: Paul Feigin (Avni Hall)
12:20-13:45	Lunch
	S1 A \| Biomedical informatics, Chair: Mark Last (Avni Hall)	S1 B \| Sound Applications, Chair: Roee Diamant (Amichai Hall)
14:00-14:20	Text Mining for Past Medical History in Electrodiagnostic Studies \| Roni Ramon-Gonen	Deep MUSIC Algorithms for Data-Driven DoA Estimation \| Nir Shlezinger
14:20-14:40	Optimizing Surgery Duration via Prediction and Causality Analysis \| Onn Shehory	A Graph-Based Clustering of Chirplet Signals Towards Monitoring of Coastal Dolphins \| Roee Diamant
14:40-15:00	Locally Sparse Neural Networks for Tabular Biomedical Data \| Ofir Lindenbaum	Single Microphone Speaker Extraction Using Unified Time-Frequency Siamese-Unet \| Sharon Gannot
15:00-15:20	Using ECG signals for hypotensive episode prediction in trauma patients \| Mark Last	Can one hear the position of nodes? \| Rami Puzis
15:20-15:40	Coffee Break \| Hotel Check In & key distribution (Avni Hall)
	S2 A , Chair: Tsvi Kuflik (Avni Hall)
15:40-16:00	Automatic Identification of Rhetorical Elements in Classical Arabic Poetry \| Tsvi Kuflik and Ali Hussein
16:00-16:20	Causal Inference Under Misspecified Interference \| Bar Weinstein
16:20-16:40	Imams, Social Media, and Pro-Regime Mobilization in Turkey \| Michael Freedman
16:40-17:00	Using a Machine Learning Approach to Promote Early Detection of Autism Risk from Infant Electronic Health Records \| Ayelet Ben-Sasson
18:00-19:00	Dinner
19:15-19:30	Reception (Amichai Hall)
19:30	Poster Session 1 (Amichai Hall)

Monday, 9.1.2023


	M1 A: NLP and Vision, Chair: Yaakov Ophir (Avni Hall)	M1 B, Chair: Kfir Levy (Amichai Hall)
09:00-09:20	Identifying Women with Post-Delivery Posttraumatic Stress Disorder using Natural Language Processing of Personal Childbirth Narratives \| Alon Bartal	Imbalanced Mixed Linear Regression \| Pini Zilber
09:20-09:40	Two new approaches to textual data augmentation \| Dan Vilenchik	Dimension reduction, the curse of continuity, and topological data analysis \| Emanuel (Menachem) Lazar
09:40-10:00	Using the Deep Learning Computer Vision Tool of CLIP to Predict High Suicide Risk from Facebook images \| Yaakov Ophir	Robust Linear Regression For General Feature Distribution \| Kfir Levy
10:00-10:15	Coffee Break
	M2 A: Computational Biology, Chair: Judith Somekh (Avni Hall)	M2 B, Chair: Dana Lahat (Amichai Hall)
10:20-10:40	BitterMatch: Recommendation Systems for Matching Molecules with Bitter Taste Receptors \| Yuli Slavutsky	A New View of Inverse Problems via Diffusion Models \| Michael Elad
10:40-11:00	G-S-M: Grouping, Scoring and Modeling Approach. Integration of Biological Domain Knowledge to Machine Learning Based Gene Expression Data Analysis for Selecting Affected Gene Sets \| Malik Yousef	Conformance Checking Over Stochastically Known Logs \| Eli Bogdanov
11:00-11:20	Unsupervised approach for detecting whole-body gene expression coordination pattern \| Judith Somekh	Interactive Explanations Of Agent Behavior \| Yotam Amitai
11:20-11:40	Using data processing methods for understanding immune germline and somatic selection \| Itai Danielli	Multimodal Data Fusion: An Overview of Methods, Challenges and Prospects \| Dana Lahat
11:50-12:50	K2 - Keynote Speaker \| Prof. Ido Dagan, Chair: Sol Efroni (Avni Hall)
12:50-13:50	Lunch + Preparing for the trip
13:50-17:00	2 options for trips near Ein Gedi
18:30-19:30	Dinner
19:30	Poster Session 2

