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Overview
Currently I'm Tech Lead on AI Safety (Principal / Director level) in Google K&I (Search and Ads) org at Google from June 23rd, 2025 - present
Overview
Currently I'm Tech Lead on AI Safety (Principal / Director level) in Google K&I (Search and Ads) org at Google from June 23rd, 2025 - present
Before this, I was Senior Principal Scientist (Director level) at the Artificial General Intelligence (AGI) organization in Amazon. I worked in Amazon from October 2020 - May 2025, starting out as Principal Research Scientist in the Alexa organization and ending my tenure there as Senior Principal Scientist in the AGI organization.
Till August 2020, I was a Principal Scientist (Director) and the Leader of the Machine Learning Research team at the Smart TV division of Visual Display Intelligence Lab in Samsung Research America. Before this, from May 2018 - July 2019, I also served as the Director of AI Research in the Artificial Intelligence center in Samsung Research America in Mountain View, reporting to Dr. Larry Heck.
Before May 2018, I was a Principal Computer Scientist in the Computer Science Laboratory at SRI in Menlo Park, reporting to Dr. Patrick Lincoln.
I completed my PhD in 2005 at the Computer Engineering Research Center in ECE at the University of Texas at Austin. I worked with Prof. Nur Touba in the Computer Aided Testing (CAT) Laboratory. Previously, I did my MS from the Computer Engineering Department of University of California at Santa Cruz (UCSC). At UCSC, I worked with the Semiconductor Test Group. My MS Thesis advisor was Prof. F. Joel Ferguson.
In my undergraduate studies, I majored in Physics (Honors) from St. Xavier's College, University of Calcutta -- I minored in Mathematics and Chemistry.
I was invited to be a Visiting Scientist at Google Research in Mountain View, as part of the Google Visiting Faculty Program, for more than 1 year (July 2014 to August 2015). I worked on applying deep learning (Google Brain) models to problems in natural language understanding.
My contact email address is: "shalini DOT ghosh AT gmail DOT com"
Research Interests
Research Interests
I have worked on applying machine learning models to different domains. I am specifically interested in:
LLM Foundation models and LLM Safety and Agents
Multi-modal learning (e.g., joint learning from speech, language, image, vision modalities)
Natural language applications (e.g., language models, paraphrase generation, machine reading)
Dependable computing (e.g., cyber security, fault tolerance)
Information Theory applications (e.g., error correcting codes)
Selected Awards and Honors
Selected Awards and Honors
Invited to serve on the prestigious DARPA ISAT panel on LLMs in 2023, which advises US govt. on emerging technology.
Interview on multimodal AI was featured on the list of Women in AI and Engineering: Pioneer Podcasts of ReWork 2020.
Paper on Video Content Analysis selected for Merit Award in Samsung Best Paper Award 2020 (awarded globally within Samsung for research with maximal innovation and impact) -- within the top 4.6% of all submitted papers and within top 3 in the Multimedia track.
Invited to be an Applied Data Science Invited Speaker at KDD 2020.
Selected as one of the “Top 5 AI talks” of ReWork 2020.
Selected as one of the “30 Influential Women Advancing AI in 2019” by ReWork.
Invited to serve on the prestigious ISAT panel in 2020, which advises US government and DARPA on emerging technologies.
Best Paper Award at The 19th IEEE Pacific Rim International Symposium on Dependable Computing (PRDC) 2013.
SRI PoP (Period of Performance) Award in 3 successive years for outstanding performance: 2011, 2012, 2013.
SRI Spot Award 2013 for outstanding leadership and design innovation in the ARSENAL project.
SRI Spot Award 2012 for outstanding contribution to the ARSENAL project.
Best Student Paper Runner-up Award at GLS-VLSI 2004.
All-India Second Prize for undergraduate dissertation on radioisotopes in the Annual Contest of Atomic Energy Commission, Govt. of India, at the Bhabha Atomic Research Centre in Bombay, 1996; All India First prize for the written part of the contest.
Selected Talks and Interviews (recent)
Selected Talks and Interviews (recent)
Invited to present a tutorial on Resource-efficient and Cross-Modal Learning Towards Foundation Models at InterSpeech 2023.
Invited to give Keynote talk on “Speech Recognition in the Age of LLM” at the Amazon Science and Technology Summit (along with Bjorn Hoffmeister and Ariya Rastrow) at San Francisco in May, 2023.
Invited talk "Pre-Training and Multi-Modal Training" at the ICASSP 2022 Workshop "The new era of all-neural SLU: opportunities and challenges ahead": link. Was also one of the core panel discussion members.
Invited talk at Applied Data Science track, KDD 2020: video
Invited Talk at SRI 2020
Invited talk at ReWork 2020 Deep Learning Summit: video
Interview with ReWork, Jan 2020: video
Interview with ReWork Women in AI, Jan 2019: video
Invited talk on Conversational Vision at Deep Learning session of ReWork, Jan 2017: video
Invited talk on Contextual LSTMs at AI2, in Sep 2015: video
Invited talks at various universities, e.g., UC Berkeley (2014, 2019), Stanford University (2019)
Invited talks at various industrial labs, e.g., Google, Yahoo, LinkedIn, Nuance in 2018-2019
Professional Services / Recognition/ Affiliations
Professional Services / Recognition/ Affiliations
Area Chair: NeurIPS 2022-2026, ICLR 2021-ICLR 2022, ICML 2020-2026.
Session Chair: Session Chair for ICLR 2021, IJCAI 2019, KDD 2017.
