Logistics conference

Logistics conference

First edition: covering fleet management and mobility

##About Logistics conference:

Logistics is evolving as a domain that requires understanding of:

  1. The landscape (literally), and interesting problems to solve -- be they supply-chain management, warehousing, transportation, delivery of goods and services or fleet management.
  2. Complexities in current technology and processes for collecting, managing and updating geo-spatial data.
  3. Areas of collaboration and cooperation between industry, startups and government -- including municipalities, urban planning and infrastructure.

The first edition of Logistics conference will cover fleet management and shared mobility.

##Dates and venue:

The Fifth Elephant presents the first edition of logistics conference on 24 November, at the NIMHANS Convention Centre, Bangalore.

#Topics for the conference:
We are inviting talks on the following topics:

  1. Product development for fleet management.
  2. Operational challenges with respect to fleet management.
  3. Solutions for on demand availability of vehicles to participate in a ridesharing networks.
  4. Data science for fleet management.
  5. Engineering for fleet management
  6. “Shared mobility” -- how various players in the mobility space, including cab aggregators, car pooling, metros, buses, shuttles, etc can come together to complement each other rather than compete.
  7. Thinking through and solving challenges with sparsity of data for spatio-temporal granularity
  8. India-specific challenges in traffic management and congestion.
  9. India-specific challenges with respect to address standardisation.
  10. AI-based solutions in transportation space.

##Target audience:

  1. Product managers
  2. Division and business heads
  3. Data scientists
  4. Senior engineers
  5. Technical leads
  6. VPs of engineering
  7. Representatives from municipalities, urban planning and transportation departments
  8. Geo-spatial data experts
  9. CEOs and founders of startups working in the space of logistics, fleet management, e-commerce and retail, and mobility
  10. Technology heads and VPs of companies operating in logistics space

Logistics conference is a single-day, single-track event with talks, panel discussions and Birds of Feather (BOF) sessions. We are accepting proposals for the following formats:

  1. Full talks of 30 minutes.
  2. Crisp talks of 15 minutes.
  3. BOF sessions on focussed topics / questions. A BOF session is 60-90 minutes long, and typically has up to two-four facilitators.

##Selection criteria:

The criteria for selecting proposals, in the order of importance, are:

  1. Key insight or takeaway: what can you share with participants that will help them in understanding the domain better.
  2. Structure of the talk and flow of content: a detailed outline – either as mindmap or draft slides or textual description – will help us understand the focus of the talk, and the clarity of your thought process.
  3. Ability to communicate succinctly, and how you engage with the audience. You must submit link to a two-minute preview video explaining what your talk is about, and what is the key takeaway for the audience.

No one submits the perfect proposal in the first instance. We therefore encourage you to:

  1. Submit your proposal early so that we have more time to iterate if the proposal has potential.
  2. Write to us on fifthelephant.editorial@hasgeek.com if you want to discuss an idea for your proposal, and need help / advice on how to structure it.

Our editorial team helps potential speakers in honing their speaking skills, fine tuning and rehearsing content at least twice - before the main conference - and sharpening the focus of talks.

##How to submit a proposal (and increase your chances of getting selected):

The following guidelines will help you in submitting a proposal:

  1. Focus on why, not how. Explain to participants why you made a business or engineering decision, or why you chose a particular approach to solving your problem.
  2. The journey is more important than the solution you may want to explain. We are interested in the journey, not the outcome alone. Share as much detail as possible about how you solved the problem. Glossing over details does not help participants grasp real insights.
  3. Focus on what participants from other domains can learn/abstract from your journey / solution.
  4. We do not accept how-to talks unless they demonstrate latest technology. If you are demonstrating new tech, show enough to motivate participants to explore the technology later.
  5. Similarly, we don’t accept talks on topics that have already been covered in the previous editions. If you are unsure about whether your proposal falls in this category, drop an email to: fifthelephant.editorial@hasgeek.com
  6. Content that can be read off the internet does not interest us. Our participants are keen to listen to use cases and experience stories that will help them in their practice.

