Need-based travel grants will be awarded to workshop participants. The travel grant can be used for covering costs associated with the workshop such as NIPS registration, accommodation and travel. Please note that the travel grants may not cover all of your costs and we may not be able to award them to all applicants. The amount of money we award to each person will depend on the number of applicants and the location each applicant will be traveling from.

If you are a student who has not conducted research and would like a travel grant to attend our workshop, you may do so by either:

1) Submitting an abstract, and a paragraph describing financial need on the conference submission page OR

2) Submitting a one page statement describing your research interests in AI and reasons for participating in the workshop, and a paragraph describing financial need on the conference submission page These must be done by the deadline, October 13, 2017.

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The first Black in AI event will be co-located with NIPS 2017 in the Pike Ballroom at the Renaissance Long Beach Hotel in Long Beach, California on December 8th from 1:00pm to 6:00pm. The poster session will be held at the Broadlind 2 room on the second floor of the Renaissance hotel. The workshop will be followed by dinner 6:30-8:30. We invite Black AI researchers from around the world to share their work and learn about others’ research. The workshop will have invited talks from prominent researchers, oral presentations, and a poster session. There will also be socials to facilitate networking, discussion of different career opportunities in AI, and sharing of ideas to increase participation of Black researchers in the field. We invite all Black researchers, including undergraduates, graduate students, faculty, and researchers in industry to participate in this workshop. People of all races are also invited to attend the workshop to learn about the research being conducted by Black researchers across the world. Deadline for registration is October 31, 2017 and can done here. Please register as soon as possible to help us figure out headcount.

Important Dates

• October 13, 2017: Abstract submission deadline
• October 13, 2017: Travel grant application deadline
• October 29, 2017: Notification of acceptance
• October 31, 2017: Workshop registration deadline
• December 8th from 1:00pm-5:30pm: Workshop
• December 8th from 6:30pm-9:00pm: Dinner

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Submission Instructions

We welcome theoretical, empirical, and applied work in machine learning and artificial intelligence, including, but not limited to, search, planning, knowledge representation, reasoning, natural language processing, computer vision, robotics, multiagent systems, statistical reasoning, and deep learning. Work may be previously published, completed, or ongoing. Submissions will be peer-reviewed by at least 2 reviewers. The workshop will not publish proceedings. The presenter must be a Black researcher in AI, and does not need to be first author.

Submissions can be up to two page abstracts and must state the research problem, motivation, and technical contribution. Submissions must be self-contained and include all figures, tables, and references.

• Submission page: Black in AI CMT Page
• Travel Grants: In order to be considered for a travel grant, please select yes to the question Do you need a travel grant?

