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Children’s Hospital
Boston, Harvard Medical School |
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Program in Biophysics, Program in Neuroscience at Harvard |
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Center for Brain Science, Harvard University |
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Center for Minds, Brains and Machines |
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617-919-2530 |
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Boston, MA 02115 |
Education
1991-1996 B.Sc. University of Buenos Aires. Physical Chemistry
(Argentine Chemistry Association
summa cum laude)
1998-2002 M.Sc. California Institute of Technology. Computation
and Neural Systems. Advisor = Professor Christof Koch
1996-2002 Ph.D. California Institute of Technology. Biology Division.
Advisor = Professor Christof Koch
(Caltech best Ph.D. Award and
Caltech best biology Ph.D. Award)
2002-2006 Whiteman Science Fellow and McGovern Institute Fellow. Massachusetts Institute of
Technology. Dept. of Brain
and Cognitive Science and Computation and Systems Biology Initiative.
Advisor = Professor Tomaso Poggio.
1984 Metropolitan Chess Champion. Buenos
Aires. Argentina. (category < 15 yrs old)
1990 Sub-champion. National
Math Olympiads. Argentina. (high school)
1994 Outstanding Youth Award. Buenos Aires Stock Exchange Foundation.
1995 A.
Luna Honor Award. Dow Chemical Company.
1997 Argentine Chemistry Association,
Best B.Sc. in Physical Chemistry.
2000 Everhart Distinguished Graduate
Student Lecture Award. Caltech.
2002 Lawrence L. and Audrey W.
Ferguzon Prize, Caltech. Best Biology Ph.D. Thesis.
2002 Milton and Francis Clauser
Doctoral Prize, Caltech. Best Ph.D. Thesis.
2003 MIT
Dean of Science Whiteman Fellowship
2007 Children’s
Hospital Boston Career Development Award
2008 Klingenstein
Fund Award
2008 Whitehall
Foundation Award
2009 NIH
New Innovator Award
2010 NSF
Career Award
2010 Career
Development Award, Society for Neuroscience
2015 Pisart Award for Vision Research
2017 McKnight
Award for Neuroscience
Books
·
Kreiman G. Biological and Computer
Vision. Cambridge University Press, To Appear.
·
Fried I, Rutishauser
U, Cerf M and Kreiman G, eds. Single neuron studies of
the human brain. MIT Press. 2014.
·
Kriegeskorte N and Kreiman
G, eds. Understanding visual population codes. MIT
Press. 2011.
Peer-reviewed
primary publications
·
Ponce C.R., Xiao W., Schade P.F., Hartmann T.S., Kreiman G., Livingstone M.
(2019). Evolving Images for Visual Neurons Using a Deep Generative Network
Reveals Coding Principles and Neuronal Preferences. Cell, 177:999-1009.
·
Kreiman G and Serre
T. The role of feedback in vision (Submitted to This Year in Cognitive
Neuroscience)
·
Kreiman G (2019). What do neurons
really want? The role of semantics in cortical representations. In Psychology
of Learning and Motivation, Volume 70. Chapter 8.
·
Vinken
K, Boix X, Kreiman G (2019). Incorporating adaptation
in object recognition models captures temporal dynamics in neurophysiology and
perception. bioRxiv 642777
·
Xiao W. and Kreiman G. (2019).
Gradient-free activation maximization for identifying effective stimuli. arXiv
1905.00378
·
Madhavan R, Bansal AK, Madsen JR, Golby
AJ, Tierney TS, Eskandar EN, Anderson WS, Kreiman G
(2018). Neural interactions underlying visuomotor associations in the human
brain. Cerebral Cortex,
·
Misra
P, Marconi A, Kreiman G. (2018) Minimal memory for details in real life events.
Scientific Reports, 8, 16701.
·
Tang H, Schrimpf
M, Lotter W, Moerman C, Paredes
A, Ortega Caro J, Hardesty W, Cox D, Kreiman G. (2018) Recurrent computations
for visual completion. PNAS,
115:8835-884.
·
Zhang M, Feng
J, Ma KT, Lim JH, Zhao Q, Kreiman G. (2018) Finding any Waldo: zero-shot
invariant and efficient visual search. Nature
Communications, 9:3730.
·
Lotter W, Kreiman G, Cox D. (2018) A
neural network trained to predict future video frames mimics critical
properties of biological neuronal responses and perception. arXiv:1805.10734
·
Zhang M, Feng
J, Lim JH, Zhao Q, Kreiman G. (2018) What am I searching for? arXiv
1807.11926
·
Palepu
A, Premananthan CS, Azhar
F, Vendrame M, Loddenkemper
T, Reinsberger C, Kreiman G, Parkerson K, Sarma VS, Anderson
WS (2018). Development of automated interictal spike detector. IEEE Engineering in Medicine and Biology
Society.
