Project Set 1
project details-
Projects of Interest (choose all that interest you)

Understanding and Improving Contact Interfaces to Nanomaterials for Nanoelectronic Transistors
Faculty Advisor: Prof. Aaron Franklin
Nanomaterials offer considerable advantages over traditional bulk materials for next-generation electronic devices.  In particular, field-effect transistors (FETs) used for high-performance computing must be able to operate at low voltages and sub-20 nm dimensions.  Carbon nanotubes (CNTs), 2D transition metal dichalcogenides (TMDs), and graphene are among the most promising nanomaterials for implementation into FETs.  One of the foremost challenges for such nanoelectronic transistors is the prohibitively high contact resistance, which results from poorly understood/controlled electron injection at the metal contact-nanomaterial interface that ultimately limits voltage scaling.
In this project, the interface between the metal source/drain contacts to certain nanomaterials will be modified to improve carrier injection.  Using a custom materials deposition system that includes electron-beam evaporation (e-beam evap) and a broad beam ion source, novel contact interfaces will be fabricated and characterized.  The student involved in this project will contribute to the use this custom deposition tool to study the impact of preconditioning nanomaterial surfaces with a low energy ion beam prior to (and during) e-beam evap of contact metals.  The impact of the ion beam surface preparation will be studied using materials characterization tools, including Raman spectroscopy and atomic force microscopy.  In addition to performing this fabrication of custom contact interfaces to nanoelectronic devices, the student will also be trained on a low-temperature probe station and will characterize the FET devices to extract information regarding carrier transport behavior
  and overall device performance.  The student will also be expected to take part in discussions where results will be analyzed and new ideas potentially formulated for inclusion in the project.
The student will learn: 1) the ins and outs of characterizing semiconductor devices, 2) the basics of vacuum systems, and 3) data analysis skills related to understanding nanomaterial interfaces.  An ideal candidate for this project would have some previous knowledge and experience in solid-state physics including carrier transport in semiconductors, previous knowledge and/or interest in nanoelectronics and nanofabrication, and be competent in operating complex tools.  They should also be self-motivated and maintain a strong work ethic in terms of commitment and follow-through.  A collaborative, team player is a must.

Project in the Human and Autonomy Lab
Faculty Advisor: Prof. Missy Cummings
This project will look at developing technologies to help managers of small facilities passively detect drones. The project will be adapted to match the background of the selected student; a background in Java or C++ is helpful.

Deep Learning Robotic Grasps from Large Simulation Datasets
Facluty Advisor: Prof. Kris Hauser
Deep learning has had impressive success in computer vision and language understanding, but progress on robotic planning and control tasks have been limited. One reason for this slow progress is that it is difficult to generate huge amounts of data; the other is that it is unclear what network structures work well for robotic tasks. This project will leverage advancements in robust simulation of object manipulation to train and evaluate deep networks to generate robot grasps for novel objects. Students must have a background in machine learning, Python programming experience, and have experience in PyTorch, TensorFlow or related deep learning packages. Experience in robotics is a plus.

Investigation of field emission cathodes for mass spectrometry applications
Grand Challenge: Engineer the Tools of Scientific Discovery
Faculty Advisor: Prof. Jeff Glass
Currently researchers at Duke in the group of Professor Jeffrey Glass are developing a miniature mass spectrometer incorporating aperture coding, carbon nanotube field emission ion sources, and ion array detectors. Typical mass spectrometers are large and expensive limiting their use in the field. Aperture coding and field emission ion sources enable reducing the size of the instrument without sacrificing performance. It is expected that the REU student will primarily be assisting with analytical characterization of carbon nanotubes field emission ion sources using resources available at Duke's Nanomaterials and Thin Films Laboratory and Shared Materials Instrumentation Facility We envision the student taking SEM images, helping with the collection of field emission data, and potentially operating other SMIF characterization tools. In addition, the student will have the opportunity to participate in field testing of the miniature mass spectrometer prototype.



Odorant Modulation for Sanitation in the Developing World
Sponsor: Gates Foundation
Faculty Advisor: Prof. Jeff Glass, Resarch Advisors: Dr. Edgard Ngaboyamahina and Mariana Vasquez
One in three people world-wide do not have access to appropriate sanitation of human waste. This results in dirty drinking water and several million preventable deaths each year related to gastroenteritis from its consumption. This is a preventable problem, but requires rethinking how human waste should be sanitized in areas where infrastructure such as sewers, electricity and running water are not available. Our work, in collaboration with RTI International and the Bill and Melinda Gates Foundation, aims at reinventing the toilet so that it is off-grid, affordable, energy efficient, and capable of sanitizing human waste in under-developed areas.
However, malodor nuisance is a major risk factor in the adoption of effective sanitation technologies.  Foul-smelling sanitation facilities persuade people to practice open defecation in developing countries. Most common odorant molecules consist of carbon backbone ending with functional groups such as aldehydes, alcohols, or ketones. Interestingly, the change of the chemical functional group on a common carbon backbone can result in dramatically different odorant perceptions, from fruity to waxy or grassy for instance. Our previous work has demonstrated the capability to modulate malodor and generate a pleasant olfactory perception simply by applying an electrical signal to the offending liquid/gas source.
The REU project will aim at expanding the family of odorants that can be treated through the modulation process. The undergraduate student will be expected to use a variety of electrochemical (electrolysis, voltammetry and electrochemical impedance spectroscopy) and physical-chemical (chromatography and nuclear magnetic resonance spectroscopy) techniques for synthesis and characterization. The student will gain knowledge in fundamental and experimental analytical chemistry and will improve her/his laboratory skills.

