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Professor |
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Children’s Hospital
Boston, Harvard Medical School |
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Center for Brain
Science, Harvard University |
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Center for Brains, Minds
and Machines Kempner Institute for
the Study of Natural and Artificial Intelligence |
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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.
2000
Everhart Distinguished Graduate
Student Lecture Award. Caltech.
2002 Lawrence L. and
Audrey W. Ferguson 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
Google scholar: https://scholar.google.com/citations?user=WxZ_6nsAAAAJ&hl=en
TLDR (too-long didn’t read), 5 selected recent publications
· Recurrent computations for visual pattern completion. Tang H, Schrimpf M, Lotter W, Moerman C, Paredes A, Ortega Caro J, Hardesty W, Cox D, Kreiman
G. (2018) PNAS, 115:8835-884.
·
Benchmarking out-of-distribution
generalization capabilities of DNN-based encoding models for the ventral visual
cortex. Madan S, Xiao W, Cao M, Pfister H,
Livingstone M, Kreiman G. (2024). NeurIPS.
Books
1.
Kreiman G. Biological and Computer
Vision. Cambridge University Press, 2021.
2.
Fried I,
Rutishauser U, Cerf M and Kreiman G, editors. Single neuron studies of the
human brain.
Probing
cognition. MIT Press,
2014.
3.
Kriegeskorte N and Kreiman
G, editors. Understanding visual population codes. MIT Press, 2011.
Peer-reviewed primary publications
1.
Hidalgo D, Dellaferrera
G, Xiao W, Papadopouli M, Smirnakis
S, Kreiman G. Trial-by-trial inter-areal interactions in visual cortex in
the presence or absence of visual stimulation. eLife, under review.
2.
Zhang M, Dellaferrera
G, Sikarwar A, Armendariz M, Mudrik
N, Agrawal P, Madan S, Barbu A, Yang H, Kumar T, Sadwani M, Dellaferrera S, Pizzochero M, Pfister
H, Kreiman G. Can machines imitate humans? Integrative Turing tests for vision
and language demonstrate a narrowing gap. Nature Human Behavior, under
review.
3.
Armendariz M, Blumberg J, Singer J, Aiple F, Kim J, Reinacher P, Schulze-Bonhage A, Kreiman G. Neurons in the human brain encode
rapidly learned visual information to reshape perception. Nature, under
review.
4.
Casile A, Cordier A, Kim JG, Cometa A, Madsen JR, Stone S, Ben-Yosef G, Ullman S, Anderson
W, Kreiman (2025). Neural correlates of minimal recognizable configurations
in the human brain. Cell Reports, In Press.
5.
Ferrante O, Gorska U, Henin S, Hirschhorn R, Khalaf A, Lepauvre A, Liu L, Richter D, Vidal Y, Bonacchi
N, Brown T, Sripad P, Armendariz M, Bendtz K, Ghafari T, Hetenyi D, Jeschke J, Kozma C, Mazumder DR, Montenegro S, Seedat A, Sharafeldin A, Yang, S, Baillet
S, Chalmers DJ, Cichy RM, Fallon F, Panagiotaropoulos TI, Blumenfeld H, de Lange FP, Devore S,
Jensen O, Kreiman G, Luo H, Boly M, Dehaene S, Koch C, Tononi G, Pitts M, Mudrik
L, Melloni L (2025). An adversarial collaboration
to critically evaluate theories of consciousness. Nature, In Press.
6.
Bono S, Madan S, Grover I, Yasueda M, Breazeal C, Pfister H, Kreiman G (2025). The
indoor training effect: unexpected gains
from distribution shifts in the transition function. AAAI Conference on
Artificial Intelligence.
7.
Talbot MB, Kreiman G, DiCarlo JJ, Gaziv G (2025). L-WISE: Boosting human image category learning
through model-based image selection and enhancement. International
Conference on Learning Representations (ICLR)
8.
Xiao W, Sharma S, Kreiman G,
Livingstone MS (2024) Feature-selective responses in macaque visual
cortex follow
eye movements during natural vision. Nature
Neuroscience 6:1157-1166
9.
Li C, Kreiman G, Ramanathan S (2024). Discovering
neural policies to drive behavior by integrating deep reinforcement learning
agents with biological neural networks. Nature Machine Intelligence,
6:726–738
10.
Madan S, Xiao W, Cao M, Pfister H,
Livingstone M, Kreiman G. (2024). Benchmarking out-of-distribution
generalization capabilities of DNN-based encoding models for the ventral visual
cortex. NeurIPS.
11.
Wang C, Yaari
A, Singh A, Subramaniam V, Rosenfarb D, Misra P,
Madsen J, Stone S, Kreiman G, Katz B, Cases I, Barbu
A (2024). Brain treebank: Large-scale intracranial recordings from
naturalistic language stimuli. NeurIPS.
12.
Zheng J, Yebra
M, Schjetnan AGP, Mosher C, Kalia A, Chung JM, Reed
CM, Valiante TA, Mamelak A,
Kreiman G, Rutishauser U (2024). Theta phase precession supports memory formation
and retrieval of naturalistic experience in humans. Nature Human Behavior
13.