·
Wu K, Wu E, Kreiman G (2018). Learning
scene gist with convolutional neural networks to improve object recognition. IEEE Information Sciences and Systems.
·
Isik I, Singer J, Madsen JR, Kanwisher
N, Kreiman G (2017). What is changing when: Decoding visual information
in movies from human intracranial recordings. Neuroimage, 180:147-159.
·
Lotter, W, Kreiman, G, Cox, D.
(2017) Deep Predictive Coding Networks for Video PredLotter
W, Kreiman G, Cox D. Deep Predictive Coding Networks for Video
Prediction and Unsupervised Learning. ICLR Conference Proceedings 2017.
·
Gomez-Laberge C, Smolyanskaya
S, Nassi JJ, Kreiman G, Born R (2016). Bottom-up and Top-down Input
Augment the Variability of Cortical Neurons. Neuron, 91:540-547.
·
Kreiman G.
(2016). A null model for cortical representations with grandmothers galore. Language, Cognition and Neuroscience, 32,
274-285.
·
Tang H, Singer J, Ison M, Pivazyan G, Romaine M, Frias R, Meller E, Boulin A, Carroll
J Perron V, Dowcett S,
Arellano M, Kreiman G (2016). Predicting episodic memory formation for
movie events. Scientific Reports, 6:30175.
·
Lotter W, Kreiman G, Cox D. Unsupervised
Learning of Visual Structure using Predictive Generative Networks. International
Conference on Learning Representations, ICLR Conference Proceedings 2016.
·
Tang S, Hemberg M, Cansizoglu
E, Belin S, Kosik K, Kreiman G, Steen H, Steen
J. (2016) f-divergence Cutoff Index to Simultaneously Identify Differential
Expression in the Integrated Transcriptome and Proteome. Nucleic Acids Research. 44:e97.
·
Tang H, Yu H, Chou C, Crone N, Masen J,
Anderson W, Kreiman G (2016) Cascade of neural processing orchestrates
cognitive control in human frontal cortex. eLife
e123532.
·
Miconi T., Groomes L. & Kreiman
G (2016). There's Waldo! A Normalization Model of Visual Search Predicts
Single-Trial Human Fixations in an Object Search Task. Cerebral Cortex, 26:3064-82
·
Madhavan R, Millman D, Tang H, Crone
NE, Lenz FA, Tierney TS, Madsen JR, Kreiman G, Anderson WS. (2015). Decrease
in gamma-band activity tracks sequence learning. Front Syst
Neurosci. 8:222.
·
Singer JM, Madsen JR, Anderson WS, Kreiman
G. (2015). Sensitivity to timing and order in human visual cortex. Journal
of Neurophysiology 113:1656-69.
·
Prabakaran S, Hemberg M, Chauhan R,
Winter D, Tweedie-Cullen RY, Dittrich C, Hong E, Gunawardena J, Steen H, Kreiman
G, Steen JA. (2014). Quantitative profiling of peptides from RNAs
classified as noncoding. Nature Communications. 18;5:5429.
·
Singer JM, Kreiman G. (2014). Short
temporal asynchrony disrupts visual object recognition. Journal of Vision 14:7.
·
Tang H, Buia C, Madhavan R, Crone NE,
Madsen JR, Anderson WS, Kreiman G. (2014) Spatiotemporal dynamics
underlying object completion in human ventral visual cortex. Neuron, 6:736-748.
·
Bansal A, Madhavan R,
Agam Y, Golby A, Madsen J and Kreiman G. Neural dynamics underlying
target detection in thehuman brain. Journal
of Neuroscience, 2014, 34:3042-3055
·
Nassi J, Gomez-Laberge C, Kreiman G,
Born R. Corticocortical feedback increases the spatial extent of normalization.
Frontiers
in Systems Neuroscience, 2014, 8:105.
·
Singer JM, Kreiman G. Short
temporal asynchrony disrupts visual object recognition. Journal of Vision, 2014, 12:14
·
Murugan R and Kreiman
G. Theory on the coupled stochastic dynamics of transcription and
splice-site recognition. PLoS Computational Biology, 2012. 8:1-13.
·
Bansal, A, Singer J,
Anderon WS, Golby, A, Madsen JR, Kreiman G. Temporal stability of
visually selective responses in intracranial field potentials recorded from
human occipital and temporal lobes. Journal of Neurophysiology, 2012. 108:3073-3086.
