Key takeaways
- Empower women in data science through inclusive events like Intuit's Women in Data Science conference.
- Connect over 130 professionals from diverse fields to foster innovation and collaboration in data science.
- Highlight practical applications of Secure Multi-Party Computation in keynote address by Arpita Patra.
- Promote global diversity and inclusivity initiatives initiated by Stanford University through WiDS.
- Encourage future data scientists with workshops, presentations, and resources available through the WiDS movement.
Intuit, the global financial technology platform behind Intuit TurboTax, Credit Karma, QuickBooks, and Mailchimp, recently concluded the Women in Data Science (WiDS) conference held at their Bangalore office on June 27.
The event brought together over 130 data science professionals from academia, startups, GCCs, and IT services. The insightful sessions featuring a variety of speakers, including leading data science experts, left the attendees feeling empowered and inspired.
The event was dedicated to empowering women and fostering innovation in data science. WiDS, initiated by Stanford University, began as a one-day conference and has grown into a global data science movement promoting diversity and inclusivity. It features conferences, workshops, presentations of papers, podcasts, and programs for future data scientists, reaching over 100,000 professionals annually.
The conference kicked off with a welcome note by Anusha Mujumdar, an AI leader at Intuit, setting the stage for a day filled with insightful presentations and hands-on learning experiences.
Keynote: The Journey of Secure Multi-Party Computation
The keynote address, delivered by Arpita Patra, associate professor at the Indian Institute of Science, focused on the practical applications of Secure Multi-Party Computation (MPC).
Titled ‘From theory to practice: The marvellous journey of mighty MPC’, Patra's talk explored how this cryptographic protocol has evolved from a theoretical concept to a powerful tool in real-world scenarios. It enables multiple parties to jointly compute functions over their inputs while keeping those inputs private.
Tech Talks: Advancing Voice Assistants and Algorithmic Optimisation
Neela Sawant, senior applied scientist at Amazon, presented a tech talk on improving in-car voice assistants for better navigation. This presentation delved into the challenges and solutions in enhancing Automatic Speech Recognition (ASR) and natural language processing technologies specifically for automotive applications.
Later in the day, Koyel Mukherjee, senior research scientist at Adobe Research, discussed ‘Optimising costs, quality and performance – one algorithm at a time’. She explored the techniques for balancing these crucial factors in algorithm development and deployment across various data science applications.
Hands-On Workshop by Intuit
A key highlight of the conference was the hands-on workshop led by Damitri Kundu, Senior AI/ML Scientist at Intuit, and Sravyasri Garapati, Senior Machine Learning Engineer at Intuit.
The workshop, ‘Mastering the art of automated prompt optimisation in language models’, provided participants with practical skills in fine-tuning prompts for large language models, an increasingly important skill in the era of generative AI.
Paper Presentations: Emerging Research in Data Science
The conference also featured several papers by students and professionals, showcasing emerging research in the field.
- Niharika Joshi from BMS College of Engineering presented the paper titled ‘Tackling data challenges in energy domain: Synthetic data is the answer’, addressing the use of artificially generated data to overcome the limitations in real-world energy sector datasets.
- Harini Anand, a senior at PES University, discussed ‘Bitcoin price prediction using LSTM and VADER sentiment analysis’, combining advanced time-series analysis with natural language processing techniques to forecast cryptocurrency trends.
- Yashaswini Viswanath, senior specialist in data sciences at Mindtree, explored ‘Machine unlearning for generative AI’, a topic that addressed the challenges of selectively removing information from trained AI models.
- Sanjana Adapala from BITS Pilani, Hyderabad, presented on ‘Lighting estimation in virtual environments using generative models’, showcasing applications of AI in computer graphics and virtual reality.
The WiDS conference in Bangalore provided a platform for knowledge sharing, networking, and inspiration, highlighting the significant contributions of women in the rapidly evolving field of data science.
By bringing together experts from academia and industry, the event fostered collaboration and encouraged the next generation of data scientists to push the boundaries of innovation.
Watch out for the next edition of the Women in Data Science Conference at Intuit in India, where industry pioneers share cutting-edge knowledge, empowering you to thrive in a rapidly evolving landscape. Learn more at Intuit careers.
