BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:America/Los_Angeles
BEGIN:DAYLIGHT
DTSTART:20250309T030000
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3
TZNAME:PDT
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:20251102T010000
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11
TZNAME:PST
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20251028T092801Z
UID:F5C95F1B-9339-402D-BF03-DCAEDE6D9A4A
DTSTART;TZID=America/Los_Angeles:20251023T120000
DTEND;TZID=America/Los_Angeles:20251023T130000
DESCRIPTION:Title: Brain Machine Interface: Challenges and Opportunities\n\
 nDate/Time: (PST)- 12:00pm to 1:00pm Thu\, Oct 23 2025\n\nAbstract: Brain 
 Machine interfaces have the potential to revolutionize therapy for neurolo
 gical diseases\, because they target the nervous system with high spatiote
 mporal resolution as opposed to alternative therapies. Next-generation bra
 in machine interfaces will benefit from an implantable neural recording IC
  with a dense\, high channel count recording array that can be directly ma
 tched to a micro-electrode array (MEA) at the pitch of neurons (≈30 µm)
  to effectively capture spatiotemporal patterns of neural activity at sing
 le-cell resolution. These devices must support simultaneous recording from
  multiple thousands of neurons within the form factor and power budget of 
 a fully implanted device. Hence\, there is a requirement for an architectu
 ral paradigm shift to meet the design targets. In this talk\, we will delv
 e into specific challenges and approaches to achieve intended targets.\n\n
 Speaker Bio: Dante G. Muratore received a B.Sc. and an M.Sc. degree in Ele
 ctrical Engineering from Politecnico of Turin\, Italy in 2012 and 2013\, r
 espectively. He received a Ph.D. degree in Microelectronics from the Unive
 rsity of Pavia\, Italy in 2017 in the Integrated Microsystems Lab. From 20
 15 to 2016\, he was a Visiting Scholar at Microsystems Technology labs at 
 the Massachusetts Institute of Technology\, USA. From 2016 to 2020\, he wa
 s a Postdoctoral Fellow at Stanford University\, USA. He is the recipient 
 of the Wu Tsai Neurosciences Institute Interdisciplinary Scholar Award. Si
 nce 2020\, he is an assistant professor in the Bioelectronics Section at D
 elft University of Technology\, Netherlands\, where he leads the Smart Bra
 in Interfaces group. His research focuses on hardware design for brain-mac
 hine interfaces\, bioelectronics and machine learning. https://microelectr
 onics.tudelft.nl/People/bio.php?id=690\n\n[Join WebEx meeting](https://iee
 emeetings.webex.com/ieeemeetings/j.php?MTID=m3d5beb80b9d84d4efbce27fdda8cc
 485)\nhttps://ieeemeetings.webex.com/ieeemeetings/j.php?MTID=m3d5beb80b9d8
 4d4efbce27fdda8cc485\n\nMeeting number:	2535 991 4718\n\nJoin from a video
  system or application\nDial 25359914718@ieeemeetings.webex.com\nYou can a
 lso dial 173.243.2.68 and enter your meeting number.    To dial from an IE
 EE Video Conference System: *1 2535 991 4718\n\nTap to join from a mobile 
 device (attendees only)\n[+1-415-655-0002\,\,25359914718##](tel:%2B1-415-6
 55-0002\,\,*01*25359914718%23%23*01*) United States Toll\n[1-855-282-6330\
 ,\,25359914718##](tel:1-855-282-6330\,\,*01*25359914718%23%23*01*) United 
 States Toll Free\n\nVirtual: https://events.vtools.ieee.org/m/490922
LOCATION:Virtual: https://events.vtools.ieee.org/m/490922