·
Hemberg M, Gray JM,
Cloonan N, Kuersten S, Grimmond S, Greenberg ME, Kreiman
G (2012). Integrated genome analysis suggests that most conserved
non-coding sequences are regulatory factor binding sites.
Nucleic Acids Research, 2012. 40:7858-7869.
·
Burbank K and Kreiman
G. Depression-biased reverse plasticity rule is required for stable
learning at top-down connections. PLOS
Computational Biology, 2012. 8:1-16.
·
Fried I, Mukamel R, Kreiman
G. Internally generated preactivation of single neurons in human medial
frontal cortex predicts volition. Neuron, 2011. 69: 548-562.
·
Kreiman G and Maunsell J. Nine criteria for a measure of scientific output. Frontiers in Computational Neuroscience,
2011. 5:48.
·
Murugan R and Kreiman
G. On the minimization of fluctuations in the response times of autoregulatory
gene networks. Biophysical Journal, 2011.
101: 1297-1306.
·
Hemberg M and Kreiman
G. Conservation of transcription factor binding events predicts
gene expression across species. Nucleic Acids Research, 2011. 39:7092-7102.
·
Agam Y, Liu H,
Pappanastassiou A, Buia C, Golby AJ, Madsen JR, Kreiman G. Robust
selectivity to two-object images in human visual cortex. Current Biology, 2010. 20:872-879.
·
Kim TK*, Hemberg M*,
Gray JM*, Costa A, Bear DM, Wu J, Harmin DA, Laptewicz, M, Barbara-Haley K,
Kuersten S, Markenscoff-Papadimitriou E, Kuhl D, Bito H, Worley PF, Kreiman
G, Greenberg ME. Widespread transcription at thousands of enhancers during
activity-dependent gene expression in neurons. (* = equal
contribution) Nature, 2010. 465:182-187.
·
Rasch M, Logothetis
NK, Kreiman G, From neurons to circuits: linear estimation of
local field potentials.
Journal
of Neuroscience, 2009. 29:13785-13796
·
Horng S, Kreiman G,
Ellsworth C, Page D, Blank M, Millen K, Sur M. Differential Gene Expression in the Developing Lateral Geniculate
Nucleus and Medial Geniculate Nucleus Reveals Novel Roles for Zic4 and
Foxp2 in Visual and Auditory Pathway Development. Journal
of Neuroscience, 2009. 29:13672-13683
·
Liu
H, Agam Y, Madsen JR, Kreiman G. Timing, timing, timing: Fast decoding
of object information from intracranial field potentials in human visual
cortex. Neuron (2009) 62:281-290
·
Meyers
E, Freedman D, Kreiman G, Miller E, Poggio T. Dynamic Population Coding
of Category Information in ITC and PFC. Journal of Neurophysiology, (2008) 100: 1407-1419
·
Leamey
C., Glendining K., Kreiman G., Kang N., Kuan H., Fassler R., Sawatari
A., Tonegawa S., and Sur M. Differential Gene Expression between Sensory
Neocortical Areas: Potential Roles for Ten_m3 and Bcl6 in Patterning Visual and
Somatosensory Pathways. Cerebral
Cortex (2008), 18:53-66
·
Tropea
D, Kreiman G, Lyckman AW, Mukherjee S, Yu H, Horng S, Sur, M. Distinct
gene systems mediating activity-dependent plasticity in visual cortex. Nature
Neuroscience (2006) 9:660-668
·
Kreiman G*,
Hung C*, Kraskov A, Quiroga R, Poggio T, DiCarlo J. Object selectivity by local
field potentials in the macaque inferior temporal cortex. Neuron (2006) 49:433-445
(*=equal contribution)
·
Hung
C*, Kreiman G*, Poggio T, DiCarlo J. Fast read-out of object identity
from macaque inferior temporal cortex. Science (2005), 310:863-866. (*=equal contribution)
·
Quian-Quiroga R, Reddy L, Kreiman G,
Koch C, Fried I. Invariant visual representation by single neurons in the human
brain. Nature (2005), 435:1102-1107
·
Kreiman
G. Identification of sparsely distributed
clusters of cis-regulatory elements in sets of co-expressed genes. Nucleic Acids Research
(2004), 32:2889-2900
·
Su AI, Wiltshire T, Batalov S, Lapp H,
Ching KA, Block D, Zhang J, Soden R, Hayakawa M, Kreiman G, Cooke MP, Walker JR and Hogenesch JB. A gene atlas
of the mouse and human protein-encoding transcriptomes. PNAS (2004), 101:6062-6067
·
Yeo
G., Holste D., Kreiman G. and Burge C. Variation in alternative splicing
across human tissues. Genome Biology
(2004), 5:R74
·
Kreiman
G, Fried I, Koch C. Single neuron responses in the human
brain during flash suppression PNAS
(2002), 99:8378-8383
·
Krahe R., Kreiman G., Gabbiani F., Koch C. and Metzner W.