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1. AI Powered Process Improvement, Christine Custis*, NewPearl, Inc.
2. Morphological classification of Radio Sources and their Counterparts in Optical using Deep Machine Learning, Superviser: Prof R. Taylor, Wathela Alhassan*, University of Cape Town
3. Orchestra Mobile Crowdsensing and Computing Platform: A Roadmap for Further Development, Sando George*, Warsaw University of Technology; Maria Ganzha, Warsaw University of Technology; Marcin Paprzycki, Systems Research Institute, Polish Academy of Sciences
4. Using Dominant Sets for Data Association in Multi-Camera Tracking, Kedir Hamid Ahmed*, Ethiopian Biotechnology Institute
5. Churn Prediction using Structured Logical Knowledge and Convolutional Neural Networks, Gridach Mourad*, High Institute of Technology - Agadir
6. Evolving Realistic 3D Facial Expressions using Interactive Genetic Algorithms, Meareg Hailemariam*, Hanson Robotics/Labs iCog
7. Amharic-English Speech Translation, Michael Woldeyohannis*, Addis Ababa University, Addis Ababa, Ethiopia; Million Meshesha, Addis Ababa University; Laurent Besacier, LIG, Univ. Grenoble Alpes
8. Machine Learning Approach On Detection of Privilege Escalation Attacks in Android Smartphones, Bruno Ssekiwere*, Uganda Technology and Management University
9. A signature-based Denial of Service and Probe detector model based on data mining techniques, Claire Babirye*, Uganda Technology and Management University; Ernest Mwebaze, Uganda Technology and Management University
10. Modelling Virtual Enterprises Using a Multi-Agent Systems Approach, George Musumba*, Dedan Kimathi University of Technology
11. Behavioural Multi-Factor Authentication Using Keystroke Dynamics, Roy Henha Eyono*, University of Cape Town
12. Feature Extraction and Selection of Optical Galaxy Data, Roy Henha Eyono*, University of Cape Town
13. Compressive Sampling for Phenotype Classification, Eric Brooks*, Air Force
14. An iterative Dynamic Game Approach for Robust Deep Reinforcement Learning, Olalekan Ogunmolu*, University of Texas at Dallas; Nicholas Gans, UT Dallas; Tyler Summers, UT Dallas
15. Saving Newborn Lives at Birth through Machine Learning, Charles Onu*, McGill University
16. Predicting Road Traffic Accident Severity: A Small Case Study in South Africa, Mpho Mokoatle*, CSIR; Vukosi Marivate, CSIR
17. ShapeSearch: a generic search engine for 3D models, images and sketches, Flora Ponjou Tasse*, University of Cambridge
18. ZCal: Machine learning for calibrating radio interferometric data., Simphiwe Zitha*, Rhodes university & SKA-SA
19. A translation-based approach to the learning of the morphology of an under-resourced language, Tewodros Gebreselassie*, Addis Ababa University; Michael Gasser, Indiana University
20. Snake: a Stochastic Proximal Gradient Algorithm for Regularized Problems over Large Graphs, Adil SALIM*, Telecom ParisTech; Pascal BIANCHI, Telecom ParisTech; Walid HACHEM, Université Paris-Est Marne-la-Vallee
21. Orthographic Representation Learning for Modeling Dyslexia, HENRY WOLF VII*, University of Connecticut
22. Enhanced Robustness in Speech Emotion Recognition: using Acoustic and Linguistic Features, hana tisasu*, iCog-Labs
23. Semi-Supervised Learning in Brain Imaging Data for Classification of Schizophrenia, Tewodros Dagnew*, Università degli studi di milano
24. Language Guided Pixel-Space Planning, Emmanuel Kahembwe*, Edinburgh University
25. The UMD Neural Machine Translation Systemsat WMT17 Bandit Learning Task, kiante brantley*, The University of Maryland College Park
26. FPGA-Based CNN Processor Utilizing Parallel Feature Processing And Pseudo Parallel Memories, Muluken Hailesellasie*, Tennessee Tech.
27. Weakly Supervised Classification in High Energy Physics, Lucio Dery*, Stanford University
28. Prediction of neuropsychiatric conditions through switch detection in fluency tasks, Felipe Paula*, Federal University of Rio Grande do Sul - UFRGS; Rodrigo Wilkens, Université Catholique de Louvain - CENTAL; Marco Idiart, Federal University of Rio Grande do Sul - UFRGS; Aline Villavicencio, Federal University of Rio Grande do Sul - UFRGS
29. DETECTION OF ULCERS FROM CAPSULE ENDOSCOPIC IMAGES USING CONVOLUTIONAL NEURAL NETWORKS, Isa Nuruddeen*, Makerere University Uganda
30. Intelligent License Plate Recognition and Reporting, Yaecob Girmay Gezahegn, Addis Ababa University; Misgina Tsighe Hagos*, Ethiopian Biotechnology Institute; Dereje H.Mariam W.Gebreal, Addis Ababa University; Teklay GebreSlassie Zeferu, Addis Ababa University; G.agziabher Ngusse G.Tekle, Addis Ababa University; Yakob Kiros T.Haimanot, Mekelle University
31. MODELLING CONTEXT FOR A DEEP RECURRENT NEURAL NETWORK LANGUAGE MODEL, Linda Khumalo*, University of the Witwatersrand
32. Convolutional Sequence to Sequence Learning, Yann Dauphin*, Facebook
33. Integrating Attention Model into Hierarchical Recurrent Encoder-Decoder to Improve Dialogue Response Generation, Oluwatobi Olabiyi*, Capital One; Erik Mueller, Capital One
34. Advantages of Deep Learning Techniques on Grayscale Radiographs, Obioma Pelka*, University of Applied Sciences and Arts Dortmund
35. Hybrid Intelligent System for Lung Cancer Type Identification, yenatfanta Bayleyegn*, Ethiopian Biotechnology Institute; Kumudha Raimond, Karunya University
36. Towards impactful artificial intelligence on the African continent, Bonolo Mathibela*, IBM Research