Tuesday, 10.1.2023


08:45-09:45	Google Cloud for Research using AI/ML and Data AnalyticsE \| Niv Efron, Chen Blecher, Gavriel Mitran, Chair: Isana Veksler-Lublinsky (Avni Hall)
	T1 A, Chair: Eli Safra (Avni Hall)	T1 B, Chair: Galit Almoznino (Amichai Hall)
10:00-10:20	Thrill ride: Recommendations in Transportation Systems \| Eli Safra	Modelling COVID-19 Spread in a Complex Reality \| Hilla De-Leon
10:20-10:40	Unsupervised Acoustic Scene Mapping Based on Acoustic Measurements and Dimensionality Reduction \| Idan Cohen	Performative Prediction in a Stateful World \| Shlomi Hod
10:40-11:00		Rheumatic Monitor: A New Architecture For Screening, Monitoring And Analyzing Big Data Of Multiple Rheumatic Disease Patients: The Case Study Of Fibromyalgia \| Galit Almoznino
11:00-11:20	Coffee Break
	T2 A , Chair: Guy Gilboa (Avni Hall)	T2 B \| Computational Biology, Chair: Isana Veksler-Lublinsky (Amichai Hall)
11:20-11:40	More Than Meets the Eye - Anesthesiologists' visual attention in the operating room \| Sapir Gershov	Model-free prediction of microbiome compositions \| Amir Bashan
11:40-12:00	Dimensionality Reduction of the Dynamics of Neural Network Training \| Guy Gilboa	Canonical Correlation Analysis for Multi-Trait GWAS \| Or Zuk
12:00-12:20	FlexER: Flexible Entity Resolution for Multiple Intents \| Bar Genossar	Transfer learning improves cross-species prediction of miRNA-target interactions \| Eyal Hadad
12:20-14:00	Lunch
	T3 A, Chair: Orit Hazzan (Avni Hall)	T3 B (Amichai Hall), Chair: Nir Weinberger
14:00-14:20	A Dynamic Networks Approach to Language Development \| Elitzur Dattner	Active Probabilistic Databases \| Osnat Drien
14:20-14:40	Guide to Teaching Data Science: Pedagogical Principles and Main Topics \| Orit Hazzan	Baroque Simplicity: Simplicity Bias in Overparameterized Machine Learning \| Yakir Berchenko
14:40-15:00	Classification of point patterns using topological pair correlations \| Gil Ariel	Fast Nonlinear Vector Quantile Regression \| Aviv Rosenberg
15:00-15:20	Increasing the Adoption of Responsible AI and Data Science \| Ravit Dotan	Mean Estimation in High-Dimensional Binary Markov Gaussian Mixture Models \| Nir Weinberger
15:20-15:40	Coffee Break
	T4 A \| Causal Inference, Chair: Bella Vakulenko-Lagun (Avni Hall)	T4 B \| Data Science for Animals, Chair: Anna Zamansky and Itzik Klein (Amichai Hall)
	15:40-16:00 Identifying causal determinants of hospital outcomes from electronic health records using causal graphical learning \| Daniel Malinsky	15:40-16:15 AI for Happiness, Behavior, and Personality \| Oren Forkosh, Invited Speaker
	16:00-16:20 Negative controls for instrumental variables \| Daniel Nevo	16:15-16:30 Automated Recognition of Animal Affective States \| Marcelo Feighelstein
	16:20-16:40 The computation and use of tight symbolic nonparametric bounds \| Erin Gabriel	16:30-16:45 Computer Vision based system in Precision Livestock for automatic lamb identification and drinking activity \| Adi Alon
	16:40-17:00 Using Machine Learning and Causal Inference to Improve Patient Care and Reduce Costs in Diagnosis of Blood Cancers \| Michael Sachs	16:45-17:00 Canine Ataxic Classification Using Inertial Sensors \| Itzik Klein
17:00-17:15	Coffee Break
17:15-18:15	K3 - Keynote Speaker \| Prof. Marina Sirota, Chair: Judith Somekh (Avni Hall)
19:30-21:30	Gala dinner

Wednesday, 11.1.2023


08:30-09:00	Check out \| Coffee
09:00-10:00	K4 - Keynote Speaker \| Data Science for Society: Opportunities, Impact, and Challenges \| Prof. Nitesh Chawla, Chair: Mark Last (Avni Hall)
10:00-10:10	Penultimate Remarks \| Paul Feigin
	W1 A \| Data-science for improving health care systems, Chair: Nadav Rappaport (Avni Hall)	W1 B \| Data Science for Social Good , Chair: Yuli Slavutsky(Amichai Hall)
10:20-10:40	Treatment Prediction in the ICU SettingUsing a Partitioned Sequential Deep Time Series Analysis \| Yuval Shahar	Leveraging Data Science for Social Good: Introducing the New Program at the Hebrew University \| Yuli Slavutsky
10:40-11:00	Time-Dependent Iterative Imputation for Multivariate Longitudinal Clinical Data \| Omer Noy	Temporal Changes in Bird Migration Patterns - A Data Science for Social Good Project \| Ariel Vishne
11:00-11:20	Optimizing Operation Room Utilization—A Multi-Centers Prediction Model \| Nadav Rappoport	Data Science for Social Good – Open Discussion \| Ronit Lis Hacohen
11:20-11:40	Personalizing Digital Health Interventions with AI to Support Behavior Change \| Mor Peleg