Stimulus encoding and feature extraction by multiple pyramidal cells in the
hindbrain of weakly electric fish. J.
Neuroscience (2002), 22:2374-2382
·
Zirlinger M., Kreiman G. and Anderson D.
Amygdala-enriched genes identified by microarray technology are restricted to
specific amygdaloid sub-nuclei. PNAS
(2001), 98:5270-5275
·
Kreiman
G., Koch C. and Fried I. Imagery neurons
in the human brain. Nature
(2000), 408:357-361.
·
Kreiman
G., Krahe R., Metzner W., Koch C. and
Gabbiani F. Robustness and variability of neuronal coding by amplitude
sensitive afferents in the weakly electric fish Eigenmannia. J. Neurophysiology (2000),
84:189-204
·
Kreiman
G., Koch C. and Fried I.
Category-specific visual responses of single neurons in the human medial
temporal lobe. Nat. Neurosci.
(2000), 3:946-953
·
Ouyang Y., Rosenstein A., Kreiman G., Schuman E. M. and
Kennedy M. B. Tetanic stimulation leads to increased accumulation of CaMKII via dendritic protein synthesis in hippocampal
neurons. Journal of Neuroscience
(1999), 19:7823-7833.
·
Inon de Iannino N., Briones G., Kreiman G. and Ugalde R.
Characterization of the biosynthesis of b(1-2) cyclic
glucan in R. Freddii. Cell. Mol..
Biol. (1996), 42:617-629
Reviews
·
Blumberg J. and
Kreiman, G. (2010). How cortical neurons help us see: visual recognition in the
human brain. Journal of Clinical Investigation 120:3054-3063.
·
Quian Quiroga R, Kreiman G
(2010). Measuring sparseness in the brain. Psych. Reviews, 17:291-297
·
Quian Quiroga R, Kreiman G, Koch
C, Fried I. (2008). Sparse but not 'Grandmother-cell' coding in the medial
temporal lobe. Trends in Cognitive Science 12, 87-91
·
Kreiman G.
Single neuron approaches to human vision and memory. Current Opinion in Neurobiology (2007), 17:471-475
·
Serre T, Kreiman G, Kouh M,
Cadieu C, Knoblich U, Poggio T, A quantitative theory of immediate visual
recognition. Progress In Brain
Research (2007) 165C: 33-56.
·
Rees G., Kreiman G. and Koch C. Neural correlates
of consciousness in humans. Nature
Reviews Neuroscience (2002), 3:261-270
·
Crick F, Koch C, Kreiman G, Fried I. Consciousness
and neurosurgery. Neurosurgery
(2004), 55:273-282
·
Kreiman G. Neural coding: computational and biophysical
perspectives. Physics of Life Reviews
(2004), 2:71-102.
Book chapters
o
Tang H, Kreiman G. (2017). Recognition
of occluded objects. In Computational and Cognitive Neuroscience of Vision. (ed Zhao, Q). Singapore:
Springer-Verlag.
o
Rutishauser U., Cerf M. & Kreiman
G. Data analysis techniques for human microwire recordings: spike detection and
sorting, decoding, relation between units and local field potentials. In Single
neuron studies of the human brain. Probing cognition. (eds I Fried, U Rutishauser, M Cerf, & G Kreiman) Ch 6, (MIT Press, 2014).
o
Mormann F, Ison M, Quiroga RQ, Koch C,
Fried I, Kreiman G. Visual cognitive adventures of single neurons in the human
medial temporal lobe. In Single neuron studies of the human brain. Probing
cognition. (eds I Fried, U
Rutishauser, M Cerf, & G Kreiman) Ch. 8, (MIT Press, 2014).
o
Kreiman G., Rutishauser U, Cerf M.