Ensuring Timeliness in IoT Systems
Faculty Advisor: Prof. Miroslav Pajic
To manage complexity of modern Internet-of-Things (IoT) systems, employed platforms require the use of efficient operating systems (OS) that provide timing, performance and security guarantees, as well as support for key IoT networking and communication technologies. One example is the latest mbed OS 5.1, which incorporates a Real-Time Operating System (RTOS) in order to provide native real-time thread support to the applications running on top of the RTOS. However, the underlying scheduling is based on the well known round-robin policy, effectively preventing the use of this OS in development on safety critical IoT applications where timeliness is the first class citizen. In these systems (e.g., in industrial, medical, automotive, avionics and many other application domains), the ability to prioritize a critical task at any given moment in time, and guarantee availability of resources required to complete that task is essential.
Consequently, the goal of this project is to extend the open-source scheduler for the RTOS and provide support for a variety of commonly used real-time scheduling policies that take into account thread criticality and execution deadline constraints. The developed RTOS will then be deployed and evaluated in several case studies in automotive, industrial automation, and medical device domains, allowing the student to both learn foundations of the RTOS development as well as its use in design of real-world systems (e.g., electric vehicles, cloud-based reconfigurable industrial systems, networked implantable medical devices).

Securing autonomous systems against attacks:
Faculty Advisor: Prof. Miroslav Pajic
Most of existing autonomous systems have not been built with security in mind. Even with the proliferation of different networking technologies and the use of more open control architectures, until recently their security has usually been an afterthought. In the last few years, several incidents have clearly illustrated susceptibility of these systems to attacks, raising attention to serious security challenges. These include the StuxNet virus attack on an industrial SCADA system, as well as attacks on modern cars and RQ-170 Sentinel drone that was captured in Iran.
Relying exclusively on cyber-security techniques for securing these systems is insufficient. For example, GPS spoofing attacks to misguide a yacht or unmanned aerial vehicle (UAV) of their routes have been demonstrated  in recent years. Consequently, the goal of this project is to show how combination of security-aware control policies can be used to increase security guarantees in autonomous systems operating
in contested environments. The scope of this project will be to secure the video-based navigation of an UAV, by exploiting recently developed control techniques such as attack-resilient state estimation and active attack detection.

Learning-based Cooperative Control in Autonomous Cars
Faculty Advisor: Prof. Miroslav Pajic
The goal of the project is to create algorithms and software libraries for learning-based control  in collaborative autonomous driving. The considered system involves at least four fully-autonomous vehicles; the emphasis of this work is on dynamic collaborative path planning between fully-autonomous vehicles, with the goal of enabling multi-lane, multi-vehicle formation driving. Student efforts will focus on perception, planning, and control for autonomous navigation starting from the initial vehicle design and our ROS-based software that provides baseline autonomous vehicle operation.



Tomorrow is deadline ie Dec 15th. Please apply earliest and also make sure you send copy to sanjfort@gmail.com

We have been working with Duke University for some years now and continue to work closely with them. They have relied on our screening and also professional management to get them the best applicants for their summer internship program.

Pls circulate this to students in the CSE and ECE programs. Based on past experience, there have occasionally been students from departments like Mech Engg as well who have been considered. so pls feel free to send to other departments as well based on project descriptions below to enable more students to apply. I would suggest Aero, Mech, Civil etc.

Students can fill the online form but they MUST send copy of their applications to me sanjfort@gmail.com as we are coordinating directly with the ECE Dept. Head at Duke Univ Prof Krish and also their Director of Graduate Studies and the Senior Graduate Program Coordinator.

Any student who has completed 3rd Year at IITK by Spring 2018 is eligible to apply. The Deadline is Dec 15th. THIS IS A FIRM DEADLINE.

pls include in subject line of email - full name, dept, year, cpi
and in body of email, refer to which position(s) interested in (one or more) and also include resume copy and statement of interest.

Even though students will formally fill the online form provided by Duke (listed below), the official short list will be approved here and communicated directly to the ECE chair and his team.

besides, sending me the applications as above, students should fill the form below


https://duke.qualtrics.com/jfe/form/SV_3jyXja0gDU07sQl



The details of the program are as follows:

Program dates: May 20-July 28 2018 (end date can be adjusted if necessary; no accommodation is available before May 20)

Travel: Round trip airfare from Mumbai or other approved international airport to RDU is provided, plus ground transportation from and to RDU included (travel arranged by department)

Stipend: $500/week plus $30/day food stipend

Accommodation: Shared rooms in the JB Duke Hotel on Duke campus are provided

for project details pls see related note

The ECE department chair has agreed to my request to have the submission deadline extended to Dec 26th. Several students were requesting more time. The graduate program team under Prof Aaron Franklin still needs to give the final OK but tentatively, I urge any interested students to apply and without fail send a copy of their application to iitknyc@gmail.com or as per earlier email/note send to sanjfort@gmail.com.

Please see all three related notes on this site regarding the application process and also details on various projects available.

This is a special extension only for IITK students so please use this option.