37. Soft-biometrics Attributes Multi-Label Classification with Deep Residual Networks, Esube Bekele*, US Naval Research Lab; Wallace Lawson, Naval Research Laboratory
38. Learning an Interactive Attention Policy for Neural Machine Translation, Samee Ibraheem*, UC Berkeley
39. Ubiquitous Monitoring of Abnormal Respiratory Sounds, Justice Amoh*, Dartmouth College
40. Question Arbitration for Robot Task Learning, Kalesha Bullard*, Georgia Institute of Technology
41. Cluster-based Approach to Improve Affect Recognition from Passively Sensed Data, Mawulolo Ameko*, University of Virginia
42. Gaze and Voice as an Input Tool for Software Interfaces, Timothy Mwiti*, NORTHWESTERN UNIVERSITY
43. Transferring Agent Behaviors from Videos via Motion GANs, Ashley Edwards*, Georgia Institute of Technology; Charles Isbell, Georgia Institute of Technology
44. TopicRNN: A Recurrent Neural Network With Long-Range Semantic Dependency, Adji Bousso Dieng*, Columbia University
45. Probabilistic Multi-view based Diagnosis and Anomaly Detection of Sensors in Weather Station, Tadesse Zemicheal*, Oregon State University
46. Reinforcement Learning-based Simultaneous Translation with Final Verb Prediction, Alvin Grissom II*, Ursinus College
47. Towards a real-time in-seat activity tracker, Austin Little*, Georgia Institute of Technology
48. Robust Visual 6D Pose Tracking Using Learned Dense Data Association, Lanke Frank Tarimo Fu*, Independent Researcher (Formerly ETH Zurich)
49. An Ensemble-based Approach to Click-Through Rate Prediction for Promoted Listings at Etsy, Devin Guillory*, Etsy
50. Fluorescence Bioimaging of Organellar Network Evolution, Chinasa Okolo*, Pomona College
51. Intersectional Phenotypic and Demographic Evaluation of Gender Classification, Joy Buolamwini*, MIT
52. Generalizable Intention Prediction of Human Drivers at Intersections, Derek Phillips*, Stanford University
53. Application for Travel Grant, Samuel Fufa*, NA
54. Gender classification using facial components, Mayibongwe Bayana*, University of Kwazulu Natal
55. Noisy Expectation-Maximization: Applications and Generalizations, Osonde Osoba*, RAND Corporation
56. SEGCloud: Semantic Segmentation of 3D Point Clouds, Lyne Tchapmi*, Stanford University; Christopher Choy, Stanford University; Iro Armeni, Stanford University; JunYoung Gwak, Stanford University; Silvio Savarese, Stanford University
57. The Promise and Peril of Human Evaluation for Model Interpretability, Bernease Herman*, University of Washington
58. Adversarial Functionality-Preserving Training in the Malware Domain, Ousmane Dia*, ElementAI
59. Synchronized Video and Motion Capture Dataset and Quantitative Evaluation of Vision Based Skeleton Tracking Methods for Robotic Action Imitation, selamawet atnafu*, Bahirdar University
60. Constrained Dominant Sets with Applications in Computer Vision, Alemu Leulseged*, Ca’ Foscari University of Venice
61. Generalization Properties of Adaptive Gradient Methods in Machine Learning, Ashia Wilson*, UC Berkeley
62. Nods and Daps: Encouraging Gesture, Movement Rhythm & Motion that honors the black experience and in the creation of Data Sets that drive AI, Micah Morgan*, African American Art and Culture Complex
63. Collecting Data in VR For Generating Natural Language Descriptions of 3D Space, Danielle Olson*, MIT
64. AWE-CM Vectors: Augmenting Word Embeddings with a Clinical Metathesaurus, Mohamed Kane-Hassan
65. Convolutional Neural Networks for Breast Cancer Screening: Transfer Learning with Exponential Decay, Hiba CHOUGRAD
66. A comparison of the conditional inference survival forest model to random survival forests based on a simulation study as well on two applications with time-to-event data, Justine Nasajje
67. Automated detection of Malaria Parasites using CNN via Smartphones, Sanni Oluwatoyin Yetunde
68. Using Machine Learning to Detect Potential Child Suicide Bombers, Cisca Oladipo
69. Reducing Students Dropout Rate - A machine Learning Approach, Neema Mduma
70. Generating Natural Language Descriptions of Virtual Reality (VR) Spaces, Danielle Olson
71. Social Attention for Part-of-Speech Tagging, Taha Merghani
72. Automatic Radio Galaxy Classification using Deep Convolutional Neural Networks, Wathela Alhassan, University of Cape Town; R. Taylor, University of Cape Town, University of the Western Cape; Mattia Vaccari, University of the Western Cape
73. Dynamic Modelling of Cybercriminals Behaviour by Deep Neural Networks, Abiodun Modupe*
74. Big data clustering with the use of the random projection features reduction and collaborative Fuzzy C-Means, Dang Trong Hop, Hanoi University of Industry; Pham The Long, Le Quy Don Technical University; Ngo Thanh Long, Le Quy Don Technical University; Fadugba Jeremiah, FPT University
75. Orchestra Mobile Crowdsensing and Computing Platform: A Roadmap for Further Development, Sando George, Warsaw University of Technology; Maria Ganzha, Warsaw University of Technology; Marcin Paprzycki, Polish Academy of Sciences
76. An empirical experimental survey of application of Wilson’s edited Nearest Neighbour as a sampling and data reduction scheme to alleviate class imbalance problem, S. O. Folorunso, Olabisi Onabanjo University; A. B. Adeyemo, University of Ibadan
77. Luganda Text-to-Speech Machine, Irene Nandutu, Uganda Technology and Management University; Ernest Mwebaze, Makerere University