ORGANIZER:&quot;Gaurav Mahajan&quot; &lt;gmahajan027@gmail.com&gt;; 
SEQUENCE:19
SUMMARY:Brain Machine Interface: Challenges and Opportunities
URL;VALUE=URI:https://events.vtools.ieee.org/m/490922
X-ALT-DESC:Description: &lt;br /&gt;&lt;div&gt;&lt;strong&gt;Title&lt;/strong&gt;: Brain Machine In
 terface: Challenges and Opportunities&lt;/div&gt;\n&lt;div&gt;&amp;nbsp\;&lt;/div&gt;\n&lt;div&gt;&lt;str
 ong&gt;Date/Time:&lt;/strong&gt;&amp;nbsp\;(&lt;strong&gt;PST&lt;/strong&gt;)-&amp;nbsp\;12:00pm to 1:0
 0pm&amp;nbsp\;&lt;span id=&quot;OBJ_PREFIX_DWT1419_com_zimbra_date&quot; class=&quot;Object&quot; rol
 e=&quot;link&quot;&gt;&lt;span id=&quot;OBJ_PREFIX_DWT1427_com_zimbra_date&quot; class=&quot;Object&quot; role
 =&quot;link&quot;&gt;Thu\, Oct 23&lt;/span&gt;&lt;/span&gt;&amp;nbsp\;2025&lt;/div&gt;\n&lt;div&gt;&amp;nbsp\;&lt;/div&gt;\n&lt;
 div&gt;&lt;strong&gt;Abstract&lt;/strong&gt;: Brain Machine interfaces have the potential
  to revolutionize therapy for neurological diseases\, because they target 
 the nervous system with high spatiotemporal resolution as opposed to alter
 native therapies. Next-generation brain machine interfaces will benefit fr
 om an implantable neural recording IC with a dense\, high channel count re
 cording array that can be directly matched to a micro-electrode array (MEA
 ) at the pitch of neurons (&amp;asymp\;30 &amp;micro\;m) to effectively capture sp
 atiotemporal patterns of neural activity at single-cell resolution. These 
 devices must support simultaneous recording from multiple thousands of neu
 rons within the form factor and power budget of a fully implanted device. 
 Hence\, there is a requirement for an architectural paradigm shift to meet
  the design targets. In this talk\, we will delve into specific challenges
  and approaches to achieve intended targets.&amp;nbsp\;&amp;nbsp\;&amp;nbsp\;&lt;/div&gt;\n&lt;
 div&gt;&amp;nbsp\;&lt;/div&gt;\n&lt;div&gt;&lt;strong&gt;Speaker Bio&lt;/strong&gt;: Dante G. Muratore &amp;n
 bsp\;received a B.Sc. and an M.Sc. degree in Electrical Engineering from P
 olitecnico of Turin\, Italy in 2012 and 2013\, respectively. He received a
  Ph.D. degree in Microelectronics from the University of Pavia\, Italy in 
 2017 in the Integrated Microsystems Lab. From 2015 to 2016\, he was a Visi
 ting Scholar at Microsystems Technology labs at the Massachusetts Institut
 e of Technology\, USA. From 2016 to 2020\, he was a Postdoctoral Fellow at
  Stanford University\, USA. He is the recipient of the Wu Tsai Neuroscienc
 es Institute Interdisciplinary Scholar Award. Since 2020\, he is an assist
 ant professor in the Bioelectronics Section at Delft University of Technol
 ogy\, Netherlands\, where he leads the Smart Brain Interfaces group. His r
 esearch focuses on hardware design for brain-machine interfaces\, bioelect
 ronics and machine learning. &lt;a href=&quot;https://microelectronics.tudelft.nl/
 People/bio.php?id=690&quot;&gt;https://microelectronics.tudelft.nl/People/bio.php?
 id=690&lt;/a&gt;&lt;/div&gt;\n&lt;div&gt;\n&lt;div id=&quot;m_-5703135959777067700gmail-:1pt&quot;&gt;\n&lt;div
 &gt;&amp;nbsp\;&lt;/div&gt;\n&lt;div&gt;\n&lt;table&gt;\n&lt;tbody&gt;\n&lt;tr&gt;\n&lt;td&gt;&lt;a href=&quot;https://ieeeme
 etings.webex.com/ieeemeetings/j.php?MTID=m3d5beb80b9d84d4efbce27fdda8cc485
 &quot; target=&quot;_blank&quot; rel=&quot;noopener&quot; data-saferedirecturl=&quot;https://www.google.