& Fried I. The next ten years and beyond. In Single neuron studies of the
human brain. Probing cognition. (eds
I Fried, U Rutishauser, M Cerf, & G Kreiman) Ch. 19, (MIT Press, 2014).
o
Kreiman G. Neural correlates of
consciousness: perception and volition. In Cognitive Neuroscience Vol. V (ed M Gazzaniga) (MIT Press, In Press).
o
Kreiman G. Computational Models of
Visual Object Recognition. In Principles of neural coding (eds
S Panzeri & R Quiroga) (CRC Press, 2013).
o
Burbank K, Kreiman G. Introduction to
the Anatomy and Function of Visual Cortex (Chapter 17). In Kriegeskorte N and
Kreiman G, eds. Understanding visual population codes.
MIT Press. 2011
o
Singer J, Kreiman G. Introduction to
Statistical Learning and Pattern Classification (Chapter 18). In Kriegeskorte N
and Kreiman G, eds. Understanding visual population
codes. MIT Press. 2011
o
Meyers E, Kreiman G. Tutorial on
Pattern Classification in Cell Recording (Chapter 19). In Kriegeskorte N and
Kreiman G, eds. Understanding visual population codes.
MIT Press. 2011
·
Kreiman G. Models of visual recognition. (Chapter
29) In “Principles of neural coding’, edited by Quiroga and Panzeri. CRC Press,
2013.
·
Kreiman G,
Fried I, Koch C. (2005) Responses of single neurons in the human brain during
flash suppression. Ch.12, “Binocular Rivalry”, edited by Alais/Blake, MIT
Press. [Book chapter]
·
Kreiman G. Single cell studies, human.
In Encyclopedia of Consciousness, P. Wilken, ed. (Oxford, Oxford University
Press). 2010
Other
·
Kreiman G.
(2019) It's a small dimensional world after all.
Comment on The unreasonable effectiveness fo small
neural ensembles in high-dimensional brains" by Gorban
et al. Physics of Life Reviews.
·
Kreiman G
(2013). Mind the quantum? Trends in Cognitive Science,
17(3): 109
·
Kreiman G. Literary
inspiration. Nature, 2011. 475:453-454.
[Comment]
·
Tang H, Kreiman
G. Face Recognition: Vision and Emotions beyond the Bubble. Current Biology, 2011. 21:R888-890 [Comment]
·
Anderson WS
and Kreiman G. (2011). Neuroscience: What We Cannot Model, We Do Not
Understand. Current Biology. 21:
R124-R125. [Comment]
·
Anderson WS, Kreiman G.
What we cannot model, we cannot understand. Current Biology, 2011. 21:R124-R125.
[Comment]
·
Singer J, Kreiman G, Toward unmasking the dynamics of visual
perception. Neuron, 2009. 64:446-447. [Comment]
·
Tsuchiya N, Kreiman
G. (2008). Psyche, attention and consciousness. Psyche 14, 1-2. [Editorial]
·
Kreiman, G.
(2008). Biological object recognition. Scholarpedia 3, 2667. [Peer-reviewed Web entry]
·
Kreiman G,
(2007) Neuroscience: from the very large to the very small. Current Biology, 17:R768-R770
[Comment]
·
Serre, Kouh, Cadieu, Knoblich, Kreiman, Poggio. (2005)
A theory of object recognition MIT AI
Memo 2005-036. [Technical Report]
·
Kreiman G. (2001). Moveo ergo sum. BioEssays 23:662. [Comment]
·
Kreiman G.
(2001). On the neuronal activity in the human brain during visual recognition,
imagery and binocular rivalry. California Institute of Technology. (Ph.D.
Thesis) [Thesis]
·
Kreiman G.
(2001). Neural coding and feature extraction of time-varying signals.
California Institute of Technology. (M.Sc. Thesis) [Thesis]
Selected Invited
talks
Limitations of Machine Learning. Sestri Levante, Italy. 2019.
ECVP, Belgium. 2019.
AI and the brain. Beijing, 2019.
AI and Neuroscience. KAIST, South Korea.
2019.
Cosyne conference workshop. Cascais, Portugal. 2019
BrainMind Summit, Cambridge, MA. 2019.
Google-X Symposium on Brains and Computation. Mountain
View, CA. 2018
University of Pennsylvania, Computational
Neuroscience Initiative. Philadelphia, PA. 2018
IEEE Conference on Information Science and Systems.
Princeton, NJ. 2018
Cognitive Neuroscience Annual Meeting. Boston, MA.
2018
Vision Sciences Society Annual Meeting. St Pete Beach, FL.
2018
ModVis Workshop. St Pete Beach, FL. 2018
University of Washington, Seattle, WA. 2018
Neurophyilosophy of Free Will Conference. Orange, CA. 2018
Global Pediatrics Leadership Program. 2018
Invited talk. Advanced Methods in
Theoretical Neuroscience. Goettingen, Germany.