Li C, Brenner JW, Boesky A, Ramanathan
S, Kreiman G (2024). Neuron-level prediction and noise can implement
flexible reward-seeking behavior. bioRxiv 2024.05.22.595306
14.
Subramaniam V, Conwell C, Wang C,
Kreiman G, Katz B, Cases I, Barbu A (2024). Revealing
vision-language integration in the brain with multimodal networks. International
Conference on Machine Learning (ICML).
15.
Djambazovska S, Zafer A, Ramezanpour H,
Kreiman G, Kar K (2024). The impact of scene context on visual object
recognition: comparing humans, monkeys, and computational models. bioRxiv 2024.05.27.596127
16.
Hidalgo D, Dellaferrera
G, Xiao W. Papadopouli M, Smirnakis
SM, Kreiman G (2024). Trial-by-trial inter-areal interactions in visual
cortex in the presence or absence of visual stimulation. bioRxiv, 2024.12.05.626981
17.
Misra P, Shih Y, Yu H, Weisholtz D, Madsen J, Sceillig,
S, Kreiman G (2024). Invariant neural representation of parts of speech in the
human brain. bioRxiv 2024.01.15.575788.
18.
Srinivasan RF, Mignacco
F, Sorboro M, Refinetti M,
Cooper A, Kreiman G, Dellaferrera G. (2024). Forward
learning with top-down feedback: empirical and analytical characterization.
International Conference on Learning Representations (ICLR).
19.
Madan S, Li Y, Zhang M, Pfister H,
Kreiman G. (2024). Improving generalization by mimicking the human visual
diet. bioRxiv 2206.07802
20.
Singh P, Li Y, Sikarwar
A, Lei W, Gao D, Talbot MB, Sun Y, Shou MZ, Kreiman G, Zhang M. (2023). Learning
to Learn: How to Continuously Teach Humans and Machines. International
Conference on Computer Vision (ICCV).
21.
Aghajan Z, Kreiman G, Fried I (2023). Minute-scale periodicity
of neuronal firing in the human entorhinal cortex. Cell Reports 42, 113271.
22.
Xiao Y, Sanchez Lopez P, Wu R, Wei PH,
Shan YZ, Weisholtz D, Cosgrove GR, Madsen JR, Stone
S, Zhao GG, Kreiman G (2023). Integration of recognition, episodic, and
associative memories during complex human behavior. bioRxiv
2023.03.27.534384
23.
Bricken T, Davies A, Singh D, Krotov D, Kreiman
G. (2023) Sparse distributed memory is a continual learner. International
Conference on Learning Representations (ICLR)
24.
Wang C, Subramaniam
V, Yaari A, Kreiman G, Katz B, Cases I, Barbu A. (2023). BrainBERT:
Self-supervised representation learning for Intracranial Electrodes. International
Conference on Learning Representations (ICLR)
25.
Bricken T, Schaeffer R, Olshausen B, Kreiman
G. (2023) Emergence of Sparse Representations from Noise. International
Conference on Machine Learning (ICML)
26.
Xiao Y, Chou C, Cosgrove
GR, Crone NE, Stone S, Madsen JR, Reucroft I, Weisholtz D, Shih YC, Yu HY, Anderson WS, Kreiman G (2023) Cross-task
specificity and within-task invariance of cognitive control processes. Cell
Reports 42:111919
27.
Zhang Y, Aghajan ZM, Ison M, Lu Q, Tang H,
Kalender G, Monsoor T, Zheng
J, Kreiman G, Roychowdhury V, Fried I (2023). Decoding
of human identity by computer vision and neuronal vision. Scientific Reports
13:651
28.
Melloni L, Mudrik L, Pitts M, Bentz K,
Ferrante O, Gorska U, Hirschhorn R, Khalaf A, Kozma C, Lepauvre A, Liu L, Mazumder
D, Richter D, Zhou H, Blumenfeld H, Chalmers DJ, Devore S, Fallon F, de Lange F,
Jensen O, Kreiman G, Luo H, Dehaene S, Koch C, Tononi
G (2023). An adversarial collaboration protocol for testing contrasting
predictions of global neuronal workspace and integrated information theory.
PLoS One
29.
Talbot, MB, Zawar R, Badkundri R, Zhang M, Kreiman G. (2023). Tuned
compositional feature replays for efficient stream learning. IEEE
Transactions on Neural Networks and Learning Systems (TNNLS)
30.
Casper S, Nadeau M, Kreiman
G. (2022). Robust feature-level adversaries are interpretability tools.
NeurIPS 35, 33093-33106
31.
Zhang M, Dellaferrera G, Sikarwar A, Armendariz
M, Mudrik N, Agrawal P, Madan S, Barbu
A, Yang H, Kumar T, Sadwani M, Dellaferrera
S, Pizzochero M, Pfister H, Kreiman G (2022). Human
or Machine? Turing Tests for Vision and Language. arXiv
2211.13087
32.