 com/url?q=https://ieeemeetings.webex.com/ieeemeetings/j.php?MTID%3Dm3d5beb
 80b9d84d4efbce27fdda8cc485&amp;amp\;source=gmail&amp;amp\;ust=1760125832215000&amp;amp
 \;usg=AOvVaw1kvqBrBQiZRzYhvWLd64_i&quot;&gt;&lt;strong&gt;Join&amp;nbsp\;&lt;span class=&quot;il&quot;&gt;We
 bEx&lt;/span&gt;&amp;nbsp\;meeting&lt;/strong&gt;&lt;/a&gt;&lt;/td&gt;\n&lt;/tr&gt;\n&lt;/tbody&gt;\n&lt;/table&gt;\n&lt;br
 &gt;&lt;a href=&quot;https://ieeemeetings.webex.com/ieeemeetings/j.php?MTID=m3d5beb80
 b9d84d4efbce27fdda8cc485&quot; target=&quot;_blank&quot; rel=&quot;noopener&quot; data-saferedirect
 url=&quot;https://www.google.com/url?q=https://ieeemeetings.webex.com/ieeemeeti
 ngs/j.php?MTID%3Dm3d5beb80b9d84d4efbce27fdda8cc485&amp;amp\;source=gmail&amp;amp\;
 ust=1760125832215000&amp;amp\;usg=AOvVaw1kvqBrBQiZRzYhvWLd64_i&quot;&gt;https://ieeeme
 etings.&lt;span class=&quot;il&quot;&gt;webex&lt;/span&gt;.&lt;wbr&gt;com/ieeemeetings/j.php?MTID=&lt;wbr
 &gt;m3d5beb80b9d84d4efbce27fdda8cc&lt;wbr&gt;485&lt;/a&gt;&lt;br&gt;&lt;br&gt;\n&lt;table style=&quot;height:
  60px\; width: 25.4319%\;&quot;&gt;\n&lt;tbody&gt;\n&lt;tr&gt;\n&lt;td style=&quot;width: 47.2996%\;&quot;&gt;
 Meeting number:&lt;/td&gt;\n&lt;td style=&quot;width: 41.9102%\;&quot;&gt;2535 991 4718&lt;/td&gt;\n&lt;/
 tr&gt;\n&lt;/tbody&gt;\n&lt;/table&gt;\n&lt;br&gt;\n&lt;table&gt;\n&lt;tbody&gt;\n&lt;tr&gt;\n&lt;td&gt;&lt;strong&gt;Join fr
 om a video system or application&lt;/strong&gt;&lt;/td&gt;\n&lt;/tr&gt;\n&lt;tr&gt;\n&lt;td&gt;&lt;span dir
 =&quot;ltr&quot;&gt;Dial&lt;/span&gt;&amp;nbsp\;&lt;a dir=&quot;auto&quot;&gt;25359914718@ieeemeetings.&lt;wbr&gt;&lt;span
  class=&quot;il&quot;&gt;webex&lt;/span&gt;.com&lt;/a&gt;&lt;/td&gt;\n&lt;/tr&gt;\n&lt;tr&gt;\n&lt;td&gt;You can also dial 
 173.243.2.68 and enter your meeting number.&lt;/td&gt;\n&lt;/tr&gt;\n&lt;/tbody&gt;\n&lt;/table
 &gt;\nTo dial from an IEEE Video Conference System:&amp;nbsp\;&lt;strong&gt;*1 2535 991
  4718&lt;/strong&gt;&lt;br&gt;&lt;br&gt;\n&lt;table&gt;\n&lt;tbody&gt;\n&lt;tr&gt;\n&lt;td&gt;&lt;strong&gt;Tap to join fr
 om a mobile device (attendees only)&lt;/strong&gt;&lt;/td&gt;\n&lt;/tr&gt;\n&lt;tr&gt;\n&lt;td&gt;&lt;a hre
 f=&quot;tel:%2B1-415-655-0002\,\,*01*25359914718%23%23*01*&quot; target=&quot;_blank&quot; rel
 =&quot;noopener&quot;&gt;&lt;span dir=&quot;auto&quot;&gt;+1-415-655-0002\,\,25359914718##&lt;/span&gt;&lt;/a&gt;&amp;n
 bsp\;&lt;span dir=&quot;ltr&quot;&gt;United States Toll&lt;/span&gt;&lt;/td&gt;\n&lt;/tr&gt;\n&lt;tr&gt;\n&lt;td&gt;&lt;a h
 ref=&quot;tel:1-855-282-6330\,\,*01*25359914718%23%23*01*&quot; target=&quot;_blank&quot; rel=
 &quot;noopener&quot;&gt;&lt;span dir=&quot;auto&quot;&gt;1-855-282-6330\,\,25359914718##&lt;/span&gt;&lt;/a&gt;&amp;nbs
 p\;&lt;span dir=&quot;ltr&quot;&gt;United States Toll Free&lt;/span&gt;&lt;/td&gt;\n&lt;/tr&gt;\n&lt;/tbody&gt;\n&lt;
 /table&gt;\n&lt;/div&gt;\n&lt;/div&gt;\n&lt;/div&gt;
END:VEVENT
END:VCALENDAR

