**Stay tuned for more speakers!
Co-founder and CTO of IkigaiLabs
Devavrat Shah is a Professor with the department of Electrical Engineering and Computer Science at Massachusetts Institute of Technology. He is the founding director of Statistics and Data Science at MIT. He is also a member of IDSS, LIDS, CSAIL and ORC at MIT. He co-founded Celect, Inc. (now part of Nike) in 2013 to help retailers decide what to put where by accurately predicting demand using omni-channel data. He is a co-founder and CTO of IkigaiLabs with the mission to build self-driving organizations by enabling data-driven operations with human-in-the-loop.
He is interested in developing large-scale machine learning algorithms for unstructured data. He has made foundational contributions to the development of “gossip” protocols and “message-passing” algorithms for statistical inference which have been the building blocks of modern distributed data processing systems.
His work has received broad recognition, including prize paper awards in Machine Learning, Operations Research and Computer Science, and career prizes including 2010 Erlang prize from the INFORMS Applied Probability Society, awarded bi-annually to a young researcher who has made outstanding contributions to applied probability. He is a distinguished alumni of his alma mater IIT Bombay from where he graduated with the honor of President of India Gold Medal. His work has been covered in popular press including NY Times, Forbes, Wired and Reddit
Research Scientist, Google Brain
Amir Yazdanbakhsh is the founder and co-lead of the learn to design accelerator team at Google Research that targets to leverage advances in machine learning to design better accelerators. Amir joined Google Brain as a Research Scientist in 2019 following a one year AI residency. He obtained his PhD in Computer Science from the Georgia Institute of Technology. His research interests include machine learning, computer architecture and systems, and programming language for hardware design. He has received the Microsoft Research PhD Fellowship Award (2016) and Qualcomm Innovation Fellowship (2015).
Principal Data Scientist, Microsoft
Jonathan Apple joined Microsoft in early 2020 as a Data Scientist in the Azure Reliability organization. His work focuses on building scalable analytics solutions that “move the needle” in the realm of cloud reliability and platform risk management. Jonathan’s interests include distributed computing and developing insightful statistical models. His career has been focused on both research and development in Engineering (satellites, green energy, Industrial IoT, geospatial analytics), as well as building low-latency trading systems while working in FinTech. Jonathan has a B.S. and an M.S. in Physics from Drexel University and University of Pennsylvania (respectively) and is an avid chess player.
Resource Manager, VMware | Technology Contributor, Forbes Middle East | AI Expert, AI Policy Exchange
Tannya is a technology evangelist, A.I. Expert, and futurist. Through her work, Tannya encourages current and future leaders to explore the ethical and practical implications of exponential technologies on business, life and society at large. Tannya is an advocate of radical innovation, the rise of meaningful work in a post-automation world, and a proponent of educational reform.
She currently works as the Resource Manager at VMware, a leader in cloud infrastructure, is a technology contributor at Forbes Middle East, serves as an AI Expert at the AI Policy Exchange, is the co-leader of the Dubai Women in Tech Lean In Circle, and is the Head of Partnerships at Awecademy, a future-focused edtech startup whose mission is to bring a sense of awe and wonder to education and prepare learners for a post-automation world.
Sr. Manager and RAPIDS cuGraph Lead, NVIDIA
Brad Rees is a Sr. Manager in the AI Infrastructure group at NVIDIA and lead of the RAPIDS cuGraph team. Brad has been developing software for over 30 years and specializes in complex analytic systems, primarily using graph analytic techniques for social and cyber network analysis. His technical interests are in HPC, machine learning, deep learning, and graph. Brad holds a Ph.D. in Computer Science from the Florida Institute of Technology.
Research Scientist, Facebook Reality Labs Research
Zhaoyang Lv is a research scientist with the Facebook Reality Labs Research, Machine Perception team in Redmond, WA. Zhaoyang finished his Ph.D. at Georgia Tech, jointly advised by Prof. James Rehg, and Prof. Frank Dellaert. During his Ph.D., he interned at Nvidia Research under Jan Kautz and at Max Planck Institute with Prof. Andreas Geiger. Before Zhaoyang started his Ph.D., he finished his Master thesis under the supervision of Prof. Andrew Davison at the Imperial College London.
Zhaoyang’s research interest is to explore how we can photorealistically digitalize the complex dynamic world and render anything at anytime and anywhere, by rethinking the system end-to-end, from sensing and image formation system to the virtual rendered novel view video.
Research Scientist, Facebook AI Research (FAIR)
Ramakrishna Vedantam is a Research Scientist at Facebook AI Research (FAIR) in New York. Previously, he obtained his Ph.D. at the Georgia Institute of Technology (2018), an MS from Virginia Tech (2016) and did his undergraduate studies at IIIT, Hyderabad (2013). His research interest is in machine learning that mimics the capabilities of human learning and reasoning. He has been awarded the Google Ph.D. fellowship in Machine Perception and has received best reviewer awards at ICCV, CVPR, and ICLR.
Engineering Manager, NCR Software Innovation Lab
Brent Zucker serves as the Engineering Manager for the NCR Software Innovation Lab where he leads teams and projects that focus on disrupting banks, restaurants, and stores by developing concepts that leverage Machine Learning, Computer Vision, and Distributed Ledger Technology. Recently, he was awarded the NCR 2020 Co-inventor of the Year for patents he created. Brent holds a Master of Science in Computer Science from Georgia Institute of Technology and a Bachelor of Science in Computer Science from Georgia College.
Founder and CEO, Tilda Research
Ram Yalamanchili is the founder and CEO of Tilda Research, where he is focused on building data and operational infrastructure to better execute clinical trials. Prior to Tilda, he was a founder and CTO at Lexent Bio, which was acquired by Roche. Lexent built novel liquid biopsy technologies to help change the way we manage cancer. Prior to Lexent, he was the CEO/Founder of Push Computing, which pioneered predictive security and container technologies for mobile (acquired by MobileIron). Prior to that, he was an early engineer at VMware and helped architect the ESXi product. ESXi hypervisor powers a majority of the private cloud infrastructure today. Ram studied Electrical Engineering and Management Science at Carnegie Mellon and Stanford University respectively.