Liu X, Sikarwar A, Lim JH, Kreiman G, Shi Z, Zhang M (2022). Reason
from context with self-supervised learning. arXiv 2211.12817
33.
Ding Z, Ren X, David
E, Vo Melissa, Kreiman G, Zhang M (2022). Efficient Zero-shot Visual Search via
Target and Context-aware Transformer. arXiv 2211.13470
34.
Bardon A, Xiao W,
Ponce CR, Livingstone MS, Kreiman G (2022). Face neurons encode nonsemantic features. Proceedings of the National
Academy of Sciences of the United States of America 119, e2118705119,
doi:10.1073/pnas.2118705119.
35.
Zhang M, Armendariz M,
Xiao W, Rose O, Bendtz K, Livingstone M, Ponce CR, Kreiman
G (2022). Look Twice: A Computational Model of Return Fixations across Tasks
and Species. PLoS Comp Bio 18(11):e1010654
36.
Zheng J, Schjetnan AGP, Yebra M, Mosher C,
Kalia S, Valiante TA, Mamelak
A, Kreiman G, Rutishauser U (2022). Cognitive boundary signals in the human
medial temporal lobe shape episodic memory representation. Nature Neuroscience
25:358-368
37.
Hoogsteen KMP, Szpiro S, Kreiman G, Peli E (2022). Beyond the Cane:
Describing Urban Scenes to Blind People for Mobility Tasks. ACM
Transactions on Accessible Computing 2022-09-3
38.
Shaham N, Chandra J,
Kreiman G, Sompolinsky H (2022). Stochastic consolidation of lifelong memory.
Scientific Reports, 12:13107
39.
Murugan R, Kreiman G (2022). Multiple transcription autoregulatory
loops act as robust oscillators and decision making motifs. Computational
and Structural Biotechnology Journal 20:5115-5135
40.
Dellaferrera G, Kreiman G (2022). Error-driven Input Modulation:
Solving the Credit Assignment Problem without a Backward Pass. International
Conference on Machine Learning (ICML). 162:4937-4955
41.
Sikarwar, A, Kreiman G (2022). On the efficacy of co-attention
transformer layers in visual question answering. arXiv 2201.03965.
42.
Gupta SK, Zhang M,
Wu CC, Wolfe JM, Kreiman G (2021). Visual Search Asymmetry: Deep Nets and
Humans Share Similar Inherent Biases. NeurIPS 34:6946-6959
43.
Weisholtz, DS, Kreiman G, Silbersweig DA,
Stern E, Cha B, Butler T (2021). Localized Task-Invariant Emotional Valence
Encoding Revealed by Intracranial Recordings. Soc Cogn
Affect Neurosci, doi:10.1093/scan/nsab134
44.
Wang J, Tao A,
Anderson WS, Madsen JR, Kreiman G (2021). Mesoscopic physiological interactions
in the human brain reveal small world properties. Cell Reports 36
(8) 109585
45.
Bomatter P, Zhang M, Karev D, Madan S,
Tseng C, Kreiman G (2021). When Pigs Fly: Contextual Reasoning in Synthetic
and Natural Scenes. International Conference on Computer Vision (ICCV)
46.
Casper S, Boix X, D'Amario V, Guo L, Schrimpf M, Vinken K, Kreiman G. (2021). Frivolous Units:
Wider Networks are not really that Wide. AAAI Conference on Artificial Intelligence
47.
Vinken K, Boix X, Kreiman G (2020). Incorporating intrinsic
suppression in deep neural network models captures dynamics of adaptation in
neurophysiology and perception. Science
Advances, 6: eabd4205
48.
Xiao W. and Kreiman
G. (2020). XDream: Finding preferred stimuli for visual neurons using
generative networks and gradient-free optimization. PLoS Computational
Biology 16(6): e1007973
49.
Lotter W, Kreiman G,
Cox D. (2020) A neural network trained to predict future video frames mimics
critical properties of biological neuronal responses and perception. Nature
Machine Intelligence, 2:210-219
50.
Zhang M, Tseng C, Kreiman
G. (2020) Putting visual object recognition in context. Proceedings
of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
12985-12994.
51.
Jacquot V, Ying J, Kreiman G. (2020) Can Deep Learning Recognize
Subtle Human Activities? Proceedings of the IEEE/CVF Conference on Computer
Vision and Pattern Recognition (CVPR) 14244-14253.
52.
Ben-Yosef G, Kreiman
G, Ullman S. (2020) Minimal videos: Trade-off between spatial and temporal
information in human and machine vision. Cognition 201:104263.
53.
Yuan L, Xiao W, Kreiman
G, Tay FEH, Feng, JL, Livingstone, M (2020). Adversarial images for the
primate brain. arXiv. 2011.05623
54.
Olson J, Kreiman G.
(2020). Simple learning rules generate complex canonical circuits. arXiv:2009.06118
55.
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.
56.