Workshop Organizer: KDD 2026 (1st Workshop on AI for Fraud and Abuse (AI-FA 2026))
Program Committee member: NIPS (Neural Information Processing Systems) 2020, 2019, 2018, 2017, 2016 [PC Member/Reviewer]; KDD (ACM SIGKDD Conference on Knowledge Discovery and Data Mining) 2017, 2016, 2015 and 2014; ICML (International Conference on Machine Learning) 2020, 2019, 2018, 2017, 2016; SDM (SIAM International Conference on Data Mining) 2013; AISTATS (Artificial Intelligence and Statistics Conference) 2019 (refused), 2017; NAACL (North American Association of Computational Linguistics) 2012; IJCAI (International Joint Conference on AI) in 2020, 2019; NFM (NASA Formal Methods) 2016, 2014; VALID 2013, 2014, ACML (Asian Conference on Machine Learning) 2012. Invited to be on PC of Association for the Advancement of Artificial Intelligence (AAAI) in 2019, 2017, 2013 and 2014 PhD Symposium on Formal Methods and Analysis.
Reviewer for leading journals/conferences: ACM/IEEE Symposium on Logic in Computer Science (LICS) 2016, ACM Transactions on Reconfigurable Technology and Systems (TRETS), Journal of Electronic Testing Theory and Applications (JETTA), IEEE Transactions on Very Large Scale Integration Systems (TVLSI), IEEE Transactions on Computer, IET Circuits, Devices and Systems, Journal of Low Power Electronics (JOLPE), Elsevier Journal on Signal Processing (SIGPRO), Network & Distributed System Security Symposium (NDSS), Turing Centenary Conference in 2012, Information Processing Letters (IPL) 2016.
PhD Committee member: Tivadar Papai, University of Rochester (PhD Advisor: Prof. Henry Kautz)
Invited guest lecturer in EECS course at UC Berkeley: Gave lecture on ARSENAL at the EECS Department of the Universiy of California at Berkeley in February 2014. Course: EECS 294-98 (Formal Methods for Engineering Education).
Invited to write a blog article at ReWork on the state-of-the-art research in multimodal machine learning.
Member of Women In Machine Learning Program (affiliated to ICML), 2011.
Member of ACL (Association for Computational Linguistics), SIGKDD (ACM Special Interest Group on Knowledge Discovery and Data Mining), IEEE, Women in Engineering Program at UT Austin (2000 to 2005).
Invited panelist for various panels, e.g., AAAI-AICS in 2018, National Science Foundation panel for Emerging Technologies in 2008, VSLI Test Symposium panel at Berkeley in 2013.
Invited to give a keynote talk on ARSENAL at DATE 2017 in DUHDe, the Workshop on Design Automation for Understanding Hardware Designs (declined).
Invited talks at several leading research institutes (e.g., NASA) and universities (e.g., UC Berkeley in 2014 and 2019, Stanford University in 2019).
Invited to present whitepaper at IARPA Workshop on applying Natural language procesing for Automated International Law Compliance Monitoring in May, 2012.
Invited attendee at the BAST workshop at Bodega Bay, organized jointly by the Stanford Center for Reliable Computing and the IEEE Test Technology Committee, in 2000 and 2006.
Organized and led study groups and seminar series on (1) Statistics and Probabilistic Reasoning at CSL in SRI, 2007 to 2010, (2) Emerging technologies, 2005-2007.
Internship Research during PhD
Internship Research during PhD
Test Group of Synopsys Inc., Sunnyvale, CA in Summer 2004 (Project Advisor: Dr. Rohit Kapur, Manager: Adam Cron): Worked on state-of-the-art scan compression method, launched as the Adaptive Scan technology.
Microprocessor Validation group of Intel Corporation, Austin, TX in Summer 2001 (Manager: Dr. Neeta Ganguly): Worked with Microprocessor Validation tools for functional testing.
Design and Test Group of Intel Corporation, Santa Clara, CA in Summer 1999 (Manager: Dr. Sreejit Chakravarty): Added pattern-dependant bridge behavior modeling to Intel's internal fault simulator software.
Old News (before joining Amazon in October 2020)
Old News (before joining Amazon in October 2020)
October 2020: I joined Amazon Science (Alexa AGI team) on as Principal Research Scientist.
October 2020: Gave an oral presentation in ACM Multimedia 2020 on our multimodal video processing paper
September 2020: Our paper was selected for Merit Award in Samsung Best Paper Award for 2020 -- within the top 4.6% of all submitted papers and within top 3 in the Multimedia track.
September 2020: Gave invited talk in Computer Science Lab at SRI.
August 2020: Gave an Invited Talk at KDD 2020 (Applied Data Science track): video.
July 2020: Our latest paper on multimodal AI got accepted at the ACM Multimedia 2020 conference as an Oral Paper.
June 2020: My interview on multimodal AI was featured on the list of Women in AI and Engineering: Pioneer Podcasts of ReWork 2020.
June 2020: Paper on Video Content Analysis has been short-listed for Samsung Best Paper Award 2020, awarded globally within Samsung for research with maximal innovation and impact (final selection of winner is pending).
May 2020: An article on 13 must-read AI papers that includes an interview with me was published by ReWork.
April 2020: Invited to be an Applied Data Science Invited Speaker at KDD 2020.
March 2020: My talk got selected as one the Top 5 AI talks in ReWork 2020.
January 2020: Interview with ReWork on multi-modal video processing went live (video).
January 2020: Gave invited talk in the Deep Learning Summit and interview at ReWork 2020 (full interview video can be viewed here).
December 2019: I got selected as one of the 30 Influential Women Advancing AI in 2019.
December 2019: My contribution to ReWork's AI Experts Predict 2020 Trends got published.
October 2019: My blog article on multi-modal AI got published.
March 2019: My interview on Deep Learning for Incremental Object Detection and Visual Dialog went live.
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