Naftali (Tali) Tishby נפתלי תשבי                  

The Ruth and Stan Flinkman Family Chair in Brain Research                                     
The Edmond and Lily Safra Center for Brain Sciences

MOST Knowledge Center for Machine-Learning & Artificial Intelligence         
Intel Collaborative Research Institute for Computational Intelligence                    

Professor, Benin School of Engineering and Computer Science                                      
The Hebrew University ,  Jerusalem, 91904, Israel

Email: tishby@cs.huji.ac.il                       Office phone & Fax: +972-2-5494569

Office Hours: Rothberg B412. Sunday, 14:00-15:00 by appointment. 

Short Bio             CV              Publications

כתבות והרצאות לציבור הרחב:

 הרצאה על השפה והמוח

  ,וידאו של הרצאה קצרה באוניברסיטה הפתוחה

ראיון עם מרית סלבין ל"מוסף הארץ" מיולי  2007. הבהרה: הראיון ניתן בעקבות פנייה של "הארץ" לצורך סדרת כתבות על "התייחסות המדע למוות ולמושג חיי-נצח". אין זה נושא שאני עוסק בו ישירות ואין באוניברסיטה העברית מחקרים בנושא. עם זאת, הרעיונות בראיון מבוססים על הרחבות עתידיות אפשריות עקרונית של טכנולוגיות שונות המתפתחות במהירות בחקר המוח ובלמידה חישובית. Also in English  

To put things in the right proportion… The Astro picture of the day

 Machine Learning and Computational Biophysics

The interface between computer science, physics, and biology provides some of the most challenging problems in today’s science and technology. We focus on organizing computational principles that govern information processing in biology, at all levels. To this end, we employ and develop methods that stem from statistical physics, information theory and computational learning theory, to analyze biological data and develop biologically inspired algorithms that can account for the observed performance of biological systems. We hope to find simple yet powerful computational mechanisms that may characterize evolved and adaptive systems, from the molecular level to the whole computational brain and interacting populations.  An example is the Information Bottleneck method that provides a general principle for extracting relevant structure in multivariate data, characterizes complex processes, and suggests a general approach for understanding optimal adaptive biological behavior.

The Machine Learning Lab

·         Selected publications online

·         Recent talks

·         May 30, 2013 Workshop

Current students and lab members:

·         Noga Zaslavsky

·         Nadav Amir

·         Stas Tiomkin

·         Michal Moshkovich

·         Roy Fox

·         Ron Hecht (MSc 2007)

·         Hadar Aharoni Levi

Alumni students and postdocs:

·         Nori Jacoby (PhD 2014, Co-advisor: Merav Ahissar)

·         Jonathan Rubin (PhD 2013, Co-advisor: Eli Nelken)

·         Sivan Sabato (PhD 2012)

·         Asaf Gal (PhD 2012, Co-advisor: Shimon Marom)

·         Yuval Tassa (PhD 2010, Co-advisor: Emo Todorov)

·         Ohad Shamir (PhD 2010)

·         Dan Rosenbaum (MSc 2010)

·         Uri Heinemann (MSc 2009)

·         Naama Parush (PhD 2009. Co-advisor: Hagai Bergman)

·         Yevgeny Seldin (PhD 2009, MSc. 2002)

·         Roi Weiss (MSc 2007)

·         Eyal Krupka (PhD 2008)

·         Meital Rabani (MSc 2007)

·         Hani Neuvirth (Co-advisor: Gideon Schreiber)

·         Amir Navot  (PhD 2006)

·         Ran Gilad-Bachrach  (PhD 2005)

·         Amir Globerson. (PhD 2005) (Co-advisor: Eilon Vaadia)

·         Yaki Engel (PhD 2005) (Advisor: Ron Meir)

·         Shmuel Brody (MSc 2005)

·         Amit Rosner (Co-advisor: Udi Shapiro)

·         Gill Bejerano (PhD 2003. Co-advisor: Hanah Margalit)

·         Gal Chechik (PhD 2003. Co-advisor: Eli Nelken)

·         Noam Slonim (PhD 2002)

·         Elad Schneidman (PhD 2001. Co-advisor: Idan Segev)

·         Adi Schreibman (MSc 2000)

·         Shai Fine  (MSc 1996, PhD 1999)

·         Itay Gat  (MSc 1995, PhD 1999. Co-advisor: Moshe Abeles)

·         Golan Yona (PhD 1998. Co-advisors: Nati & Michal Linial)

·         Lidror Troyansky (PhD 1997)

·         Shlomo Dubnov (PhD 1996. Co-advisor: Dalia Cohen)

·         Dana Ron (PhD 1995)

·         Yoram Singer (PhD 1995)

·         Tzvika Svinik (MSc 1994)

·         Ran El-Yaniv (Post Doc 1996-98)

·         Shahar Mendelson (Post Doc 1999)

·         Jan Stiller (Post Doc 2000)

·         Michal Rosen-Zvi (IBM, PostDoc 2004-2005)

Complete Ph.D. and M.Sc. theses done in my lab.                                                          

Courses:

·         Introduction to Information Processing and Learning, 76915 (Noga Zaslavsky, Fall 2014).

·         New: Music and Brain, 76939 (Roni Granot, Naphtali Wagner, Israel Nelken, Naftali Tishby, Nori Jacoby. Fall 2009).

·         Introduction to Linear Systems, 67310 (Tal El-Hai, spring 2010).

·         Principled models of Perception-Action-Cycles 76911 (Spring 2009).

·         Machine learning seminar 67168 (2009-10).

·         Dynamical Systems and Control, 76929 (Fall 2009).  

·         Intro to Information Theory 67548 (Talya Meltzer, spring 2006)

·         Statistical and Computational Learning Theory, 67583 (Ofer Dekel, spring 2006).

·         Workshop in Neural Coding (For ICNC students – with data) 76928.

·         The learning club