Madhavan R, Bansal
AK, Madsen JR, Golby AJ, Tierney TS, Eskandar EN,
Anderson WS, Kreiman G (2019). Neural interactions underlying visuomotor
associations in the human brain. Cerebral
Cortex, 29:4551-4567
57.
O'Connel TP, Chun MM, Kreiman G. (2019) Zero-shot neural decoding
of visual categories without prior exemplars. bioRxiv
10.1101/700344
58.
Zhang M, Tseng C,
Montejo K, Kwon J, Kreiman G. Lift-the-flap: what, where and when for context
reasoning. arXiv 1902.00163
59.
Misra P, Marconi A, Kreiman
G. (2018) Minimal memory for details in real life events. Scientific Reports, 8, 16701.
60.
Tang H, Schrimpf M, Lotter W, Moerman C,
Paredes A, Ortega Caro J, Hardesty W, Cox D, Kreiman G. (2018) Recurrent
computations for visual pattern completion. PNAS, 115:8835-884.
61.
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.
62.
Zhang M, Feng J, Lim
JH, Zhao Q, Kreiman G. (2018) What am I searching for? arXiv
1807.11926
63.
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.
64.
Wu K, Wu E, Kreiman
G (2018). Learning scene gist with convolutional neural networks to improve
object recognition. IEEE Information
Sciences and Systems.
65.
Isik I, Singer J, Madsen JR, Kanwisher N, Kreiman G (2018). What
is changing when: Decoding visual information in movies from human intracranial
recordings. Neuroimage,
180:147-159.
66.
Lotter, W, Kreiman,
G, Cox, D. (2017) Deep Predictive Coding Networks for Video Prediction
and Unsupervised Learning. International Conference on Learning
Representations (ICLR).
67.
Cheney N, Schrimpf M, Kreiman G. (2017) On the Robustness of
Convolutional Neural Networks to Internal Architecture and Weight Perturbations.
arXiv:1703.08245v1
68.
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.
69.
Kreiman G. (2016). A
null model for cortical representations with grandmothers galore. Language, Cognition and Neuroscience,
32, 274-285.
70.
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.
71.
Lotter W, Kreiman G,
Cox D (2016). Unsupervised Learning of Visual Structure using Predictive
Generative Networks. International Conference on Learning Representations
(ICLR)
72.
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.
73.
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.
74.
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
75.
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.
76.
Singer JM, Madsen
JR, Anderson WS, Kreiman G. (2015). Sensitivity to timing and order in human
visual cortex. Journal of Neurophysiology 113:1656-69
77.
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.
78.
Singer JM, Kreiman G.
(2014). Short temporal asynchrony disrupts visual object recognition. Journal of Vision 14:7.
79.
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.
80.
Bansal A,
Madhavan R, Agam Y, Golby A, Madsen J and Kreiman G (2014). Neural dynamics
underlying target detection in the human brain. Journal of
Neuroscience, 34:3042-3055
81.
Nassi J, Gomez-Laberge C, Kreiman G, Born R (2014). Corticocortical
feedback increases the spatial extent of normalization. Frontiers
in Systems Neuroscience, 8:105.
82.
Singer JM, Kreiman G
(2014). Short temporal asynchrony disrupts visual object recognition. Journal
of Vision, 12:14
83.
Murugan R and Kreiman
G (2012). Theory on the coupled stochastic dynamics of transcription and
splice-site recognition. PLoS Computational Biology, 8:1-13.
84.
Bansal,
A, Singer J, Anderon WS, Golby, A, Madsen JR, Kreiman G (2012). Temporal stability
of visually selective responses in intracranial field potentials recorded from
human occipital and temporal lobes. Journal of Neurophysiology, 108:3073-3086.
85.
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, 40:7858-7869.
86.
Burbank K
and Kreiman G (2012). Depression-biased reverse plasticity rule is required
for stable learning at top-down connections. PLOS Computational Biology, 8:1-16.
87.
Fried I, Mukamel R, Kreiman G (2011). Internally generated
preactivation of single neurons in human medial frontal cortex predicts
volition. Neuron, 69:
548-562.
88.
Kreiman G
and Maunsell J (2011). Nine criteria for a measure of scientific output.
Frontiers in Computational Neuroscience,
2011. 5:48.
89.
Murugan R and
Kreiman G (2011). On the minimization of fluctuations in the response times
of autoregulatory gene networks. Biophysical
Journal, 101: 1297-1306.
90.
Hemberg M and Kreiman
G (2011). Conservation of transcription factor binding events predicts gene
expression across species. Nucleic Acids Research, 39:7092-7102.
91.
Agam Y,
Liu H, Pappanastassiou A, Buia C, Golby AJ, Madsen JR, Kreiman G (2010). Robust
selectivity to two-object images in human visual cortex. Current
Biology, 20:872-879.
92.
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 (2010). Widespread transcription at thousands of enhancers during
activity-dependent gene expression in neurons. (* = equal contribution) Nature,
465:182-187.
93.