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2017 Workshop Co-Chairs

• Rediet Abebe, Cornell University
• Sarah M. Brown, University of California, Berkeley
• Mouhamadou Moustapha Cisse, Facebook AI Research
• Timnit Gebru, Microsoft Research
• Sanmi Koyejo, University of Illinois, Urbana-Champaign
• Lyne P. Tchapmi, Stanford University

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2017 Program Committee

‍Thanks to the following members of the Black in AI community and supportive allies for helping review the submissions.

• Rediet Abebe
• Justice Amoh
• Silèye Ba
• Irwan Bello
• Samy Bengio
• Sarah M. Brown
• Joy Buolamwini
• Diana Cai
• Moustapha Cisse
• Charles Cearl
• Tewodros Dagnew
• Hal Daumé III
• Ousmane Dia
• Ashley Edwards
• Oluwaseun Francis Egbelowo
• Dylan Foster
• Fisseha Gidey Gebremedhin
• Timnit Gebru
• Christan Grant
• Alvin Grissom II
• Bernease Herman
• Jack Hessel
• Abigail Jacobs
• Emmanuel Johnson
• Sanmi Koyejo
• Ciira Maina
• Nyalleng moorosi
• George Musumba
• Ndapa Nakashole
• Ehi Nosakhare
• Billy Okal
• Charles Onu
• Forough Poursabzi-Sangdeh
• Alexandra Schofield
• Frank Lanke Fu Tarimo
• Lyne P. Tchapmi
• Kale-ab Tessera
• Basiliyos Tilahun BETRU
• Wil Thomason
• Marcelo Worsley

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