Maitreyee 2024
- Gurgaon & Bangalore, India and virtual
About
Maitreyee is IBM Research Labs (IRL) - India's annual diversity and inclusion student outreach event with a mission to enable computer science researchers from academia and industry to collaborate, learn, and network with each other. Every year, IBM Research India Labs organizes an event to promote diversity and inclusion in the computing and technology community. This unique initiative aims to bring together the brightest in technology, including students, researchers, faculty members, industry speakers, domain experts for an active exchange of thoughts and ideas. It also provides a platform for students to present their ongoing research as well as interact with IBM researchers on how they can successfully grow their technical careers.
Important Dates
Registration deadline: September 10, 2024Research showcase submission deadline: September 10, 2024Research showcase notification of selection: September 16, 2024- Date of event: September 21, 2024
Research Showcase
Maitreyee 2024 event invites submission of vlogs/elevator pitch from diversity students in technology willing to showcase their knowledge. The content should be on technical topics pertaining to Artificial Intelligence, Big Data, Quantum Computing, Cloud and/or Climate and Sustainability. Out of all the submissions, top 3 vlogs will be selected for a short presentation during Maitreyee by the author themselves.
Submission Guidelines
Submission must be original and an outcome of author’s own efforts.
- A max 3 minutes video
- Submission should be on technical topics related but not limited to:
- Neurosymbolic AI Applications
- Trusted Data and AI
- Data Readiness for AI
- AI Model Testing
- Quantum Applications
- Reliable Hybrid Cloud
- Conversational AI
- AI4Code
- Climate and Sustainability
- Security and Cryptography
- The goal of the submission is to talk about at least one of the following as an author:
- Own research work
- A tool developed
- Short how-to-tutorial on a technology
- Author can use any online forum to publish their vlogs that are publicly accessible (e.g., Google Drive,LinkedIn, Youtube, GitHub, etc.).
- Add to a file
- the vlog link
- This file should be uploaded as a paper to Easychair. For any further queries please reach out at: maitreyee1@ibm.com
Submission Link
- Each author can submit ONLY one Vlog link using Easychair based on their area (Login to Easychair to create the submission).
- Hybrid Cloud: ibm.biz/maitreyee-2024-hc
- AI: ibm.biz/maitreyee-2024-ai
- Other (Quantum, Sustainability, Security): ibm.biz/maitreyee-2024-others
Perks
- Selected Top entries will get a chance to present their vlog during Maitreyee event and receive a prize.
Why attend
- Hear from distinguished figures in both industry and academia.
- Present your work at IBM Research.
- Participate in in-person mentoring sessions with IBM researchers.
- Learn about potential research internship opportunities.
- Win exciting prizes.
Speakers
Amith Singhee
Agenda
- ASAmith SingheeDirector IBM Research India and CTO, IBM India and South AsiaIBM Research
Panelists
- Dr. Aruna Rajan - Director of machine learning and product management, Google.
- Saritha Route, IBM Distinguished Engineer, Automation Innovation Center Leader and Global Test Automation Program Leader
- Prof. Rijurekha Sen, Assistant Professor, IIT Delhi
Moderator
- Dr. Pratibha Moogi, IBM Research India
- AIDE-W: AI for Deepfake Detection and Empowerment of Women - Surbhi Raj, IIT Patna
- Application of Subset Selection in Efficient Machine Learning - Kiran Purohit, IIT Kharagpur
- Advancing Quantum Machine Learning - Sejal Sarada, BITS Pilani
- BlueDoS: A Novel Approach to Perform and Analyse DoS Attacks on Bluetooth Devices - Poonam Shelke, IIT Guwahati
- AI4Code: Topic: Application of AI to understand and transform legacy code by Srikanth Tamilselvam
- Reliable Hybrid Cloud : Topic: Enabling Intelligent Volume Reduction for Observability Data by Priyanka Naik
- Quantum: Topic: Nano-fab of Superconducting Chip by Richa Goel
- Conversational AI: Topic: End to end reinforcement learning framework for conversation disentanglement by Karan Bhukar