Rasch M,
Logothetis NK, Kreiman G (2009). From
neurons to circuits: linear estimation of local field potentials.
Journal
of Neuroscience 29:13785-13796
94.
Horng S, Kreiman
G, Ellsworth C, Page D, Blank M, Millen K, Sur M (2009). 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, 29:13672-13683
95.
Liu H, Agam Y, Madsen JR, Kreiman G (2009). Timing, timing,
timing: Fast decoding of object information from intracranial field potentials
in human visual cortex. Neuron 62:281-290
96.
Meyers E, Freedman D, Kreiman G, Miller E, Poggio T (2008).
Dynamic Population Coding of Category Information in ITC and PFC. Journal
of Neurophysiology, 100:
1407-1419
97.
Leamey C., Glendining K., Kreiman
G., Kang N., Kuan H., Fassler R., Sawatari A.,
Tonegawa S., and Sur M (2008). Differential Gene Expression between Sensory
Neocortical Areas: Potential Roles for Ten_m3 and Bcl6 in Patterning Visual and
Somatosensory Pathways. Cerebral
Cortex 18:53-66
98.
Tropea D, Kreiman G, Lyckman AW, Mukherjee S, Yu H, Horng
S, Sur M (2006). Distinct gene systems mediating activity-dependent
plasticity in visual cortex. Nature Neuroscience 9:660-668
99.
Kreiman G*, Hung C*, Kraskov
A, Quiroga R, Poggio T, DiCarlo J (2006). Object selectivity by local field
potentials in the macaque inferior temporal cortex. Neuron 49:433-445 (*=equal contribution)
100.
Hung C*, Kreiman G*, Poggio T, DiCarlo J (2005). Fast
read-out of object identity from macaque inferior temporal cortex. Science
310:863-866. (*=equal
contribution)
101.
Quian-Quiroga R,
Reddy L, Kreiman G, Koch C, Fried I (2005). Invariant visual representation
by single neurons in the human brain. Nature 435:1102-1107
102.
Kreiman G (2004). Identification of sparsely distributed
clusters of cis-regulatory elements in sets of co-expressed genes. Nucleic Acids Research 32:2889-2900
103.
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 (2004). A
gene atlas of the mouse and human protein-encoding transcriptomes. PNAS 101:6062-6067
104.
Yeo G., Holste D., Kreiman G. and Burge C (2004). Variation
in alternative splicing across human tissues. Genome Biology, 5:R74
105.
Kreiman G, Fried I, Koch C (2002). Single
neuron responses in the human brain during flash suppression. PNAS 99:8378-8383
106.
Krahe R., Kreiman G.,
Gabbiani F., Koch C. and Metzner W (2002). Stimulus
encoding and feature extraction by multiple pyramidal cells in the hindbrain of
weakly electric fish. J. Neuroscience
22:2374-2382
107.
Zirlinger M., Kreiman G.
and Anderson D (2001). Amygdala-enriched genes identified by microarray
technology are restricted to specific amygdaloid sub-nuclei. PNAS 98:5270-5275
108.
Kreiman G., Koch C. and Fried I (2000). Imagery
neurons in the human brain. Nature
408:357-361.
109.
Kreiman G., Krahe R., Metzner W., Koch C. and Gabbiani F (2000). Robustness and variability of
neuronal coding by amplitude sensitive afferents in the weakly electric fish Eigenmannia.
J. Neurophysiology 84:189-204
110.
Kreiman G., Koch C. and Fried I (2000). Category-specific
visual responses of single neurons in the human medial temporal lobe. Nature Neuroscience 3:946-953
111.
Ouyang Y., Rosenstein
A., Kreiman G., Schuman
E. M. and Kennedy M. B (1999). Tetanic stimulation leads to increased
accumulation of CaMKII via dendritic protein synthesis in hippocampal neurons.
Journal of Neuroscience 19:7823-7833.
112.
Inon de Iannino N., Briones G., Kreiman G. and Ugalde R (1996). Characterization
of the biosynthesis of b(1-2)
cyclic glucan in R. Freddii. Cell.
Mol.. Biol. 42:617-629
Reviews
1.
Triggiani, AI, Kreiman
G, Lewis C, Maoz U, Mele A, Mudrik L, Roskies A, Schurger A, Hallett M
(2023). What is the intention to move and when does it occur? Neuroscience
and Behavioral Reviews, 105199
2.
Kreiman G
and Serre T (2020). Beyond the feedforward sweep: feedback computations in the
visual cortex. Ann N Y Acad Sci.
1464:222-241.
3.
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.
4.
Quian Quiroga R, Kreiman G (2010). Measuring
sparseness in the brain. Psych. Reviews, 17:291-297
5.
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
6.
Kreiman G (2007). Single neuron
approaches to human vision and memory. Current Opinion in Neurobiology 17:471-475
7.
Serre T, Kreiman G, Kouh
M, Cadieu C, Knoblich U, Poggio T (2007). A
quantitative theory of immediate visual recognition. Progress In Brain Research 165C:
33-56.