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Contact us

hanat@trdf.technion.ac.il

+972-73378-1282

08:45-09:45	Google Cloud for Research using AI/ML and Data AnalyticsE \| Niv Efron, Chen Blecher, Gavriel Mitran, Chair: Isana Veksler-Lublinsky (Avni Hall)
	T1 A, Chair: Eli Safra (Avni Hall)	T1 B, Chair: Galit Almoznino (Amichai Hall)
10:00-10:20	Thrill ride: Recommendations in Transportation Systems \| Eli Safra	Modelling COVID-19 Spread in a Complex Reality \| Hilla De-Leon
10:20-10:40	Unsupervised Acoustic Scene Mapping Based on Acoustic Measurements and Dimensionality Reduction \| Idan Cohen	Performative Prediction in a Stateful World \| Shlomi Hod
10:40-11:00		Rheumatic Monitor: A New Architecture For Screening, Monitoring And Analyzing Big Data Of Multiple Rheumatic Disease Patients: The Case Study Of Fibromyalgia \| Galit Almoznino
11:00-11:20	Coffee Break
	T2 A , Chair: Guy Gilboa (Avni Hall)	T2 B \| Computational Biology, Chair: Isana Veksler-Lublinsky (Amichai Hall)
11:20-11:40	More Than Meets the Eye - Anesthesiologists' visual attention in the operating room \| Sapir Gershov	Model-free prediction of microbiome compositions \| Amir Bashan
11:40-12:00	Dimensionality Reduction of the Dynamics of Neural Network Training \| Guy Gilboa	Canonical Correlation Analysis for Multi-Trait GWAS \| Or Zuk
12:00-12:20	FlexER: Flexible Entity Resolution for Multiple Intents \| Bar Genossar	Transfer learning improves cross-species prediction of miRNA-target interactions \| Eyal Hadad
12:20-14:00	Lunch
	T3 A, Chair: Orit Hazzan (Avni Hall)	T3 B (Amichai Hall), Chair: Nir Weinberger
14:00-14:20	A Dynamic Networks Approach to Language Development \| Elitzur Dattner	Active Probabilistic Databases \| Osnat Drien
14:20-14:40	Guide to Teaching Data Science: Pedagogical Principles and Main Topics \| Orit Hazzan	Baroque Simplicity: Simplicity Bias in Overparameterized Machine Learning \| Yakir Berchenko
14:40-15:00	Classification of point patterns using topological pair correlations \| Gil Ariel	Fast Nonlinear Vector Quantile Regression \| Aviv Rosenberg
15:00-15:20	Increasing the Adoption of Responsible AI and Data Science \| Ravit Dotan	Mean Estimation in High-Dimensional Binary Markov Gaussian Mixture Models \| Nir Weinberger
15:20-15:40	Coffee Break
	T4 A \| Causal Inference, Chair: Bella Vakulenko-Lagun (Avni Hall)	T4 B \| Data Science for Animals, Chair: Anna Zamansky and Itzik Klein (Amichai Hall)
	15:40-16:00 Identifying causal determinants of hospital outcomes from electronic health records using causal graphical learning \| Daniel Malinsky	15:40-16:15 AI for Happiness, Behavior, and Personality \| Oren Forkosh, Invited Speaker
	16:00-16:20 Negative controls for instrumental variables \| Daniel Nevo	16:15-16:30 Automated Recognition of Animal Affective States \| Marcelo Feighelstein
	16:20-16:40 The computation and use of tight symbolic nonparametric bounds \| Erin Gabriel	16:30-16:45 Computer Vision based system in Precision Livestock for automatic lamb identification and drinking activity \| Adi Alon
	16:40-17:00 Using Machine Learning and Causal Inference to Improve Patient Care and Reduce Costs in Diagnosis of Blood Cancers \| Michael Sachs	16:45-17:00 Canine Ataxic Classification Using Inertial Sensors \| Itzik Klein
17:00-17:15	Coffee Break
17:15-18:15	K3 - Keynote Speaker \| Prof. Marina Sirota, Chair: Judith Somekh (Avni Hall)
19:30-21:30	Gala dinner

08:30-09:00	Check out \| Coffee
09:00-10:00	K4 - Keynote Speaker \| Data Science for Society: Opportunities, Impact, and Challenges \| Prof. Nitesh Chawla, Chair: Mark Last (Avni Hall)
10:00-10:10	Penultimate Remarks \| Paul Feigin
	W1 A \| Data-science for improving health care systems, Chair: Nadav Rappaport (Avni Hall)	W1 B \| Data Science for Social Good , Chair: Yuli Slavutsky(Amichai Hall)
10:20-10:40	Treatment Prediction in the ICU SettingUsing a Partitioned Sequential Deep Time Series Analysis \| Yuval Shahar	Leveraging Data Science for Social Good: Introducing the New Program at the Hebrew University \| Yuli Slavutsky
10:40-11:00	Time-Dependent Iterative Imputation for Multivariate Longitudinal Clinical Data \| Omer Noy	Temporal Changes in Bird Migration Patterns - A Data Science for Social Good Project \| Ariel Vishne
11:00-11:20	Optimizing Operation Room Utilization—A Multi-Centers Prediction Model \| Nadav Rappoport	Data Science for Social Good – Open Discussion \| Ronit Lis Hacohen
11:20-11:40	Personalizing Digital Health Interventions with AI to Support Behavior Change \| Mor Peleg