2018
Invited talk. Sigtuna Foundation. Stockholm, Sweden. 2017
Invited talk. International Research Center for Neurointelligence. International Symposium. Tokyo, Japan.
2017.
Google-X Symposium on Brains and Computation. Mountain
View, CA. 2018
University of Pennsylvania, Computational
Neuroscience Initiative. Philadelphia, PA. 2018
IEEE Conference on Information Science and Systems.
Princeton, NJ. 2018
Cognitive Neuroscience Annual Meeting. Boston, MA.
2018
Vision Sciences Society Annual Meeting. Boston, MA. 2018
Invited keynote talk. AAAI, The science of
intelligence. Stanford, CA. 2017
Computer Vision and Pattern Recognition. Hawaii, HI. 2017
Caltech Computation and Neural Systems Program. Pasadena, CA.
2017
Biology of Brain Disorders International Workshop. Dublin,
Ireland, 2016.
Brains, Minds and Machines International Workshop. Sestri
Levante, Italy, 2016.
Society of Industrial and Applied Mathematics. Recent Advances for Image Classification and Recognition. Albuquerque, 2016.
IEEE Conference on Information Sciences and Systems,
Princeton 2016.
Cosyne Workshop. Snowbird, Utah, 2016.
NIPS Symposium. Montreal 2015.
Shilac conference. Puerto
Rico 2015.
Science Foo. June 2015.
Renaissance Weekend. June 2015.
Klingenstein Foundation. May 2015.
University of Buenos Aires. April
2015.
Singapore A*Star. March
2015.
University of Vanderbilt. March
2015.
Cosyne Workshop, February 2015.
NIH High-Risk High Reward Symposium. November
2014.
Columbia University. November 2014.
Johns Hopkins University. October 2014.
Areadne Computational Neuroscience
Conference, June 2014.
Johns Hopkins University, February 2014
Caltech, Computation and Neural Systems. Feb 2013.
British Neuroscience Association, London, Apr 2013.
Cognitive Neuroscience, Lake Tahoe, Jul 2013
Bernstein Center for Computational Neuroscience, Germany
2012.
Mini-symposium. Society for Neuroscience,
2012.
MIT Intelligence Initiative. August
2012.
Portuguese Society of Neurology Annual Meeting. Portugal
2012.
University of Chicago. Chicago.
2012.
Brown University. Providence. 2012.
Baylor College of Medicine. Houston, 2011.
NSF/NIH CRCNS Annual Meeting. Princeton 2011.
NIH New Innovator Award Annual Symposium. Washington
2011.
Universita di Trento, Center for Brain/Mind Sciences. Roveretto, Italy. 2011
Satellite Symposium, ASSC Annual Meeting. Kyoto,
Japan. 2011.
RIKEN Institute. Tokyo, Japan. 2011.
NIPS Institute. Okasaka, Japan. 2011.
University of Pennsylvania.
Philadelphia. 2011.
University of Leuven, Leuven, Belgium. 2010.
MEEI Annual Meeting, Boston, US. 2010.
International Conference on Cognitive Neuroscience,
Beijing, China. 2010.
Computation and Systems Neuroscience conference. Local field potentials workshop. Salt Lake City, US. 2010.
University of Birmingham.
Birmingham, UK. 2010.
SFN mini-symposium. Chicago, US. 2009.
ECVP symposium, Regensburg, Germany. 2009.
International Neuropsychology Society, Dubrovnik,
Croatia. 2009.
Chinese National Academy of Science, Beijing, China. 2008.
Institute of Neuroscience and Brain Research Center,
National Yang Ming University, Taipei, Taiwan. 2008.
MEEI Annual Meeting, Boston, US. 2008.
Cosyne 2008, Decoding Information Workshop, Salt Lake
City, US. 2008.
Harvard Vision Lab, Cambridge, US. 2007.
Imperial College London, London, UK. 2007.
University of Leicester, Leicester, UK, 2007.
University of Trento, Roveretto, Italy.
2007.
Workshop “A Journey through computation”, Genova,
Italy, June 2007.
Visual Sciences Society, Workshop on decoding brain
activity. Sarasota, US. 2007.
Janelia Farm, Virginia, US. 2007.
Dana Foundation Conference, Los Angeles, US. 2007.
Center for Cognitive Science, Duke University,
Durham, US. 2006.
Department of Bioengineering, Duke University, Durham, US. 2006.
Department of Computer Science, Columbia University,
New York, US. 2006.
Department of Bioengineering, Columbia University, New York,
US. 2006.