8.
Serre
T, Kouh M, Cadieu C, Knoblich U, Kreiman G, Poggio T. (2005) A theory of object
recognition MIT AI Memo 2005-036.
9.
Crick F, Koch C, Kreiman G, Fried I (2004). Consciousness
and neurosurgery. Neurosurgery
55:273-282
10.
Kreiman G (2004). Neural coding: computational and biophysical perspectives.
Physics of Life Reviews, 2:71-102.
11.
Rees G., Kreiman G. and Koch C (2002). Neural correlates of consciousness
in humans. Nature Reviews
Neuroscience 3:261-270
Book
chapters
1.
Xiao W, Zhang M, Kreiman G (2023). Artificial
intelligence in neuroscience. Chater 10 in
Neuroscience for Neurousrgeons, edited by Akter F, Emptage N, Engert F, and Berger M. Cambridge University Press.
2.
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.
3.
Tang H, Kreiman G. (2017). Recognition
of occluded objects. In Computational and Cognitive Neuroscience of Vision.
(ed Zhao, Q). Singapore: Springer-Verlag.
4.
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).
5.
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).
6.
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).
7.
Kreiman G. Neural correlates of
consciousness: perception and volition. In Cognitive Neuroscience Vol. V
(ed M Gazzaniga) (MIT Press, In Press).
8.
Kreiman G. Computational Models of
Visual Object Recognition. In Principles of neural coding (eds S Panzeri
& R Quiroga) (CRC Press, 2013).
9.
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
10.
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
11.
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
12.
Kreiman G. Models of visual recognition.
(Chapter 29) In “Principles of neural coding’, edited by Quiroga and Panzeri. CRC
Press, 2013.
13.
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]
14.
Kreiman G. Single cell studies,
human. In Encyclopedia of Consciousness, P. Wilken, ed. (Oxford, Oxford
University Press). 2010
Commentaries
1.
Kreiman G (2023). Neural coding:
Stimulating cortex to alter visual perception. 33, R117-R118. Current
Biology 33:R117-R118
2.
Armendariz M, Xiao W, Vinken K, Kreiman
G (2022). Do computational models of vision need shape-based
representations? Evidence from an individual with intriguing visual perceptions.
Cognitive Neuropsychology 39:75-77.
3.
Zhang M and Kreiman G. (2021) Beauty
is in the eye of the machine. Nature Human Behavior, 5(6): 675-676
4.
Kreiman G. (2019) It's a small dimensional
world after all. Comment on “The unreasonable effectiveness of small neural
ensembles in high-dimensional brains" by Gorban et al. Physics
of Life Reviews 29:96-97.
5.
Kreiman G (2013). Mind the quantum? Trends
in Cognitive Science, 17(3): 109
6.
Kreiman G. Literary inspiration.
Nature,
2011. 475:453-454.
7.
Tang H, Kreiman G (2011). Face Recognition:
Vision and Emotions beyond the Bubble. Current Biology 21:R888-890
8.
Anderson WS and Kreiman G. (2011). Neuroscience:
What We Cannot Model, We Do Not Understand. Current Biology. 21: R124-R125.
9.
Singer J, Kreiman G (2009). Toward unmasking
the dynamics of visual perception. Neuron. 64:446-447.
10.
Tsuchiya N, Kreiman G. (2008). Psyche,
attention and consciousness. Psyche 14, 1-2.
11.
Kreiman G. (2008). Biological object
recognition. Scholarpedia 3,
2667.
12.
Kreiman G, (2007) Neuroscience: from
the very large to the very small. Current Biology, 17:R768-R770
13.
Kreiman
G. (2001). Moveo ergo sum. BioEssays 23:662.
2018-2025 Harvard. HMS 140/240. Biological and Artificial Intelligence
2014-2025 MBL, Woods. Brains, Minds and Machines Summer Course
2007-2024 Harvard. HMS 130/230. Visual Object Recognition
2010-2024 Harvard Biophysics 300
2022, 2024 Harvard HMS MedSci302qc. Responsible conduct in science
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)
TLDR, 5 selected mentees:
William Anderson (now: Associate Professor, Johns
Hopkins School of Medicine)
Arjun Bansal (now: co-founder and vice-president,
Nervana Systems/Intel/Log10)
Martin Hemberg (now: Associate Professor,
Harvard Medical School)
Leyla Isik (now: Assistant Professor, Johns
Hopkins University)
Hanlin Tang (now: Founder and
CTO, MosaicML)
Full list (current position when
known, faculty, start-up,
other)
Postdocs: Yigal Agam (now: Associate
Director of Bioinformatics, Fluent Biosciences), William
Anderson (now: Associate Professor, Johns Hopkins School of Medicine), Marcelo
Armendariz (current), Frederico Azevedo (now: Postdoc,
MIT), Feraz Azhar (now: Assistant Professor,
University of Notre Dame), Arjun Bansal (now:
co-founder and vice-president, Nervana Systems/Intel/Log10), Katarina Bendtz (now: R&D at Novatron
Fusion Group), Xavier Boix (now: Research Scientist, Fujitsu), Calin Buia (now: GM Pace Consulting), Kendra
Burbank (now: Assistant Senior Instructional Professor, University of Chicago),
Camille Gomez-Laberge (now: Associate Teaching Professor,
Northeastern University), Martin Hemberg
(now: Associate Professor, Harvard Medical School), Leyla Isik (now: Assistant Professor, Johns Hopkins
University), Jiye Kim (now: Research
Scientist, DeepHealth), Hesheng Liu
(now: Assosciate Professor, MGH), Radhika Madhavan
(now: Senior Scientist, GE Global Research),
Thomas Miconi (now: Research Leader, Uber AI),
Rajamanickam Murugan (now:
Professor, IIT Madras), Carlos Ponce (now: Assistant
Professor, Harvard Medical School), Nimrod Shaham (now: Research leader,
MobileEye), Jed Singer (now: Data Scientist, Infinite
Analytics), Sarit Szpiro
(now: Assistant Professor, University of Haifa), Kasper Vinken (now: Senior
Researcher, Fujitsu Research), Daniel Weisholtz (now: Instructor, Harvard Medical School),
Mengmi Zhang (now: Assistant Professor, University
of Singapore), Jie Zheng (now: Assistant
Professor, University of California, Davis).