To summarize, we do not accept talks that gloss over details or try to deliver high-level knowledge without covering depth. Talks have to be backed with real insights and experiences for the content to be useful to participants.

##Passes for speakers:
Confirmed speakers receive a pass to the conference. We do not provide free passes for speakers’ colleagues and spouses. Please do not ask us for these.

##Travel grants for outstation speakers:
Travel grants are available for international and domestic speakers. We evaluate each case on its merits, giving preference to women, people of non-binary gender, and Africans. If you require a grant, request it when you submit your proposal in the field where you add your location.
Logistics conference is funded through ticket purchases and sponsorships; travel grant budgets vary.

##Last date for submitting proposals is: 20 September 2018
You must submit the following details along with your proposal, or within 10 days of submission:

  1. Draft slides, mind map or a textual description detailing the structure and content of your talk.
  2. Link to a self-recorded, two-minute preview video, where you explain what your talk is about, and the key takeaways for participants. This preview video helps conference editors understand the lucidity of your thoughts and how invested you are in presenting insights beyond the solution you have built, or your use case. Please note that the preview video should be submitted irrespective of whether you have spoken at HasGeek conferences in the past.

##Contact details:
For more information about the conference, sponsorships, or any other information contact info@hasgeek.com or call 7676332020.

Hosted by

All about data science and machine learning

Divya Choudhary


From an archived data field to GOJEK’s world class product feature for customer-experience

Submitted Sep 21, 2018

This talk will focus on details of how machine learning & natural language processing was used on customer notes data along with bookings data by our team at GOJEK to come up with a product feature enabling customers to see all pickup gates near him/her with their appropriate names that they can understand & choose from while booking a car or ride service.

Like any other service company, customer experience while booking a service is of prime importance at GOJEK, a technology startup based in Jakarta, Indonesia that specialises in ride/car hailing along with 17+ other services. With immense data influx in the system from more than 18 services, the data field that have been archived earlier turned out to be the best data that improved how customers book rides/car on GOJEK app. If you want to understand through examples, the untapped value your data can add to your product through curated machine learning and natural language processing, no use case can better explain it than this.

Divya Choudhary, the speaker will speak in detail about this use case- problem statement, solution outline, data processing, major algorithmic decisions/learnings & final output feature. The presentation will highlight on how the product feature was built, focussing majorly on two algorithmic piece that constituted the problem solution:

  • Machine learning clustering technique
  • DBSCAN vs K-means, how to know when to use what
  • Wonders of Language modeling
  • Pre-processing of corpus is the key
  • Great potential of N-gram modeling

Key takeaway from the talk:

  • understanding the importance of correct machine learning algorithm on data in driving business to an unimaginable higher level
  • understanding that no data is waste - all you need is correct algorithm to best utilize it
  • understanding of building an excellent product feature using textual & geospatial data
  • the talk will be focussed on how this product feature that’s live now was practically built using machine learning and NLP
  • understanding of impact that a data solution like this can bring to the logistics service with a live example of metrics being upscaled by this at GOJEK
  • understanding of possible use cases of application of similar solution is different other scenarios across logistics industry
  • greater understanding of clustering geo spatial data
  • understanding of an amazing use case of n-gram language model


Who would have imagined that a random chat message or note written in a local language sent by customers to their drivers while waiting for a ride/car to arrive for their pickup can be utilized to carve out unparalleled information about pickup points, their names that sometimes even Google map has no idea of & to finally help in creating a world class customer pick-up experience feature!

Speaker bio

A computer science engineer turned decision scientist turned data scientist. I have an experience of ~4 years.

Having worked closely with the board of directors of 3 startups in India & Indonesia, I am known for my business understanding, problem solving approach and obviously driving data science problems to the final execution.

a yoga lover, a poetess, a painter, a avid trekker & wanderer who is best at talking to people and learning about them




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Hosted by

All about data science and machine learning