Stanford, Department of Bioengineering, Palo Alto, US 2006.
Children’s Hospital Boston, Boston, US. 2006.
Center for Brain Science, Boston, Harvard University,
Boston, US. 2006.
Memorial Sloan Kettering, New York, US. 2005.
Stanford, Department of Computer Science, US. 2005.
Institute for Neuroinformatics, Zurich, Switzerland. 2005.
Salk Institute, San Diego, US. 2004.
Harvard Vision Seminar, Cambridge, US. 2004.
Caltech CNSE Special Symposium, Pasadena, US. 2004
New paradigms in Computational Neuroscience, Cordoba,
Argentina. US. 2004.
Computational Systems Biology Symposium 2004. Cambridge,
US. 2004.
Methods in Comp. Neuroscience,
Marine Biological Laboratory, Woods Hole, US 2003.
Hamburg University, Germany. 2003.
Gottingen Neurobiology Conference, Germany. 2003.
ASSC Annual Meeting, Memphis. 2003.
AAAS Meeting, Denver. 2003.
UC Irvine, Irvine, US. 2002.
Caltech. Everhart Distinguished Graduate
Student Lecture. Pasadena, US. 2000.
Ad hoc reviewer for
the following journals
Acta Astronomica, Cerebral Cortex, Cognitive Computation, Genome
Biology, Journal of Anatomy, Journal of Computational Neuroscience, Biotechniques, Journal of Cognitive Neuroscience,
Experimental Brain Research, Nature Neuroscience, Journal of Comparative
Physiology A, RECOMB, Neurocomputation,
Bioinformatics, Nucleic Acids Research, PLoS Computational Biology,
Neuroscience, Journal of Neurochemistry, Journal of Neuroscience, PNAS, HFSP
Journal, Computational Neuroscience Annual Meeting, Neural Networks, Nature, Nature
Methods, Brain, Journal of Neuroscience Methods, Journal of Neurophysiology,
Computational Intelligence and Neuroscience, Scholarpedia, IEEE Journal of
Selected Topics in Signal Processing, IEEE transactions in Computational
Biology and Bioinformatics, Comparative Biochemistry and Physiology, PLoS
Biology, Neural Computation, Current Biology, Journal of Neural Engineering,
Nature Protocols, ISMB, Neuroimage, BMC Bioinformatics, Trends in Neuroscience,
IEEE Spectrum, Neuron, Frontiers in Perception Science / Computational
Neuroscience, Trends in Cognitive Science.
Grant Review Panels
National
Science Foundation (NSF, Robust Intelligence Panel, Collaborative Research in
Computational Neuroscience Panel, Cognitive Neuroscience Panel); NIH (SPC, LAM,
ZRG1 Study Sections), King Trust, World Class University (Korea), Rappaport
Institution, Technion (Israel); Engineering and Physical Sciences Research
Council (EPSRC, UK); Agence Nationale
de la Reserche (ANR, France); Kolumb
program (Poland), US-Israel Binational Science Foundation, FWO (Belgium), NWO
(Netherlands).
Patent Review
Patent evaluation for US Patent
and Trademark Office
2018-2019 Harvard. Biological and
Artificial Intelligence.
2014-2019 MBL, Woods. Brains,
Minds and Machines Summer Course.