Ph.D.
students:
Trenton Bricken (current), Julie
Blumberg (U. Freiburg, now: Instructor, University of Freiburg), Giorgia Dellaferrera (now: McKinsey
Consulting), Emma Giles (now: Founder and CEO, SoWork), Dianna Hidalgo (current), William Lotter (now: Founder
DeepHealth, Assistant
Professor, Harvard Medical School), Chenguang
Li (current), Spandan Madan (current), David Mazumder
(now: graduate student at HMS), Ethan Meyers (now
Assistant Professor, Hampshire College and Visiting Professor, Yale University),
Kim Minnyung (current), Pranav Misra (current),
Joseph Olson (now: Postdoc, U. Alabama), Elisa Pavarino
(current), Leonardo Pollina (current), Shane Shang
(current), Morgan Talbot (current), Hanlin Tang (now: Founder and CTO, MosaicML),
Jerry Wang (now: Postdoc, Boehringer, Germany), Yuchen
Xiao (now: Assistant Professor, Westlake University), Will Xiao (now: Postdoc,
Harvard Medical School), Mengmi Zhang (now:
Assistant Professor, University of Singapore),
Masters
students:
Phillipe Bommater, Serena Bono (now: PhD student,
MIT), Aurelie Cordier, Sara Djambazovska, Camille Gollety, Stephan Grzelkowski, Marana Hakobyan, Eleonora Iaselli (now: Technology consulting analyst, Accenture), Vincent
Jacquot (Engineer, Merck Group), Alexandre Luster, Charlotte Moermann (Clinical affairs manager, Compremium),
Alice Motschi (now: PhD student, Medical University
of Vienna), Leonardo Pollina (now: PhD student, EPFL),
Yael Porte (now: Clinical evaluator, Biotronik), Paula
Sanchez Lopez, Martin Schrimpf
(now: Assistant Professor, EPFL), Ravi Srinivasan (now: PhD student, UC
Berkeley), Matthias Tsai (now: PhD student, University of Bern), Eric Wu, Kevin
Wu, Zihao Xu.
MD students: Laura Groomes, Wui Ip, Nambi Nallasamy,
Undergraduate
students (selected list) from
Harvard, MIT, Boston College, Emmanuel College, Northeastern University,
Caltech, Princeton, Johns Hopkins University (including current position where
known): Stephen Casper, Alexander Davies, Victoria Eisenhauer, Ilai Gavish, Deepak Singh, Warren Sunada-Wong,
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, 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, Rohil Badkundry, 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, Claire
Tseng, RunLin Wang, Michelle Lim, Grant Chau, Jay
Chandra, Leonard Tang, Annabelle Tao, Gabriela Taveras, Tuyen Tran, Katterin Vargas, Pricila Vieria-Gameiro, Ziyi Zhu (Rochester).
High-school students: Eshan Govil, Daniel Hanover, Martin Pleynet,
Myles Epstein.