2007-2019 Harvard. HMS 130/230. Visual Object
Recognition
2010-2016 Harvard Biophysics 300 (Hogle)
2009-2012 Harvard HMS204. Neurophysiology
of Central Circuits. (Wilson, Born)
2008-2012 Harvard. MCB145 (Uchida)
2004-2005
MIT IAP class: The quest for
consciousness
2003 MIT
7.3444 Genomics and bioinformatics of transcription (with U.Ohler)
1998-1999 Caltech CNS/Bi 163
20090297573 Identifying and
Modulating Molecular Pathways that Mediate Nervous System Plasticity (with
Mriganka Sur and Daniela Tropea)
Postdocs: Yigal Agam
(now Instructor MGH), Hesheng Liu (now Assistant
Professor, MGH), Rajamanickam Murugan
(now Professor IIT Madras), Calin Buia (now, McKinsey
Consulting), Kendra Burbank (now, Instructor, University of Chicago), Martin
Hemberg (now Professor, Sanger Institute, Cambridge UK), Jed Singer (now Data
Scientist, Infinite Analytics), William Anderson (now, Associate Professor,
Johns Hopkins School of Medicine), Thomas Miconi (now Research Leader, The
Neuroscience Institute), Arjun Bansal (now co-founder Nervana Systems, now
Intel), Radhika Madhavan (now Research leader, GE), Camille Gomez-Laberge (now Instructor,
Harvard Physics), Leyla Isik (now Assistant Professor, Johns Hopkins
University), Daniel Weisholtz (current), Frederico
Azevedo (current), Xavier Boix (current), Carlos
Ponce (now Assistant Professor, Washington University), Kasper Vinken (current), Nimrod Shaham
(current), Mengmi Zhang (current)
Graduate students: Ethan Meyers (MIT w/Poggio, now Assistant
Professor, Hampshire College), Julie Blumberg (U. Freiburg, now U. Freiburg),
Mengmi Zhang (now postdoc HMS), Hanlin Tang (now Intel), William Lotter (now founder
startup), Joseph Olson (now postdoc U. Alabama), Jerry Wang (current), Yuchen
Xiao (current), Emma Giles (now founder startup), Will Xiao (current), David Mazumder (current), Pranav Misra (current)
Masters students: Charlotte Moermann, Eleonora
Iaselli, Martin Schrimpf, Stephan Grzelkowski,
Matthias Tsai, Vincent Jacquot, Eric Wu, Kevin Wu
MD students: Nambi Nallasamy,
Wui Ip
Selected
List of Undergraduate students
from Harvard, MIT, Boston College, Emmanuel College, Northeastern University,
Caltech, Princeton, Johns Hopkins University (including current position where
known): Arielle Benico, Josiah Ryan, Allison
Rosenberg, Joanna Li, Iulia Neagu (Grad. Student, Harvard
University), Brenda Li, Jasmine Yan, Ben Tsuda
(Associate Computational Biologist, Broad Institute), Enrique Tobis (Tools Developer, Two Sigma Investments), Vanesa Tan
(Engineer Manager, Quora), Andre Souffrant
(Quality Assurance Automation Engineer, HealthFortis),
Melissa Romaine, Gnel Pivazyan
(MD student, Keck School of Medicine), Patricia Pedreira
(Research Assistant, University of Miami), Jessie Pascal, Nida Nashaud, Nambi Nallasami (Ophthalmology Resident, Duke Medical School),
Elizabeth Meller, Daniel Lopez Martinez (Grad.
Student at MIT, Dept. of CBE), Frank Maldonado (Analyst at Peter J Solomon
Company), Randall Lin (Research Engineer at Halo Neuroscience), Hoey Lim, Ishika Kulatilaka, Phil Kuhnke (Grad.
Student at University of Trento, Program in Cognitive Neuroscience), Andrew
Kim, Tessa Kaslewicz (Neurologic Music Therapist,
MT-BC), Sandra Hernandez, Laura Groomes (Med. Student
at University of New England), Rosa Frias (Research Technician, MGH), McKayla Finneran (Clinical Assistant, Dana Farber Cancer
Institute), Sheila Drakeley (Research Assistant,
Boston Children’s Hospital), Danielle Christy (Mental Health Worker at Monte Nido & Affiliates), Veronica Camara
(Grad. Student, Regis College), Adrianna Boulin
(Founder, Jamakin Me Smart), Amir Bitran (Grad.
Student, Harvard University), Katelyn Barry, Asante Badu, Walter Hardesty (MD
student, The Ohio State University College of Medicine), Candace Ross (Grad.
Student, MIT), Nicholas Knouf (Assistant Professor,
Wellesley College), Angela Yu (Associate Professor, UCSD), Stacey Emile,
Garrett Lam (Rhodes Scholar), Ege Yumusak
(Grat. Student, University of Cambridge), Tais Alemar (Grad. Student, St.
John’s University), Pamela Ardizzone, Marlise Arlellano, Emma Barker,
James Carroll, Sarah Dowcett, Katherine Fazioli (Research Assistant, Harvard Medical School), Wendy
Fernandez, Melanie Fu, Meron Girmaiy
(Program Coordinator at Ascentria Care Alliance),
Caroline Harley, Kaley Jenny, Nicholas Lavorna,
Christina Leahy (Emergency Room Technician, Brigham and Women's Hospital), Ana
Paredes, Josue Ortega (Grad. Student, Baylor College of Medicine), Ayotunde Odejayi (Xeon Phi Design
Verification Intern at Intel), Victoria Perron,
Justin Sanchez, Jacky Sarette, Duncan Stothers, Annabelle Tao, Gabriela
Taveras, Tuyen Tran, Katterin
Vargas, Pricila Vieria-Gameiro,
Ziyi Zhu (Rochester).
High-school students: Eshan Govil,
Daniel Hanover, Martin Pleynet