Ad hoc reviewer
or Area Chair for the following journals/conferences
AAAI Conference on Artificial
Intelligence, Acta Astronomica, Bioinformatics, Biotechniques, BMC Bioinformatics, Brain, Cell Reports, Cerebral Cortex, Comparative Biochemistry and Physiology, Computational
Intelligence and Neuroscience, Computational Neuroscience Annual Meeting, Computer
Vision and Pattern Recognition (CVPR), Cognitive Computation, Current Biology, Experimental
Brain Research, Frontiers in Computational
Neuroscience, Frontiers in Perception
Science, Frontiers in Neuroscience, Genome Biology, HFSP Journal, IEEE Journal
of Selected Topics in Signal Processing, IEEE Spectrum, IEEE Transactions in Computational
Biology and Bioinformatics, International Conference on Computer Vision (ICCV),
International Conference on Learning Representations (ICLR), International Conference
on Machine Learning (ICML), ISMB, Journal
of Anatomy, Journal of Cognitive Neuroscience, Journal of Comparative Physiology
A, Journal of Computational Neuroscience, Journal of Neural Engineering,
Journal of Neurochemistry, Journal of Neuroscience, Journal of Neuroscience
Methods, Journal of Neurophysiology, Nature, Nature Communications, Nature
Machine Intelligence, Nature Methods, Nature Protocols, Nature Neuroscience, Neural
Computation, Neural Networks, Neural Information Processing Systems (NeurIPS), Neurocomputation,
Neuroimage, Neuron, Neuroscience, Nucleic Acids Research, PLoS Computational
Biology, PLoS Biology, PNAS, RECOMB, Science Advances, Scholarpedia,
Trends in Cognitive Science, Trends in Neuroscience.
Grant Review
Panels
National Science Foundation (NSF, Robust Intelligence Panel, Collaborative
Research in Computational Neuroscience Panel, Cognitive Neuroscience Panel,
Graduate Research Fellowship); NIH (SPC, LAM, ZRG1, T32 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), Wellcome Trust
(UK).
Patent Review
Patent
evaluation for US Patent and Trademark Office
Selected
Invited talks
Singapore U. 2024 | UCBerkeley,
2024 | MIT Museum of Science 2024 | Forth Symposium, Greece 2024. Haar workshop, Sestri Levante,
Italy, 2024 | Computational neuroscience, Heraklion, Greece, 2024 | Trieste,
Italy 2024 | NIH Consciousness Symposium, DC, 2023 | A*Star. Singapore 2023 | Janelia Farm, March 2023 | Sigtuna
Conference on Free will. Sweden, 2023 | Caltech, Pasadena, 2023 | ASSC,
Amsterdam, Netherlands, 2022 | Cleveland Clinic, Cleveland, 2022 | Cognitive
Neuroscience Annual Meeting, San Francisco 2022 | Cosyne conference, Lisbon,
2022 | NeurIPS, New Orleans, 2022 | Free will conference, Palm Springs 2022 | Memory
and the brain. Tel Aviv, Israel 2022 | Advanced Neuroscience School, Venice,
Italy, 2022 | McKnight Foundation Conference, Aspen, 2021 | How to review interdiscriplinary work. Berlin, Germany, 2021 | Cognitive
Neuroscience Symposium. Tel Aviv, Israel, 2020 | Cosyne conference workshop.
Denver, 2020 | Neuroscience-inspired AI vision systems. Kyoto, Japan, 2020 | AI
and the brain. Beijing, China, 2020 | Neuroscience-Inspired AI. Seoul, Korea,
2020 | Models of visual recognition. SFN Workshop. 2020 | Volitional decisions
and the brain. Sigtuna Conference, Sweden, 2020 | Limitations
of Machine Learning. Sestri Levante, Italy. 2019 | ECVP, Belgium. 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
09/1996 – 08/2002 Graduate student Computational Neuroscience Caltech
02/1999 – 08/2002 Visiting Scientist Neurosurgery UCLA
09/2002 – 12/2006 Whiteman fellow Brain and Cognitive Science,
CSAIL MIT
09/2001 – 08/2002 Research Scientist Genomics Institute Novartis
09/2008 – 08/2012 Advisory Board Medical Plexus
01/2007 – 12/2011 Assistant Professor Ophthalmology Harvard
Medical School
09/2009 – 06/2013 Faculty Neurology Boston
Children’s Hospital
01/2012 – 12/2018 Associate Professor Ophthalmology Harvard
Medical School
09/2016 – 08/2022 Advisory Board Caltech NIMH Brain Initiative
08/2018 – present Full Professor Ophthalmology Harvard Medical School
01/2007 – present Faculty Center
for Brain Science Harvard University / HMS
01/2007 – present Faculty Program
in Neuroscience Harvard University / HMS
09/2007 – present Faculty Swartz
Center for Theoretical Neuroscience Harvard University
09/2008 – present Faculty Mind
Brain and Behavior Initiative Harvard
University
09/2008 – present Faculty Program
in Biophysics Harvard University
01/2007 – present Faculty Program in Neurobiology Boston Children’s Hospital
01/2007 – present Faculty Ophthalmology Boston Children’s Hospital
01/2007 – present Visiting scientist Brain and Cognitive Science MIT
09/2013 – present Associate Director Center for Brains, Minds and Machines Harvard/MIT
09/2013 – present International collaborator Institute for Infocomm
Research A*Star, Singapore
09/2017 – present Advisory Board Zeta Interactive Corporation
09/2023 – present Faculty Kempner
institute for the study of natural and artificial intelligence
Antikythera.
Co-founder. Antikythera provides a platform for biophysically realistic simulations
of neural circuits.
Memorious.
Co-founder. Memorious uses AI and large language models to help people with
memory deficits.